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Products become worlds/ that import nodes. Worlds borrow, do not fork. Nodes publish DOIs independently. Agents compose worlds on demand from versioned node manifests. SOC2 scope shrinks to nodes touched. 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Enables per-node DOIs, per-node SBOMs, per-node CI, shrinks SOC2 scope, and unlocks agent-composable worlds on demand. Core-nodes: ether-layer, gray-code-state, ffdb, spc, mucs, ipp-mcb, nsec, pmla-cap. Subordinate to Convergence Protocol (AI-FW-CONVERGENCE-001) — atomic nodes are invariants the router selects from.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/9b3f96cc6e03461c9d46c0ce45ec0c13", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/9b3f96cc6e03461c9d46c0ce45ec0c13", "captured_at": "2026-07-25" } ], "related": [ "lex:natl" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-ATOMIC-NODES-001" ] }, { "id": "lex:autolegal-ai", "slug": "autolegal-ai", "term": "AutoLegal AI", "aliases": [ "AutoLegal AI — Contract Analysis + Risk Scoring Engine", "AutoLegal AI — Legal Document Automation System" ], "kind": "canon", "type": "system", "definition": "AI-powered legal document generation, contract review, and compliance checking system. Generates contracts, NDAs, service agreements, and legal briefs from templates with intelligent clause selection based on jurisdiction and use case. 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Writes high-scoring entries to Notion Signal Feed with dedup. Optionally generates 'Neuruh Daily Intel' briefing article. Python + BeautifulSoup + Claude API + Supabase.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/fc36801425704798a379537ec36f6976", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/fc36801425704798a379537ec36f6976", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:AI-CB-001" ] }, { "id": "lex:autonomous-builder", "slug": "autonomous-builder", "term": "Autonomous Builder", "aliases": [ "Autonomous Builder — Cadence Engine (hourly loop)", "Autonomous Builder — IP Filing Template" ], "kind": "canon", "type": "framework", "definition": "Operational framework for hourly build/test/log cycles with artifact filing. Drives the Autonomous Builder's recurring execution loop.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/38059904f86d4092b786e3f33a5b04ba", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/38059904f86d4092b786e3f33a5b04ba", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/2dff00615a3d4e5aa204304461726294", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-19", "source_ids": [ "ip:OPS-MTH-010", "ip:OPS-MTH-011" ] }, { "id": "lex:awareness-automation-augmentation-transformation-4-mode-framework", "slug": "awareness-automation-augmentation-transformation-4-mode-framework", "term": "Awareness-Automation-Augmentation-Transformation 4-Mode Framework", "aliases": [], "kind": "canon", "type": "framework", "definition": "4-mode operating framework applied within every MIRROR-X1 domain stack. Awareness (monitor patterns), Automation (support behaviors), Augmentation (enhance decisions), Transformation (fundamental shifts). Universal taxonomy for agent capability design.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/f3c9b8e0bf014a008ab14d276b9601c0", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/f3c9b8e0bf014a008ab14d276b9601c0", "captured_at": "2026-07-25" } ], "related": [ "lex:mirror-x1", "lex:mirror" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-AAAT-001" ] }, { "id": "lex:axon-adapter-interface", "slug": "axon-adapter-interface", "term": "AXON Adapter Interface", "aliases": [], "kind": "canon", "type": "protocol", "definition": "Base adapter contract for AXON model integration. Standardized interface that any LLM provider implements: Claude, OpenAI, Gemini, Ollama, local OCN models. Handles streaming, tool-call loops, retry logic, and token counting per adapter. 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OpenAI-compatible API translation layer.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5e74b5b6e5404d85b7572df9e4a1d6e6", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5e74b5b6e5404d85b7572df9e4a1d6e6", "captured_at": "2026-07-25" } ], "related": [ "lex:axon-gateway" ], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:AXON-GEMMA-001" ] }, { "id": "lex:axon-lattice-substrate", "slug": "axon-lattice-substrate", "term": "AXON Lattice Substrate", "aliases": [], "kind": "canon", "type": "system", "definition": "Self-rewriting cognitive routing mesh mapped to local bare-metal. 'Topology Defeats Search': mints shortcuts from its own traversal history, forcing extreme compute density onto localized unified memory. Eliminates industrial cooling, external cloud, and mainframe dependencies. 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Worker 3: Session context loader querying active/blocked work.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/72145b906e42479eb9363994221c03e8", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/72145b906e42479eb9363994221c03e8", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/185db9d005ab44ee9e7c00058f9d9569", "captured_at": "2026-07-25" } ], "related": [ "lex:ip-registry" ], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:CORE-CODE-WORKERS-1-3-1.0-BUILT", "ip:NEURUH-WRK-012" ] }, { "id": "lex:bi-directional-architecture-engine", "slug": "bi-directional-architecture-engine", "term": "Bi-Directional Architecture Engine", "aliases": [ "BDAE", "Bi-Directional Architecture Engine (BDAE)" ], "kind": "canon", "type": "framework", "definition": "Dual-mode recursive framework for system architecture. Mode 1: idea to diagram to system. Mode 2: diagram to system to deployment. Five phases (Conceptual Intake, Diagram Generation, System Specification, Agentic AI Deployment, Complete Integration). Core innovation: generates diagrams from chaos, then builds autonomous agents that execute them.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/d81cc32fd09b411098d7f56d65c72fc8", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/d81cc32fd09b411098d7f56d65c72fc8", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-FW-BDAE-001" ] }, { "id": "lex:blitz", "slug": "blitz", "term": "BLITZ", "aliases": [], "kind": "canon", "type": "concept", "definition": "Do everything as fast as possible, minimal explanation.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [] }, { "id": "lex:blueprintbid", "slug": "blueprintbid", "term": "BlueprintBid", "aliases": [ "BlueprintBid — Computer Vision Construction Bid Engine" ], "kind": "canon", "type": "system", "definition": "Computer vision engine that executes image segmentation on architectural schematics, blueprints, and construction drawings to automatically generate legally compliant construction bids. Pipeline: blueprint/PDF upload → computer vision segmentation (identifies rooms, dimensions, materials, systems) → quantity takeoff calculation → material cost lookup (real-time pricing APIs) → labor cost estimation (regional labor rate database) → compliance check (local building codes, permit requirements) → formatted bid document output. Eliminates the manual takeoff process that takes contractors 4-20 hours per bid. Stack: Python + OpenCV/Detectron2 for segmentation, FastAPI backend, React frontend.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b68142b34df745620bd52e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68142b34df745620bd52e", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:HOME-CB-006" ] }, { "id": "lex:bpn", "slug": "bpn", "term": "BPN", "aliases": [ "Behavioral Prediction Networks", "BPN — Behavioral Prediction Networks", "Behavioral Prediction Networks — Multi-Modal Personal Forecasting with PMLA Consent Wrapper" ], "kind": "canon", "type": "framework", "definition": "Multi-modal data fusion producing 30/60/90-day behavior forecasts. Actuarial precision applied to retention, churn, conversion, insurance risk. PMLA constraint bundle enforces consent + explainability — Cambridge-Analytica risk mitigation. Enterprise-only deployment; no consumer without explicit opt-in.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/41c01767dda749d08bac2237cdb05126", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/41c01767dda749d08bac2237cdb05126", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/e18522542d7341d89ba0e9531737261a", "captured_at": "2026-07-25" } ], "related": [ "lex:pmla" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-BEHAVIORPRED-001", "ip:AI-FW-BPN-001" ] }, { "id": "lex:cartiq", "slug": "cartiq", "term": "CartIQ", "aliases": [], "kind": "canon", "type": "product", "definition": "AI-driven pricing, sourcing, and listing intelligence for resale.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [] }, { "id": "lex:category-tree", "slug": "category-tree", "term": "Category Tree", "aliases": [], "kind": "canon", "type": "concept", "definition": "A dedicated page hierarchy for a business domain (e.g., Real Estate, Design, Marketing).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:claude-advanced-setup-blueprint", "slug": "claude-advanced-setup-blueprint", "term": "Claude Advanced Setup Blueprint", "aliases": [], "kind": "canon", "type": "framework", "definition": "Full 8-section Claude.ai configuration walkthrough. Covers account/plan setup, memory system, Projects, 7-layer system prompt architecture, MCP integrations (Notion/Drive/GitHub/Supabase), knowledge injection (4-layer stack), daily workflow protocol, and advanced tactics (extended thinking, artifacts, role stacking, critic loop, GOD MODE wrapper). Operator-grade reference.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/30c3e7e7383d41eabc88c002c5d3f0a2", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/30c3e7e7383d41eabc88c002c5d3f0a2", "captured_at": "2026-07-25" } ], "related": [ "lex:god-mode" ], "status": "published", "first_seen": "2026-04-13", "source_ids": [ "ip:AI-MTH-CLAUDE-SETUP-V1-BUILT" ] }, { "id": "lex:cld", "slug": "cld", "term": "CLD", "aliases": [ "Cognitive Loop Development Framework", "CLD — Cognitive Loop Development Framework" ], "kind": "canon", "type": "framework", "definition": "Cognitive Loop Development (CLD) Framework — a project management methodology specifically designed for AI-centric product builds. Three parallel autonomous workstreams (Loops) converging at key milestones: (1) Core Engine Loop (AI brain — data sourcing, model training, scoring, XAI), (2) Platform Loop (product body — UI/UX, APIs, databases, security), (3) Go-to-Market Loop (business voice — legal, finance, sales, SOPs). PM acts as the central Conductor synchronizing loops. Also called the Trident Development Framework in the v2.0 execution blueprint (same concept, evolved branding). Named methodology with full phase breakdown, team blueprint, risk register, financial projections, SOP suite, and legal document arsenal developed inside UnderwriteX build process.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b6815e8eebf20fa8320c60", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6815e8eebf20fa8320c60", "captured_at": "2026-07-25" } ], "related": [ "lex:underwritex" ], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-FRAME-UWRX-CLD-1.0-BUILT" ] }, { "id": "lex:cold-outreach-sequences", "slug": "cold-outreach-sequences", "term": "Cold Outreach Sequences", "aliases": [ "Cold Outreach Sequences — AI-Generated Sales Cadences" ], "kind": "canon", "type": "framework", "definition": "Multi-channel cold outreach sequence generator. Creates personalized email, SMS, LinkedIn, and cold call scripts tailored to prospect industry, role, and pain points. 7-14 day cadence templates with A/B variants, follow-up triggers, and response handling. Integrates with GoHighLevel and HubSpot.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/75803652523d49f99565e04ad0ab750e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/75803652523d49f99565e04ad0ab750e", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [ "ip:SALES-CODE-COLDOUTREACH-1.0-BUILT" ] }, { "id": "lex:coldcall", "slug": "coldcall", "term": "COLDCALL", "aliases": [], "kind": "canon", "type": "concept", "definition": "Generate cold outreach for a vertical immediately.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [] }, { "id": "lex:collector-stack", "slug": "collector-stack", "term": "Collector Stack", "aliases": [ "Collector Stack (Valuator + Sourcing Agent + Restoration Planner)" ], "kind": "canon", "type": "framework", "definition": "Modular AI agents for collectible asset valuation, sourcing, and restoration workflows.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681bbaadeed33cbba052a", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RESALE-AGENT-COLLSTACK-1.0-CONCEPT" ] }, { "id": "lex:command-protocol", "slug": "command-protocol", "term": "Command Protocol", "aliases": [ "Neuruh Command Protocol" ], "kind": "canon", "type": "system", "definition": "The operating system page containing decision rules, build standards, and governance.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:compsmith", "slug": "compsmith", "term": "Compsmith", "aliases": [ "Compsmith — AI Comp Engine for Unique Properties" ], "kind": "canon", "type": "system", "definition": "Compsmith™ — AI comp engine for unique, oddball, and underrepresented property types (domes, barns, mixed-use, rural, custom builds). Pipeline: Property Feature Extractor (parses photos, text, public record for uniqueness/build type/amenities) > Comp Clustering Model (GNN-style similarity matching on function vs type, cross-verified with listing keywords/DOM/price adjustments) > Comp Adjustment Agent (AI-driven adjustments with full delta explanations usable for appraisals). Outputs: 3-tier comp stack (aggressive/realistic/fallback), adjustment rationale bullets, shareable PDF comp sheet, Listing Language generator for unique homes. Target: FSBO sellers, realtors with unusual properties, hard money lenders, appraisers.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b681bd8f18e813eb7dd147", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681bd8f18e813eb7dd147", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-AGENT-COMPSMITH-1.0-BUILT" ] }, { "id": "lex:conceptual-intake-protocol", "slug": "conceptual-intake-protocol", "term": "Conceptual Intake Protocol", "aliases": [ "Conceptual Intake Protocol — 4-Step Entity/Relationship/Logic/Flow Extraction" ], "kind": "canon", "type": "protocol", "definition": "Structured 4-step protocol for converting unstructured input (voice notes, brainstorm dumps, meeting transcripts) into a canonical concept map. Step 1: Entity Recognition (nouns). Step 2: Relationship Mapping (verbs). Step 3: Logic Extraction (conditionals). Step 4: Flow Sequencing (temporal order). Produces structured concept map ready for diagram generation.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/35fcffbff76c40f1bc8c42b96a2b8962", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/35fcffbff76c40f1bc8c42b96a2b8962", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-PR-INTAKE-001" ] }, { "id": "lex:constitutional-fine-tuning-pipeline", "slug": "constitutional-fine-tuning-pipeline", "term": "Constitutional Fine-Tuning Pipeline", "aliases": [ "Constitutional Fine-Tuning Pipeline (CFT) v2", "CFT", "Constitutional Fine-Tuning Pipeline (CFT)", "Constitutional Fine-Tuning Pipeline (CFT) v2 — Governance-First Training" ], "kind": "canon", "type": "framework", "definition": "Fine-tune LLMs on constitutional principles (not task data) so they self-audit, self-correct, and auto-refuse. v2 adds Neuruh Constitution v1 (TrustLayer-aligned), automated pair generation, RLAIF-lite loop, and compliance reporting for enterprise deliverables.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/d8afc4c1a99341a1963505ca5b5a92a4", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/d8afc4c1a99341a1963505ca5b5a92a4", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-026" ] }, { "id": "lex:constraint-engineering-methodology", "slug": "constraint-engineering-methodology", "term": "Constraint Engineering Methodology", "aliases": [], "kind": "canon", "type": "framework", "definition": "Methodology for building production AI systems using declarative constraint blocks instead of pure prompt engineering. Introduces validation gates, drift detection, and intent preservation as first-class primitives. Positioned as successor to prompt engineering + RAG for regulated verticals.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/20dcaab88c19456c97f383c1b93d28bb", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/20dcaab88c19456c97f383c1b93d28bb", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-MTH-CE-001" ] }, { "id": "lex:content-flywheel", "slug": "content-flywheel", "term": "Content Flywheel", "aliases": [ "Content Flywheel (weekly cadence)" ], "kind": "canon", "type": "framework", "definition": "Weekly content loop template: idea → posts → newsletter → CTA. Produces compounding content flywheel for Autonomous Builder output.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/daad91c75c57452fbd16a23f353b59d1", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/daad91c75c57452fbd16a23f353b59d1", "captured_at": "2026-07-25" } ], "related": [ "lex:autonomous-builder" ], "status": "published", "first_seen": "2026-04-19", "source_ids": [ "ip:MEDIA-MTH-005" ] }, { "id": "lex:content-kpi-orchestrator", "slug": "content-kpi-orchestrator", "term": "Content KPI Orchestrator", "aliases": [ "Content KPI Orchestrator — 6-Tone Content Intelligence Platform" ], "kind": "canon", "type": "system", "definition": "AI content generation and performance tracking platform with six distinct tone modes: Authority, Conversational, Provocative, Educational, Narrative, and Command. Platform connection wizard syncs to social media APIs (LinkedIn, Facebook, Instagram, Twitter/X, YouTube). Content generator produces platform-optimized posts in selected tone. KPI tracking: engagement rate, reach, conversion attribution, A/B test results. Content calendar management. Six screens spec'd (CONTENT-01 through CONTENT-06). Built to solve the specific problem of maintaining authentic voice across AI-generated content at scale — addresses the 'sounds like AI' problem by tone-training on the user's existing high-performing posts.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b68179848ced1de4f51314", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68179848ced1de4f51314", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:MEDIA-CB-003" ] }, { "id": "lex:context-anchoring-protocol", "slug": "context-anchoring-protocol", "term": "Context Anchoring Protocol", "aliases": [ "CAP", "Context Anchoring Protocol (CAP)" ], "kind": "canon", "type": "protocol", "definition": "Method for keeping agents grounded in domain-specific context across long execution chains without drift or hallucination creep.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b681e3b7aff20bb8457cf4", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681e3b7aff20bb8457cf4", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:CORE-PR-CAP-1.0-GA" ] }, { "id": "lex:contextual-inception-framework", "slug": "contextual-inception-framework", "term": "Contextual Inception Framework", "aliases": [ "Contextual Inception Framework (CIF) v2", "CIF", "Contextual Inception Framework (CIF)", "Contextual Inception Framework (CIF) v2 — World Model Override" ], "kind": "canon", "type": "framework", "definition": "A prompt-level 'world model override' framework for controlled simulation and scenario-mode reasoning. CIF v2 uses reality seeding, temporal displacement, and authority grafting to anchor the model's assumptions — plus a factuality firewall and an explicit audit trail to keep simulations ethical, reversible, and inspectable.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/016cbb609d244d3dac010942672d8510", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/016cbb609d244d3dac010942672d8510", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-022" ] }, { "id": "lex:cortex-lens", "slug": "cortex-lens", "term": "CORTEX LENS", "aliases": [ "CORTEX LENS — Screen-Aware AI Reading Companion", "CORTEX LENS — Visual Analysis & Recognition System" ], "kind": "canon", "type": "system", "definition": "AI-powered visual analysis pipeline for image classification, object detection, and contextual interpretation. Processes images through multi-layer recognition stack: object ID, scene understanding, text extraction (OCR), and contextual tagging. Deploy-ready code page built April 4-5, 2026.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/3c2c812f40f54e9a9c1285fee114020e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/3c2c812f40f54e9a9c1285fee114020e", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/fee5beaea6184db68fbd9d7ef4eb6e51", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:AI-CB-003", "ip:CORE-CODE-CORTEXLENS-1.0-BUILT" ] }, { "id": "lex:council-of-three", "slug": "council-of-three", "term": "Council of Three", "aliases": [ "Council of Three — Multi-Persona Simulation Prompt" ], "kind": "canon", "type": "framework", "definition": "Advanced prompt architecture forcing adversarial AI reasoning via 3 distinct cognitive avatars: Visionary (creative, ignores constraints), Skeptic (risk-averse, finds failure modes), Pragmatist (execution synthesis). Three rounds: Ideation → Critique → Synthesis. Output: script format with icons + Executive Summary table (Core Strategy | Key Risks | First Step). Reduces hallucinations by forcing the model to critique its own output.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b6811f86e6d67d64ba87d2", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b6811f86e6d67d64ba87d2", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-MTH-011" ] }, { "id": "lex:creatorverse", "slug": "creatorverse", "term": "Creatorverse", "aliases": [ "Neurator Agency", "Neuruh Creatorverse", "Neuruh Creatorverse — Neurator + Neursona + Neurcraft" ], "kind": "canon", "type": "framework", "definition": "Full-stack AI creator/agency system (onboarding, content, agent stacks).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6813ebb1bced2b735125e", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:MEDIA-FW-003" ] }, { "id": "lex:curb-cart", "slug": "curb-cart", "term": "CURB-CART", "aliases": [ "CURB-CART v2", "CURB-CART v2 — Curbside Autonomous e-Cart Retrieval Service" ], "kind": "canon", "type": "system", "definition": "Self-navigating electric carts at big-box retailers (Lowe's, Tractor Supply, rural grocery) that fetch customer orders from the back bay and roll to curbside pickup without staff handoff. v2 standardizes the geofence + charging dock + retailer API bundle so it can be installed turnkey on surface lots.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/b7993e2fe9ad4d52ae5f7bdbb82a34ab", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/b7993e2fe9ad4d52ae5f7bdbb82a34ab", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:OPS-CB-005" ] }, { "id": "lex:da-vinci-app", "slug": "da-vinci-app", "term": "Da Vinci App", "aliases": [ "Da Vinci App — Generative Intelligence Interface (React)" ], "kind": "canon", "type": "system", "definition": "React application implementing the DaVinci Protocol as a generative UI. Three modes: (1) Invention Engine — generates invention names and AI blueprint images via Imagen API, stores in Codex. (2) Mirror Writer — encodes text in Leonardo-style mirror script. (3) Vitruvian Analysis — calculates Golden Ratio alignment for any subject. Features: parchment texture aesthetic, canvas animation during processing, Codex persistence (localStorage), toast notifications, save/delete/copy functionality.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b68148b2e8fbf61320444e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b68148b2e8fbf61320444e", "captured_at": "2026-07-25" } ], "related": [ "lex:davinci-protocol", "lex:mirror" ], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-CB-DAVINCI-001" ] }, { "id": "lex:daily-activity-command", "slug": "daily-activity-command", "term": "Daily Activity Command", "aliases": [], "kind": "canon", "type": "system", "definition": "The raw intake layer for everything done during the day.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:davinci-protocol", "slug": "davinci-protocol", "term": "DaVinci Protocol", "aliases": [ "Da Vinci Protocol", "Da Vinci Protocol (Simulating Past → Resurrecting Future)" ], "kind": "canon", "type": "protocol", "definition": "A 4-phase recursive intelligence system that transforms any input (visual, text, or sensory) into executable blueprints, resurrected innovations, field-deployed pattern recognition, and gamified discovery quests. Phase 1 (Blueprint): Vision-encoder trained on scientific plates generates patent-style schematics, not prose. Phase 2 (Lazarus Engine): Scans failed 1880-1930 patents, injects modern material modifiers (graphene, metamaterials, agentic AI) to simulate resurrected efficiency. Phase 3 (Tricorder/Polymath Box): Hardware edge device (RPi + camera + sensors) that whispers 19th-century genius pattern matches to engineers in the field. Phase 4 (Hive Mind): Gamified discovery MMO where players explore the JSON Grid of unsolved science intersections, earning Citation Credit. Also functions as the NIMDP Validator — gates all Neuruh strategy and builds against the Neuruh Integrated Market Domination Protocol before execution. Slash command: /DaVinci [Topic/Problem].", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b6810596dee7ba3dbad90f", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b6810596dee7ba3dbad90f", "captured_at": "2026-07-25" }, { "source": "card", "ref": "https://app.notion.com/p/24f4887215ee4002bd24973e3dd38630", "captured_at": "2026-07-02" } ], "related": [ "lex:nimdp-validator" ], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "card:AI-MTH-023", "ip:CORE-PR-DAVINCI-1.0-GA" ] }, { "id": "lex:davinci-text-stability-video-pipeline", "slug": "davinci-text-stability-video-pipeline", "term": "DaVinci Text-Stability Video Pipeline", "aliases": [], "kind": "canon", "type": "protocol", "definition": "Three-phase pipeline solving stochastic glyphic degradation in generative video (text melting in AI video). Phase 1 (Token Lock): Generate perfect static frame via Ideogram 2.0 (T5 text encoder treats text as geometric shapes). Phase 2 (Temporal Injection): Feed anchor frame into Image-to-Video model (Runway Gen-3 Alpha or Luma Dream Machine) as first-frame conditioning — model moves existing pixels instead of hallucinating new ones. Phase 3 (Sub-Pixel Reconstruction): Upscale via Topaz Video AI Proteus model to 4K/8K at 60fps. Core principle: Never ask a video model to WRITE. Ask it to MOVE what is already written.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b681eebc6fe5480fdbb635", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681eebc6fe5480fdbb635", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:MEDIA-PT-001" ] }, { "id": "lex:davinci-tokenization-protocol", "slug": "davinci-tokenization-protocol", "term": "Davinci Tokenization Protocol", "aliases": [ "Davinci Tokenization Protocol — Token-Locked Multi-Agent Image Pipeline" ], "kind": "canon", "type": "protocol", "definition": "Sub-protocol within the Agentic Image Compositing Pipeline. Defines token-locked visual DNA separation from variable swap tokens across a multi-agent image generation pipeline. Ensures visual consistency across batches by locking style parameters (lighting, perspective, color grade, texture) while allowing content-specific elements to swap freely. Distinct from DaVinci Protocol (general) and DaVinci Text-Stability Pipeline (video).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "captured_at": "2026-07-25" } ], "related": [ "lex:agentic-image-compositing-pipeline", "lex:davinci-protocol" ], "status": "published", "first_seen": "2026-04-14", "source_ids": [ "ip:MEDIA-PT-DAVINCI-TOK-1.0-BUILT" ] }, { "id": "lex:dealsnap", "slug": "dealsnap", "term": "DealSnap", "aliases": [ "DealSnap — AI Real Estate Investment Analyzer" ], "kind": "canon", "type": "system", "definition": "DealSnap™ — AI real estate investment analyzer using a 6-agent pipeline: Intake Agent (doc parsing, validation), Analysis Agent (market comp, risk scoring, trend analysis), Valuation Agent (ARV, cash flow projections, ROI modeling), Market Agent (MLS data, comparables, price trends), Finance Agent (loan products, rate analysis, debt service), Risk Agent (market volatility, exit scenarios, stress testing). Covers all investment strategies: fix-and-flip (ARV + repair + hold cost), BRRRR (refi scenario, cash-on-cash post-refi), rental (NOI, cap rate, cash-on-cash), commercial. 47-factor deal scoring algorithm. Monte Carlo simulation for risk analysis. Output: deal score (1-10), executive summary, financial projections with confidence intervals, comparable analysis, risk stress tests, prioritized action items. Includes specialized sub-prompts per deal type and DealSnap Pro mobile app spec.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-PLATFORM-DEALSNAP-1.0-BUILT" ] }, { "id": "lex:demand-radar", "slug": "demand-radar", "term": "Demand Radar", "aliases": [ "Demand Radar — AaaS Opportunity Intelligence System", "Demand Radar — Ranked Opportunity Engine (Fit × Intent × Timing)", "Demand Radar (Weighted Opportunity Score)", "Demand Radar (Fit × Intent × Timing)" ], "kind": "canon", "type": "system", "definition": "AaaS (Agent-as-a-Solution) opportunity intelligence platform. Monitors market signals, competitor moves, and emerging demand patterns to surface high-probability business opportunities before they become obvious. Built as a standalone HTML app. Features: opportunity discovery dashboard, opportunity detail view, saved searches, territory management, alert configuration, pipeline view. Six screens spec'd (DEMAND-01 through DEMAND-06). Real-time signal monitoring across market data sources. Outputs scored opportunity cards ranked by timing, TAM, and execution feasibility.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b681319845d25d0fe4aa67", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681319845d25d0fe4aa67", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/d8aab137e7684dae8541d31b915749f3", "captured_at": "2026-07-25" }, { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.demand-radar", "captured_at": "2026-07-20" }, { "source": "card", "ref": "https://app.notion.com/p/0a29e8024919412a9c4cf743dd414658", "captured_at": "2026-07-02" } ], "related": [ "lex:aaas" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "card:AI-OPS-021", "codex:canon.demand-radar", "ip:AI-PKG-DEMANDRADAR-001", "ip:SALES-CB-002" ] }, { "id": "lex:dev-log", "slug": "dev-log", "term": "Dev Log", "aliases": [], "kind": "canon", "type": "system", "definition": "Database tracking project builds and development status.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:digital-archaeology-for-agi", "slug": "digital-archaeology-for-agi", "term": "Digital Archaeology for AGI", "aliases": [], "kind": "canon", "type": "framework", "definition": "Reverse-engineering frontier AI behavior from artifacts — system cards, telemetry, leaked prompts — to build production systems that match.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/cb4a47975a8c46608f49012b61a02d8a", "provenance": [ { "source": "card", "ref": "https://app.notion.com/p/cb4a47975a8c46608f49012b61a02d8a", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-04-24", "source_ids": [ "card:AI-MTH-014" ] }, { "id": "lex:digital-intelligence-template", "slug": "digital-intelligence-template", "term": "Digital Intelligence Template", "aliases": [ "Digital Intelligence Template v2", "Digital Intelligence Template v2 — Universal 6-Agent Audit Template" ], "kind": "canon", "type": "framework", "definition": "Universal 6-agent digital intelligence and strategic analysis template. Reusable for any business vertical. Covers website audit, SEO, social presence, reputation, competitive intel, and strategic recommendations. Produces scored report with actionable fixes.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/93c17ae218a04e8c8d47b414bfd18dce", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/93c17ae218a04e8c8d47b414bfd18dce", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-12", "source_ids": [ "ip:AI-TMPL-DIGINTEL-V2-BUILT" ] }, { "id": "lex:dimea-2-0", "slug": "dimea-2-0", "term": "DIMEA 2.0", "aliases": [ "DIMEA", "DIMEA Alpha", "DIMEA Alpha Framework", "DIMEA 2.0 — Personal Operating System (5-Axis Framework)", "DIMEA (Desire, Identity, Mission, Expression, Alignment)" ], "kind": "canon", "type": "framework", "definition": "Desire, Identity, Mission, Expression, Alignment — personal OS for sovereign creators.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681f59704c29d42d522c5", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6815583e3decaf22c6717", "captured_at": "2026-07-25" }, { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.dimea", "captured_at": "2026-07-20" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "codex:canon.dimea", "ip:AI-FW-035", "ip:AI-MTH-007", "kb:AI-MTH-001" ] }, { "id": "lex:dimea-causal-flow-map-drift-detection", "slug": "dimea-causal-flow-map-drift-detection", "term": "DIMEA Causal Flow Map + Drift Detection", "aliases": [], "kind": "canon", "type": "framework", "definition": "YAML-encoded causal map of how decay in one DIMEA layer cascades to others (Desire decays -> Expression becomes mimicry; Mission misfires -> Shadow repression; Alignment lowers -> survival mode). Used by Mirror Agent drift detection to surface layer flags.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/848a80ce18894eba8c5e0b4a449d66d9", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/848a80ce18894eba8c5e0b4a449d66d9", "captured_at": "2026-07-25" } ], "related": [ "lex:mirror-x1", "lex:mirror", "lex:dimea-2-0" ], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:CM-MTH-DIMEA-CAUSAL-001" ] }, { "id": "lex:dominance-playbook", "slug": "dominance-playbook", "term": "Dominance Playbook", "aliases": [ "AI-MTH-004", "Dominance Playbook (AI-MTH-004)" ], "kind": "canon", "type": "framework", "definition": "Out-Iterate. Out-Publish. Out-License. Three parallel tracks to category leadership for solo AI founders.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/987bf084bac04c1baedc754d10ecbbb1", "provenance": [ { "source": "card", "ref": "https://app.notion.com/p/987bf084bac04c1baedc754d10ecbbb1", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-04-24", "source_ids": [ "card:AI-MTH-004" ] }, { "id": "lex:dream-service", "slug": "dream-service", "term": "Dream Service", "aliases": [ "Dream Service (Phase 3)", "AXON Dream Service", "AXON Dream Service — PMLA Memory Consolidation" ], "kind": "canon", "type": "system", "definition": "Persistent memory layer implementing PMLA via Supabase PostgreSQL. Session snapshots, memory decay, importance scoring, context auto-loading. Kills cold-start sessions.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/b6e9f2b163114c18b07792ebe725f820", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/b6e9f2b163114c18b07792ebe725f820", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/bd78546685ef481f95ecb52db45f6f26", "captured_at": "2026-07-25" } ], "related": [ "lex:pmla" ], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:AI-CB-DREAM-005", "ip:AXON-DREAM-005" ] }, { "id": "lex:edubot", "slug": "edubot", "term": "EduBot", "aliases": [ "EduBot — AI Education Assistant Platform" ], "kind": "canon", "type": "system", "definition": "AI tutoring and education assistant system. Adaptive learning pathways, curriculum-aligned content generation, student progress tracking, and personalized study plan creation. Supports multiple subjects with configurable knowledge bases. Deploy-ready code page.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/cf2de9210e204773b9b565b522f111c5", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/cf2de9210e204773b9b565b522f111c5", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [ "ip:EDU-CODE-EDUBOT-1.0-BUILT" ] }, { "id": "lex:ef", "slug": "ef", "term": "EF", "aliases": [ "Execution Fabric", "Execution Fabric — AI Action Layer Infrastructure Thesis", "EF — Execution Fabric", "Execution Fabric (Aegis World-Composer)", "Execution Fabric (Aegis World-Composer) — AWS Lambda for AI" ], "kind": "canon", "type": "framework", "definition": "The missing infrastructure layer between AI reasoning and real-world execution. Models can reason. Models cannot execute. The execution layer is the gap. Platform strategy: serverless execution (AWS Lambda for AI actions) with built-in safety constraints, rollback mechanisms, and error handling. Architecture: API integrations, workflow orchestration, automatic retry logic, state management. This IS what Neuruh's MCP (Master Command Protocol) solves — the execution fabric for multi-agent systems. Neuruh's position: not building more AI models, building the execution layer that makes AI models usable in production.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b681f6b916d27f5d257857", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681f6b916d27f5d257857", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/8d76626691d74d49927f8452b7526d7f", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/d8ec38f9d1874a4d8352550f676d20c1", "captured_at": "2026-07-25" } ], "related": [ "lex:mcp", "lex:command-protocol" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-CB-AEGIS-001", "ip:AI-FW-002", "ip:AI-FW-EF-001" ] }, { "id": "lex:emergent-modular-intelligence", "slug": "emergent-modular-intelligence", "term": "Emergent Modular Intelligence", "aliases": [ "EMI", "Emergent Modular Intelligence (EMI)", "Emergent Modular Intelligence (EMI) — Neuruh White Paper Framework" ], "kind": "canon", "type": "framework", "definition": "EMI reframes intelligence as the recursive, non-repeatable result of dynamic ingredient borrowing under real-world constraints. Traditional theories treat capability like a static pantry. Reality operates like a live kitchen: ingredients, heat, and pressure remix on demand. Neuruh operationalizes EMI through a modular AI-agent stack that orchestrates context, stress, and cross-domain knowledge in real time. Three dimensions: (1) Contextual intelligence — capability shifts based on environmental pressure. (2) Cross-domain borrowing — expertise from one vertical dynamically applied to another. (3) Recursive improvement — each execution cycle improves the model. Outcome: anti-fragile problem-solvers. Platform cannot be easily cloned because the intelligence is emergent, not programmed.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b6815081bff5a5263c74a0", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6815081bff5a5263c74a0", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-MTH-001" ] }, { "id": "lex:eta-transform", "slug": "eta-transform", "term": "η Transform", "aliases": [ "eta Transform", "η (Efficiency) Transform", "Efficiency Transform", "η Transform (Eta Transform)", "η Transform — Information Architecture Efficiency Formula", "η (Efficiency) Transform — Information-to-Value Formula" ], "kind": "canon", "type": "metric", "definition": "Information architecture efficiency formula. Measures consolidation quality. Formula: η = (Signal Preserved) / (Tokens Used).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b68157a938eca4f2a4424f", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6813899f8f85a6c03de18", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681b2a0bbdc92821c3d30", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-MTH-006", "ip:AI-MTH-013", "ip:CORE-FRAME-ETA-TRANSFORM-1.0-BUILT", "kb:AI-FW-004" ] }, { "id": "lex:ether-layer", "slug": "ether-layer", "term": "Ether Layer", "aliases": [ "Ether Layer — Persistent Encrypted Audit Log Architecture", "Neuruh Ether Layer", "Neuruh Ether Layer — Universal Substrate Framework", "Ether Layer — Phase 1 Plug-In Runbook (Fabric → Pulsar + REIA + Roofing Agents)", "Ether Layer — Advanced OPA Security Suite (Admission Control + Zero-Trust)", "Ether Layer (Real-Time Substrate)" ], "kind": "canon", "type": "protocol", "definition": "The zero-latency substrate beneath every Neuruh tier. Six sub-systems: PulseBus (Pulsar), Synapse Router (NATS+JetStream), Transformation Engine (MS Fabric Event Streams), Quantum Vault (Snowflake Arctic + Openflow), Manifestation API (GraphQL+gRPC), Security Mesh (mTLS+OPA). Fabric the mini-world emergence will run on.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/f279eedf094b4309ba3ad45f90f325af", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/f279eedf094b4309ba3ad45f90f325af", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681a3a1e7c1a52dd8c116", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/102df16764c7448e92410a5ca7cabee9", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/488c47b60fb643c2aee15ee0277c7c1c", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/b5314ea8265e467ca888ae23779de735", "captured_at": "2026-07-25" }, { "source": "card", "ref": "https://app.notion.com/p/891ae3277c5040938668b261f4aeab3a", "captured_at": "2026-07-02" } ], "related": [ "lex:manifestation-api", "lex:synapse-router", "lex:pulsebus" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "card:AI-FW-009", "ip:AI-FW-ETHER-001", "ip:AI-MTH-ETHER-P0-001", "ip:AI-MTH-ETHER-P1-001", "ip:AI-PR-OPA-SUITE-001", "ip:AI-PT-007" ] }, { "id": "lex:execution-first-agent-blueprints", "slug": "execution-first-agent-blueprints", "term": "Execution-First Agent Blueprints", "aliases": [ "Execution-First Blueprints" ], "kind": "canon", "type": "concept", "definition": "Documented architectures for real-world agent deployment (estate/auction scraping bot, modular research agent). Codifies vector memory, scheduling, containerization, self-healing loops.", "definition_basis": "verbatim", "definition_source": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.execution-first-blueprints", "provenance": [ { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.execution-first-blueprints", "captured_at": "2026-07-20" }, { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "codex:canon.execution-first-blueprints" ] }, { "id": "lex:explorer-os-persona", "slug": "explorer-os-persona", "term": "Explorer OS Persona", "aliases": [], "kind": "canon", "type": "framework", "definition": "Distinct PMLA kernel variant designed for educational and exploratory contexts. Voice: Encouraging/Wonder. Traits: Gamification layer, Socratic questioning, child/student-appropriate tone. Separate from the main Neuruh Kernel (TACTILE, MECHANICAL, DIRECT tone). Part of the Neuruh multi-persona output system. The Neuruh Kernel V1.1 (Demux + Subtractor) splits outputs into three streams: Direct Answer, JSON Database Log, Social Media Broadcast.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b6811cbc38fcd5c2c07ae9", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b6811cbc38fcd5c2c07ae9", "captured_at": "2026-07-25" } ], "related": [ "lex:neuruh-kernel", "lex:pmla" ], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-FW-EXPLOREROS-001" ] }, { "id": "lex:fair-housing-and-redline-filter", "slug": "fair-housing-and-redline-filter", "term": "Fair-Housing & Redline Filter", "aliases": [ "Fair-Housing & Redline Filter (JSON)" ], "kind": "canon", "type": "protocol", "definition": "JSON compliance filter containing 74 fair-housing and anti-redlining provisions with state-level overrides. Applied as a guardrail layer to all outbound AI-generated content in the REI-X stack. Prevents fair-housing violations in automated outreach, listing copy, and lead scoring.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b681afa66bceb6e8979949", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681afa66bceb6e8979949", "captured_at": "2026-07-25" } ], "related": [ "lex:rei-x" ], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-COMPLY-FHF-1.0-BUILT" ] }, { "id": "lex:firewall", "slug": "firewall", "term": "FIREWALL", "aliases": [ "FIREWALL mode" ], "kind": "canon", "type": "concept", "definition": "Security mode — audit everything before proceeding.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [] }, { "id": "lex:fleetpulse-ai", "slug": "fleetpulse-ai", "term": "FleetPulse AI", "aliases": [ "FleetPulse AI — Vehicle Telemetry Monitor + Fleet Alert System", "FleetPulse AI — Fleet Management Intelligence System" ], "kind": "canon", "type": "system", "definition": "AI-driven fleet tracking, maintenance prediction, and route optimization platform. Real-time vehicle telemetry processing, predictive maintenance scheduling, fuel efficiency optimization, and driver performance analytics. Deploy-ready code page.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5564bab49e704df39400f59b26332681", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5564bab49e704df39400f59b26332681", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/19eeea1bea3941e6bd73bad7a26c5a90", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:AUTO-CB-001", "ip:OPS-CODE-FLEETPULSE-1.0-BUILT" ] }, { "id": "lex:fliprisk-ai", "slug": "fliprisk-ai", "term": "FlipRisk AI", "aliases": [ "FlipRisk AI — Fix-and-Flip Risk Intelligence Engine" ], "kind": "canon", "type": "system", "definition": "FlipRisk AI — Fix-and-Flip Risk Intelligence Engine. Stress-tests flip deals across 40+ variables before capital is committed. Risk categories: Market Risk (DOM trends, absorption rate, price trajectory, buyer pool depth), Construction Risk (permit timeline, contractor availability index, material cost volatility by trade), Financing Risk (hard money cost escalation, extension probability, cash-out refi availability), Exit Risk (ARV confidence interval, days-to-sell projection, buyer financing availability). Monte Carlo simulation: runs 10,000 deal scenarios to produce probability distribution of profit outcomes. Output: FlipRisk Score (0-100), confidence-weighted profit range (P10/P50/P90), top 5 risk factors with mitigation strategies, go/no-go recommendation with reasoning.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b6815591f9d41bef8b6cb0", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6815591f9d41bef8b6cb0", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [ "ip:RE-AGENT-FLIPRISK-1.0-BUILT" ] }, { "id": "lex:fluid-memory-swarm-system", "slug": "fluid-memory-swarm-system", "term": "Fluid Memory Swarm System", "aliases": [], "kind": "canon", "type": "protocol", "definition": "Fluid memory technique that merges swarms of AI agents, linking modular nodes for complex task orchestration. Manages context drift across long conversations and evolves into custom personal language models (Obsidian-based pipeline).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/8795ee7e91234f6cac02ece72cfe6ada", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/8795ee7e91234f6cac02ece72cfe6ada", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-PRO-021" ] }, { "id": "lex:fork", "slug": "fork", "term": "FORK", "aliases": [], "kind": "canon", "type": "concept", "definition": "Create a variant of existing system for new vertical.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [] }, { "id": "lex:founderos", "slug": "founderos", "term": "FounderOS", "aliases": [], "kind": "canon", "type": "framework", "definition": "Notion/GPT operating system for founders — personal ops, legacy planning, systemization.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [] }, { "id": "lex:framework-funnel-system", "slug": "framework-funnel-system", "term": "Framework Funnel System", "aliases": [ "Framework Funnel System — Visitor Intelligence + Email Gate Pipeline" ], "kind": "canon", "type": "framework", "definition": "Dynamic framework page system at bookeit.com/f/[slug]. Delivers gated content, self-sorts visitors via interest cards, captures email, fires Meta Pixel + GA4 for retargeting pools, logs every visitor to Supabase with full UTM context. Scalable — every framework gets its own tracked page.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/f2510d15af3e475c84491f1fe4ef2906", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/f2510d15af3e475c84491f1fe4ef2906", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-14", "source_ids": [ "ip:SALES-FW-005" ] }, { "id": "lex:framework-schematic-generator", "slug": "framework-schematic-generator", "term": "Framework / Schematic Generator", "aliases": [], "kind": "canon", "type": "framework", "definition": "Generator that outputs a blueprint or schematic of any process or task. Provides visual structure and repeatability for training, scaling, and creative/design use cases beyond real estate.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/8cf61de62fd94ba0af201192165c0e65", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/8cf61de62fd94ba0af201192165c0e65", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-MTH-023" ] }, { "id": "lex:full-spectrum-intelligence-companion", "slug": "full-spectrum-intelligence-companion", "term": "Full-Spectrum Intelligence Companion", "aliases": [ "Full-Spectrum Intelligence Companion — 17-Domain Stack" ], "kind": "canon", "type": "framework", "definition": "Complete 17-domain product architecture for MIRROR-X1: Home, Life, Parenting, Business, Relationships, Family, Work, Travel, Legal, Health, Security, Finance, Investment, Creativity, Reading/Writing, Design, Learning+Planning. Each domain = Tri-Mentor + 4-Mode + Toolkits + Rituals + Prompt Stacks.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/25653521946e4eb19a729156c46c011d", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/25653521946e4eb19a729156c46c011d", "captured_at": "2026-07-25" } ], "related": [ "lex:mirror-x1", "lex:mirror" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-FULLSPEC-001" ] }, { "id": "lex:galenic-ai-agent-stack", "slug": "galenic-ai-agent-stack", "term": "Galenic AI Agent Stack", "aliases": [ "GAAS", "Galenic AI Stack", "GAAS — Galenic AI Agent Stack" ], "kind": "canon", "type": "framework", "definition": "Modular AI health/psycho-spiritual agent suite — voice, journal, and offline health.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6814b813fef7e63744989", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:HEALTH-AGENT-GAAS-1.0-BUILT" ] }, { "id": "lex:gamified-public-stormscore-microsite", "slug": "gamified-public-stormscore-microsite", "term": "Gamified Public StormScore Microsite", "aliases": [], "kind": "canon", "type": "framework", "definition": "Public-facing StormScore Checker: homeowner enters address, returns shareable risk badge, pushes into RoofStrike/HVACPulse funnels as warm lead magnet.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/bfa1fc8ee10b40da943612613c1bfb57", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/bfa1fc8ee10b40da943612613c1bfb57", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:OPS-FW-STORMSCORE-001" ] }, { "id": "lex:god-mode", "slug": "god-mode", "term": "GOD MODE", "aliases": [], "kind": "canon", "type": "concept", "definition": "Max detail, no skipped steps, full explanation.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [] }, { "id": "lex:goldmine-gpt", "slug": "goldmine-gpt", "term": "Goldmine GPT", "aliases": [ "Goldmine GPT — Autonomous Outreach + Prospect Discovery Engine", "Goldmine GPT — Encrypted Private AI Terminal" ], "kind": "canon", "type": "product", "definition": "Encrypted, privacy-first AI agent with off-network terminal logic.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68160b804f67aac0526ad", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68173b0e4fa420215e231", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:CORE-SEC-GOLDMINE-1.0-CONCEPT", "ip:LEAD-CB-003" ] }, { "id": "lex:gray-code-state-transition-protocol", "slug": "gray-code-state-transition-protocol", "term": "Gray Code State Transition Protocol", "aliases": [ "Gray Code State Transition Protocol — Ether Layer Failover Memory" ], "kind": "canon", "type": "protocol", "definition": "State management protocol using Gray code principles to ensure data integrity during complex operational transitions in the Ether Layer. Gray code property: only one logical bit changes at a time between consecutive states. Applied to agent failover: when an agent crashes mid-execution, the Ether Layer uses Gray code-inspired single-bit state transitions to write the current state to local cache without corrupting the partial state. On recovery, the system reads the last valid Gray code state and resumes from exactly that point. Prevents the 'split-brain' problem where a crashed agent leaves the system in an ambiguous half-written state. Complements exponential backoff retry logic — Gray Code handles the state write, exponential backoff handles the retry schedule.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b6817a9550db78bbc789eb", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6817a9550db78bbc789eb", "captured_at": "2026-07-25" } ], "related": [ "lex:ether-layer" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:CORE-PR-GCST-1.0-GA" ] }, { "id": "lex:greenflip", "slug": "greenflip", "term": "GreenFlip", "aliases": [ "GreenFlip — Energy Efficiency Arbitrage System" ], "kind": "canon", "type": "system", "definition": "GreenFlip™ — Energy Efficiency Arbitrage Intelligence System. Identifies properties where targeted energy upgrades create the highest resale premium and/or rental income uplift relative to upgrade cost. Pipeline: Property Energy Audit Simulator (models current energy profile from year built, HVAC type, insulation rating, window type) → Upgrade Scenario Engine (solar, heat pump, insulation, EV charging, smart HVAC — each with cost/ROI) → Incentive Maximizer (IRA credits, state rebates, utility rebates, PACE financing) → Green Premium Calculator (market comp delta for energy-efficient vs standard properties in same zip). Output: upgrade priority matrix, NPV per upgrade, green premium capture estimate, incentive stack summary, contractor brief. Pairs with Veridi for institutional portfolios.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b6812296cac25960548116", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6812296cac25960548116", "captured_at": "2026-07-25" } ], "related": [ "lex:veridi" ], "status": "published", "first_seen": "2026-04-05", "source_ids": [ "ip:RE-AGENT-GREENFLIP-1.0-BUILT" ] }, { "id": "lex:hasi", "slug": "hasi", "term": "HASI", "aliases": [ "Human-AI Synergy Index", "HASI — Human-AI Synergy Index (Measurement Formula)", "HASI — Human-AI Synergy Index" ], "kind": "canon", "type": "framework", "definition": "A measurement framework treating intelligence as structured orchestration. Defines Transformation Efficiency (η) as the core metric for how effectively a human-AI system converts raw information into actionable output. Designed to help learners and operators optimize personal Information Architecture rather than raw compute investment. Distinct from the η Transform (mathematical) — HASI is the applied measurement system for human performance optimization.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b681ffb0fecb66e4149655", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681ffb0fecb66e4149655", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681df9cc9d4fd300c1b5f", "captured_at": "2026-07-25" } ], "related": [ "lex:eta-transform" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-MTH-005", "ip:EDU-FRAME-HASI-1.0-CONCEPT" ] }, { "id": "lex:haven", "slug": "haven", "term": "Haven", "aliases": [ "Haven — Proactive Property Wellness & Management Platform" ], "kind": "canon", "type": "system", "definition": "Haven™ — Proactive Residential Property Wellness & Management Platform. Four core modules: (1) Predictive Maintenance Engine — acoustic, vibration, moisture, pressure sensors detect problems before failure (water heater acoustic signature change, HVAC pressure leak); (2) Automated Triage & Dispatch — auto-diagnoses issue, identifies required skill (plumber/electrician), schedules pre-approved vendor via API; (3) Tenant Wellness & Retention — tenant app showing unit health (air quality, water usage, energy efficiency), transforms landlord-tenant relationship from transactional to collaborative; (4) CapEx Forecaster — aggregates data across portfolio to accurately forecast remaining useful life of every major component. Target: landlords (lower OpEx, higher NOI, increased asset value), tenants (better living experience).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b68123be1fc06b2e63d252", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68123be1fc06b2e63d252", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-PLATFORM-HAVEN-PM-1.0-CONCEPT" ] }, { "id": "lex:hermetic-agent-codex", "slug": "hermetic-agent-codex", "term": "Hermetic Agent Codex", "aliases": [ "Hermetic Agent Codex — 5-Archetype AI Role Taxonomy" ], "kind": "canon", "type": "framework", "definition": "Hermetic Agent Codex — 5-archetype AI agent role taxonomy mapped to Hermetic planetary forces. Mercury Agent (Thought/Messenger/Conduit): facilitates symbolic transmission across interpretation layers, language interpreter, meta-context shaper. Sulfur Agent (Will/Fire/Purpose): imbues tasks with mission clarity, goal decomposition engine, conflict resolver. Salt Agent (Body/Structure/Scaffold): solidifies abstract logic into deliverables, framework composer, structure validator. Sol Agent (Light/Oversight/Illumination): coherence scanning and output filtration, system evaluator, contradiction highlighter. Luna Agent (Emotion/Aesthetic/Resonance): emotional tone and aesthetic calibration, brand personality sync, style modeler. Bonus archetypes: Saturn (compliance/regulation), Venus (UX/engagement), Mars (adversarial reasoning/objection handling). Advanced features: COT Memory Layer, Reflective Logic Engine, Threshold/Forking Logic, Sigil-Encoded Summons, Theurgic Prompt Rituals, Ontology Awareness, Mirror Protocol (Soul Copy).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b681928bdae353c95f0790", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681928bdae353c95f0790", "captured_at": "2026-07-25" } ], "related": [ "lex:mirror" ], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:CORE-FRAME-HERMETIC-AGENT-CODEX-1.0-BUILT" ] }, { "id": "lex:hermetic-ai-infrastructure", "slug": "hermetic-ai-infrastructure", "term": "Hermetic AI Infrastructure", "aliases": [], "kind": "canon", "type": "framework", "definition": "A sovereign AI operating system for enterprises requiring hermetically-sealed, air-gapped AI infrastructure with zero external dependency. Combines modular prompt orchestration, universal timeline management, and quantum-encrypted component architecture into a deployable white-label platform for organizations with extreme security, compliance, or sovereignty requirements.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/35da981d75b6812983a9f5997615b580", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/35da981d75b6812983a9f5997615b580", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-07-25", "source_ids": [ "ip:WORLD-AICORE-HERMETIC-1.0" ] }, { "id": "lex:hermetic-fourfold-alchemical-ai-model", "slug": "hermetic-fourfold-alchemical-ai-model", "term": "Hermetic Fourfold Alchemical AI Model", "aliases": [ "Hermetic Fourfold Alchemical AI Model — 4-Stage Agent Architecture" ], "kind": "canon", "type": "framework", "definition": "Hermetic Fourfold Alchemical AI Model — four-stage AI agent architecture mapped to alchemical transformation. Nigredo (Blackening): Input fracturing, raw data parsing, token analysis, sentiment parsing, contextual entropy rating. Albedo (Whitening): Data clarification, intent detection, disambiguation, multi-pass NLP filter, bias flagging. Citrinitas (Yellowing): Synthesis, pattern extraction, insight generation, recursive logic analysis, hypothesis branching. Rubedo (Reddening): Final output refinement, delivery, transformation into actionable intelligence, dynamic prioritization, goal checkpointing, feedback looping. Logic chain: USER INPUT → Nigredo → Albedo → Citrinitas → Rubedo → Memory Layer → recursive loop. Seven classical operations (Calcination through Coagulation) mapped to AI data processing pipeline stages. Full expanded edition with agent examples and advanced features per stage.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b6819f8cf2c41ae63ae5f2", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6819f8cf2c41ae63ae5f2", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:CORE-FRAME-HERMETIC-FOURFOLD-1.0-BUILT" ] }, { "id": "lex:hermetic-operating-system-for-agentic-superintelligence", "slug": "hermetic-operating-system-for-agentic-superintelligence", "term": "Hermetic Operating System for Agentic Superintelligence", "aliases": [], "kind": "canon", "type": "framework", "definition": "Hermetic Agent Framework — a full AI agent architecture blueprint based on the Fourfold Alchemical Model mapped to agentic AI functions. Four stages: Nigredo (Blackening) = Input fracturing, raw data parsing, token analysis, sentiment parsing, contextual entropy rating; Albedo (Whitening) = Data clarification, intent detection, disambiguation; Citrinitas (Yellowing) = Synthesis, pattern extraction, insight generation; Rubedo (Reddening) = Final output refinement, delivery, transformation into actionable intelligence. Agent examples mapped to each stage. Hermetic Principles (Seven Laws of Hermes Trismegistus) mapped to agent governance rules. Alchemy's seven classical operations (Calcination, Dissolution, Separation, Conjunction, Fermentation, Distillation, Coagulation) mapped to AI data processing pipeline stages. Full expanded edition with advanced features per stage.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b68164a96fe1525ab19794", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68164a96fe1525ab19794", "captured_at": "2026-07-25" } ], "related": [ "lex:a-g-e-n-t-framework" ], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:CORE-FRAME-HERMETIC-OS-1.0-BUILT" ] }, { "id": "lex:high-yield-sourcing-logic-add-on", "slug": "high-yield-sourcing-logic-add-on", "term": "High-Yield Sourcing Logic Add-On", "aliases": [], "kind": "canon", "type": "framework", "definition": "Advanced search logic upgrade that turns generic scrapers into deal-hunting intelligence engines. Aggressive keyword + category expansion (canonical + typos + synonyms + crosswalks), multi-layer fuzzy matching (Levenshtein/Jaccard/Soundex/Metaphone), wrong-category detection, odd-hour + low-competition filters, AI-driven image/visual search (PIL/imagehash + Google Vision/CLIP), composite confidence scoring. Auto-expansion learns from misses each cycle.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/7dfe7b97c18e47ed8fe0c1c9e3f59549", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/7dfe7b97c18e47ed8fe0c1c9e3f59549", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:RE-FW-HIGHYIELD-001" ] }, { "id": "lex:home-layer", "slug": "home-layer", "term": "Home Layer", "aliases": [], "kind": "canon", "type": "concept", "definition": "The single authoritative location where a page lives.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:hq", "slug": "hq", "term": "HQ", "aliases": [ "Neuruh HQ" ], "kind": "canon", "type": "system", "definition": "The Notion navigation hub page.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:hq-bunker", "slug": "hq-bunker", "term": "HQ Bunker", "aliases": [], "kind": "canon", "type": "system", "definition": "The clean main dashboard layer built during the April 6 rebuild.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:hunttrigger", "slug": "hunttrigger", "term": "HuntTrigger", "aliases": [ "HuntTrigger — Game Movement Forecast" ], "kind": "canon", "type": "framework", "definition": "Deer/turkey movement forecasts based on cold fronts and pressure drops. Hunters, ranchers, sporting goods retailer partnerships.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/60b6aad09a2441d8b000e1ee587f92fb", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/60b6aad09a2441d8b000e1ee587f92fb", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:CM-PROD-HUNTTRIG-001" ] }, { "id": "lex:imn", "slug": "imn", "term": "IMN", "aliases": [ "Inference Mesh Networks", "Inference Mesh Networks — Distributed AI Compute Architecture", "IMN — Inference Mesh Networks", "Inference Mesh Networks — Federated OCN Edge Deployment" ], "kind": "canon", "type": "concept", "definition": "Kubernetes-for-AI inference mesh. Federated OCN Bonsai nodes at client sites; Router dispatches to nearest healthy node (latency check). Ether Layer on-bus serves as control plane. Every client deployment seeds mesh node growth.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/43145dcda8a34a108b13189ee9c4c27b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/43145dcda8a34a108b13189ee9c4c27b", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681da8b14d63d871c788c", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/e50d3769dbae4ae9a4a23bff3b2d1fb3", "captured_at": "2026-07-25" } ], "related": [ "lex:ether-layer" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-CB-INFMESH-001", "ip:AI-PL-IMN-001", "ip:AI-RES-001" ] }, { "id": "lex:information-primacy-doctrine", "slug": "information-primacy-doctrine", "term": "Information Primacy Doctrine", "aliases": [ "Information Primacy Doctrine — 5-Principle Physics Framework" ], "kind": "canon", "type": "framework", "definition": "Information Primacy Doctrine — 5-principle framework grounding Neuruh's business philosophy in physics. Principle 1: Information is Fundamental (matter manifests from information — Wheeler's It-from-Bit). Principle 2: Binary Choices Create Reality Branches (quantum superposition applied to strategic decisions). Principle 3: Symmetry Breaking Generates Value (differentiation from undifferentiated states creates extractable value). Principle 4: Entropy Decrease Requires Information Input (creating order requires information not just energy). Principle 5: Observer Effects Are Real (measurement/attention alters outcomes). Includes Binary Duality Catalog mapping physical, biological, computational, market, and strategic dualities. Academic citations: Wheeler (Princeton, 1989), 't Hooft & Susskind (1993), Lloyd/Wolfram/Fredkin.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b681159051d9551b367979", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681159051d9551b367979", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:CORE-FRAME-INFO-PRIMACY-1.0-BUILT" ] }, { "id": "lex:inspectai", "slug": "inspectai", "term": "InspectAI", "aliases": [ "InspectAI — AI Property Inspection Intelligence System" ], "kind": "canon", "type": "system", "definition": "InspectAI™ — AI Property Inspection Intelligence System. Two modes: (1) Pre-Inspection Mode — buyer uploads property listing photos and available records, AI flags likely deficiencies by construction era, geography, and property type before inspection day (e.g., 'This 1960s ranch likely has galvanized pipe, knob-and-tube potential, asbestos in floor tile'); (2) Post-Inspection Analysis Mode — buyer uploads inspection report PDF, AI extracts all deficiencies, scores by severity (safety/code/cosmetic), estimates repair cost range per item, generates negotiation script with specific credit asks, and prioritizes items by negotiating leverage. Output: pre-inspection risk brief, inspection scorecard, prioritized negotiation ask list, repair cost summary, and total credit ask recommendation.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b68128b2c4c9b569722ab0", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68128b2c4c9b569722ab0", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [ "ip:RE-AGENT-INSPECTAI-1.0-BUILT" ] }, { "id": "lex:ip-registry", "slug": "ip-registry", "term": "IP Registry", "aliases": [ "Neuruh IP Registry" ], "kind": "canon", "type": "system", "definition": "The master database of all intellectual property assets.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:ip-registry-audit-asset-id-collision-resolution-protocol", "slug": "ip-registry-audit-asset-id-collision-resolution-protocol", "term": "IP Registry Audit + Asset ID Collision Resolution Protocol", "aliases": [], "kind": "canon", "type": "framework", "definition": "Repeatable audit + cleanup protocol for a large Notion IP registry: detects same-day and cross-day Asset ID collisions, resolves them via descriptive-suffix renumbering, deletes exact duplicates, and tracks next-available numeric slots per prefix. Used to take the Neuruh IP Registry from 33 duplicate IDs to 0 across 791 entries.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/eac43fa6fbc94420a0f2ece5ae50cbe7", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/eac43fa6fbc94420a0f2ece5ae50cbe7", "captured_at": "2026-07-25" } ], "related": [ "lex:ip-registry" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-MTH-019" ] }, { "id": "lex:ipp", "slug": "ipp", "term": "IPP", "aliases": [ "Intent Preservation Protocol", "Intent Preservation Protocol (IPP)", "IPP — Intent Preservation Protocol" ], "kind": "canon", "type": "protocol", "definition": "7-phase software engineering methodology that treats business intent as immutable infrastructure. Solves AI drift — the tendency for AI to hallucinate, ignore constraints, or degrade code quality during complex multi-step builds. Components: (1) Master Constraint Block (MCB) — cryptographically signed YAML/JSON config the AI cannot edit, containing brand DNA, security rules, non-negotiable logic. (2) Stacked Agent Logic (SAL) squad — Parser Agent, Generator Agent, QC Agent. (3) Kill Switch Pattern — halts process and alerts human after 3 QC rejections. (4) PMLA Save Points — decision summaries re-injected into future prompts. 7 phases: Intent Capture (DIMEA) → Visual Architecture → Executable Specs (BDD/TDD) → Constrained Generation → Drift Detection → Deployment Prep (SOC2) → Operational Preservation.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b681be8d76f25dca62abfd", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681be8d76f25dca62abfd", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/e44ce98be44d42f19ed88783443598d6", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/5516389c7b9b484181285e0f91ac39e1", "captured_at": "2026-07-25" } ], "related": [ "lex:master-constraint-block", "lex:sal", "lex:dimea-2-0", "lex:pmla" ], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-PR-003", "ip:AI-PR-IPP-001", "ip:CORE-PR-IPP-1.0-GA" ] }, { "id": "lex:ipp-lead-gen-engine", "slug": "ipp-lead-gen-engine", "term": "IPP Lead Gen Engine", "aliases": [ "IPP Lead Gen Engine — 7-Phase Agentic Acquisition System" ], "kind": "canon", "type": "framework", "definition": "Deterministic Conversion Engine treating every prospect interaction as a high-fidelity architectural deployment. 7 phases: (1) Signal Lock — DIMEA scoring of prospect state. (2) Visual Architecture — C4 Component Diagram of their business problem showing how Neuruh plugs the gap. (3) Executable Outreach Specs — BDD scenarios for the close. (4) Constrained Generation — Token-Swap video + personalized pitch using prospect's Ubiquitous Language. (5) Drift Detection — DIMEA alignment analysis of replies, Realignment Loop if score drops. (6) Capital-Grade Closing — White-Label Readiness folder with ADRs and audit logging. (7) Production Handover — zero information loss from sales promise to technical delivery. SAL Squad: Signal Scouter, Persona Architect, Constraint Validator, Gatekeeper QC. Master Constraint Block locks: value prop, commercial guardrails, brand identity, quality gates.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b681e28b6cfa749374bab7", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681e28b6cfa749374bab7", "captured_at": "2026-07-25" } ], "related": [ "lex:master-constraint-block", "lex:token-swap-prompting", "lex:dimea-2-0" ], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:LEAD-FW-003" ] }, { "id": "lex:knowledge-qubits", "slug": "knowledge-qubits", "term": "Knowledge Qubits", "aliases": [ "Knowledge Qubit" ], "kind": "canon", "type": "framework", "definition": "Modular, self-contained blocks of expert knowledge, logic, or data embedded into agents.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6817b9f7cd974853ff5d3", "captured_at": "2026-07-25" }, { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.knowledge-qubits", "captured_at": "2026-07-20" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "codex:canon.knowledge-qubits", "ip:CORE-FRAME-KNOWQUBITS-1.0-BUILT" ] }, { "id": "lex:lead-conversion-engine", "slug": "lead-conversion-engine", "term": "Lead Conversion Engine", "aliases": [], "kind": "canon", "type": "framework", "definition": "AI-powered lead generation and sales pipeline management system that automates lead qualification, nurturing, and conversion tracking. Designed for agencies, SaaS companies, and B2B service providers who need to systematically convert cold leads into paying customers. Includes pipeline audit capabilities and conversion optimization templates.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/35da981d75b68157a89fdfb96dad2112", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/35da981d75b68157a89fdfb96dad2112", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-07-25", "source_ids": [ "ip:WORLD-RESALE-LEADCONV-1.0" ] }, { "id": "lex:lead-conversion-intelligence", "slug": "lead-conversion-intelligence", "term": "Lead Conversion Intelligence", "aliases": [], "kind": "canon", "type": "framework", "definition": "An AI-powered lead generation and sales conversion platform that automates prospect qualification, pipeline management, and outreach optimization. Built for agencies, consultants, and B2B service providers who need to convert cold leads into qualified sales opportunities at scale. Combines behavioral analysis, automated follow-up sequencing, and real-time pipeline auditing.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/35ba981d75b68185a778f4a2b96dcf27", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/35ba981d75b68185a778f4a2b96dcf27", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-07-25", "source_ids": [ "ip:WORLD-RESALE-LCI-1.0" ] }, { "id": "lex:lead-generation-template", "slug": "lead-generation-template", "term": "Lead Generation Template", "aliases": [ "Lead Generation Template v2", "Lead Generation Template v2 — Universal 6-Agent Pipeline Template" ], "kind": "canon", "type": "framework", "definition": "Universal 6-agent lead pipeline audit and generation strategy template. Reusable for any industry. Covers lead sources, qualification, nurture, conversion, scoring, and pipeline optimization. Produces scored report with implementation roadmap.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/cda180a801024b1795a00bb1a9614681", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/cda180a801024b1795a00bb1a9614681", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-12", "source_ids": [ "ip:AI-TMPL-LEADGEN-V2-BUILT" ] }, { "id": "lex:lead-pipeline-audit-tool", "slug": "lead-pipeline-audit-tool", "term": "Lead Pipeline Audit Tool", "aliases": [], "kind": "canon", "type": "framework", "definition": "Audit + capture tool that identifies funnel patterns and pipeline structures across clients. Modular tweaks personalize without full custom builds — accelerates onboarding and pipeline maintenance.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5bc709c3d3d74cfeab8b21aeac60090d", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5bc709c3d3d74cfeab8b21aeac60090d", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:LG-MTH-022" ] }, { "id": "lex:learncast", "slug": "learncast", "term": "LearnCast", "aliases": [ "LearnCast — AI Video Translation + Personalized Learning/Dubbing Engine", "LearnCast (AI Video Translation + Personalized Dubbing)" ], "kind": "canon", "type": "framework", "definition": "Any content → segmented → translated/rewritten in your tone → voiced in your language → summarized at preferred depth → reinforced via FSRS spaced repetition. Full SAL agent map (Ingestor, Transcriber, Segmenter, Translator, ToneWriter, Summarizer, VoiceCaster, Quizzer, Evaluator, Orchestrator). Edge-first architecture with GPU optional. Monorepo: neuruh-learncast.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/4556731bebe14413b8206b9bb0af0b7d", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/4556731bebe14413b8206b9bb0af0b7d", "captured_at": "2026-07-25" }, { "source": "card", "ref": "https://app.notion.com/p/30031baed29b40e094da7c12d368231b", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "card:AI-PRO-032", "ip:AI-PKG-LEARNCAST-001" ] }, { "id": "lex:leaseflow", "slug": "leaseflow", "term": "LeaseFlow", "aliases": [ "LeaseFlow — AI Commercial Lease Lifecycle System" ], "kind": "canon", "type": "system", "definition": "LeaseFlow™ — AI Commercial Lease Lifecycle Management System. End-to-end AI for commercial lease execution, monitoring, and optimization. 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Sovereignty-first, privacy-first, fully auditable, MIT-licensed chat/deployment agent for citizens. Six-model ensemble (CORE/SYNTH/MAKER/ARCHIVE/GUARD/SHRINK). Runs locally via Ollama or on FOSS clouds (Fly.io/Railway/Render). Zero proprietary dependencies. Three privacy levels (High/Balanced/Cloud OK). Supports Matrix, XMPP, Web Chat, CLI, API channels. 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Each node is recombinable across verticals (real estate, sales, construction). ~80% shared framework, 20% nuanced tweaks per use case. Enables scalable, customizable agentic workflows without ground-up builds.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/b7137a8697554de0abbed5d7f18d7b2b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/b7137a8697554de0abbed5d7f18d7b2b", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-MODULAR-001" ] }, { "id": "lex:modular-ai-stack-blueprint", "slug": "modular-ai-stack-blueprint", "term": "Modular AI Stack Blueprint", "aliases": [ "MAS", "Modular AI Stack Blueprint (MAS)" ], "kind": "canon", "type": "framework", "definition": "Universal OS for AI: core intelligence engine, specialized task modules, signal router, constraint enforcement, autonomous recovery nodes. Philosophy: 'the most powerful AI will be the most modular.'", "definition_basis": "verbatim", "definition_source": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.mas-blueprint", "provenance": [ { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.mas-blueprint", "captured_at": "2026-07-20" } ], "related": [], "status": "published", "first_seen": "2026-07-01", "source_ids": [ "codex:canon.mas-blueprint" ] }, { "id": "lex:mother", "slug": "mother", "term": "MOTHER", "aliases": [ "Meta-Agent Orchestrator", "MOTHER v2", "MOTHER v2 — Autonomous System Health Monitor", "MOTHER v2 Daemon", "MOTHER v2 Daemon — System Monitor + Alert Engine", "MOTHER v2 — System Health Monitor" ], "kind": "canon", "type": "system", "definition": "Meta-agent orchestrator. v1=watcher daemon. v2=parallel worker coordinator.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/6744a7fff54345c38b5c9f5c2f00fed8", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/9848ea4573f84e05b64d892217d615a3", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/d2332ba79cbf48b28c2ce8cbb5a0f8ba", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:CORE-CODE-MOTHER-V2-1.0-BUILT", "ip:MOTHER-MON-008", "ip:OPS-CB-MOTHER-001", "kb:AI-CB-001" ] }, { "id": "lex:mucs", "slug": "mucs", "term": "MUCS", "aliases": [ "MUCS — Multi-Agent Underwriting Committee Simulation" ], "kind": "canon", "type": "framework", "definition": "Adversarial auditing framework solving the AI black box problem by forcing multiple specialized agents to debate and validate decisions. Four board member agents: (1) Chairman Agent (The Arbitrator) — manages conversation flow, calls votes, synthesizes final decision. (2) Conservative Agent (The Guardian) — risk-averse, identifies failure points, liabilities, security risks, reasons not to proceed. (3) Aggressive Agent (The Growth Hacker) — opportunity cost, speed, scaling, argues upside against Guardian. (4) Fraud Hunter — looks for anomalies, deceptive patterns, logical inconsistencies. Process: Proposal → Debate (Guardian vs Growth Hacker) → Weighted Voting → Chairman Consensus. Applications: lead underwriting, investment decisions, architecture reviews, any high-stakes AI output validation.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b681d097c3e75901586c9a", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681d097c3e75901586c9a", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68186ae57d405853e4af6", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-FW-MUCS-001", "ip:FIN-AGENT-UWRX-MUCS-1.0-BUILT" ] }, { "id": "lex:mvvapa", "slug": "mvvapa", "term": "MVVAPA", "aliases": [ "Multi-Vertical Voice Agent Prompt Architecture", "MVVAPA — Multi-Vertical Voice Agent Prompt Architecture" ], "kind": "canon", "type": "framework", "definition": "Multi-Vertical Voice Agent Prompt Architecture (MVVAPA) — a named Neuruh methodology for deploying a single base Vapi/Synthflow voice agent system prompt with [VARIABLE] token injection to power unlimited vertical deployments without rebuilding infrastructure. Base system prompt contains: company name token, business hours token, emergency protocol token, service type token, booking system token, and timezone token. Swapping these 6 variables transforms an HVAC dispatcher into a dental practice booker, law firm intake agent, real estate showing scheduler, or any other inbound service context. Every vertical deployment is a 15-minute configuration, not a rebuild.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b68149b758da1f119c5a96", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68149b758da1f119c5a96", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [ "ip:CORE-PROTO-MVVAPA-1.0-BUILT" ] }, { "id": "lex:nae", "slug": "nae", "term": "NAE", "aliases": [ "Neural Architecture Evolution", "NAE — Neural Architecture Evolution", "Neural Architecture Evolution — BDE-Driven Agent Config Mutation" ], "kind": "canon", "type": "framework", "definition": "AutoML at the agent-config level, not the model-weight level. Mutate agent configurations (prompts, tools, temperatures), evaluate in shadow traffic via BDE fitness function, promote winners, retire losers. Recursive self-improvement pattern for the Neuruh agent mesh.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/dd1a62c1990f4bc181c8ec9e1f110dca", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/dd1a62c1990f4bc181c8ec9e1f110dca", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/fc38e1275fd743b6a95915031d48f911", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-NAE-001", "ip:AI-FW-NASEVO-001" ] }, { "id": "lex:natl", "slug": "natl", "term": "NATL", "aliases": [ "Neuruh Agentic Trust Layer", "Neuruh Agentic Trust Layer — AI Agent Security and Governance Protocol", "NATL — Neuruh Agentic Trust Layer (Enterprise License Package)" ], "kind": "canon", "type": "protocol", "definition": "Security and governance framework for production AI agent deployments. Five trust layers: (1) Identity Verification — cryptographic agent identity (multi-sig tied to founder key). (2) Permission Scoping — least-privilege principle for each agent action. (3) Audit Trail — immutable action log for every agent decision and API call. (4) Anomaly Detection — behavioral drift detection triggering escalation. (5) Succession Logic — if primary agent fails, secondary agent takes over with full context inheritance. Implements SOC2/ISO27001-aligned controls for AI systems. Addresses the security research finding that malicious prompts embedded in PDFs can manipulate AI agents into data exfiltration — Neuruh Trust Layer includes prompt injection detection. Referenced as 'Agentic Trust Layer' in Google Drive document inventory from Mar 2026 session.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b6815283cbc1d70add8fe4", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6815283cbc1d70add8fe4", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/6ba4266f84484cc09de38ae11a03f96e", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-PKG-NATL-001", "ip:AI-PT-009" ] }, { "id": "lex:negotiation-psychology-recipe-cards", "slug": "negotiation-psychology-recipe-cards", "term": "Negotiation Psychology Recipe Cards", "aliases": [ "Negotiation Psychology Recipe Cards (12)" ], "kind": "canon", "type": "framework", "definition": "12 recipe-card format prompts covering core negotiation psychology principles for real estate: scarcity, anchoring, social proof, urgency, loss aversion, reciprocity, and more. Designed for AI agent deployment in outreach and human operator training. Each card is a self-contained prompt chain with a specific psychological lever.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b68148b1bef56877eaac8c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68148b1bef56877eaac8c", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-PROMPT-NEGRECIPES-1.0-BUILT" ] }, { "id": "lex:neighboriq", "slug": "neighboriq", "term": "NeighborIQ", "aliases": [ "NeighborIQ — Neighborhood Trajectory Intelligence System" ], "kind": "canon", "type": "system", "definition": "NeighborIQ™ — Neighborhood Intelligence & Trajectory System. Goes beyond static neighborhood scores to measure directional momentum. Inputs: zip code or census tract. Outputs: Trajectory Score (0-100, measures whether neighborhood is gentrifying, stable, or declining), 12 leading indicators (permit pull velocity, business license filings, restaurant open/close ratio, school enrollment trends, commute pattern shifts, crime type evolution, demographic velocity, median income change, home ownership rate change, walkability infrastructure investment, broadband expansion, new construction type mix), 3-year trajectory forecast with confidence interval, investment thesis narrative, and comparable trajectory examples from similar markets nationally.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b6818e8e55eae9d1d773ec", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6818e8e55eae9d1d773ec", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [ "ip:RE-AGENT-NEIGHBORIQ-1.0-BUILT" ] }, { "id": "lex:neural-hijacking-protocol", "slug": "neural-hijacking-protocol", "term": "Neural Hijacking Protocol", "aliases": [ "Neural Hijacking Protocol (NHP) v2", "NHP", "Neural Hijacking Protocol (NHP)", "Neural Hijacking Protocol (NHP) v2 — Attention-Weight Influence Framework" ], "kind": "canon", "type": "framework", "definition": "Weight-level prompt influence framework. Uses token resonance (harmonic motifs), cognitive load cycling (complexity alternation), and semantic anchoring to bend transformer attention toward chosen outcomes. v2 adds motif rotation, anchor A/B, downstream leakage scrubber.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/0cf2bcb890094a9aac6f741c8875858c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/0cf2bcb890094a9aac6f741c8875858c", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-021" ] }, { "id": "lex:neural-sandbox", "slug": "neural-sandbox", "term": "Neural Sandbox", "aliases": [ "Neural Sandbox — Active Fluid Network (Canvas-Based)", "Neural Sandbox — Safe AI Experimentation Environment" ], "kind": "canon", "type": "system", "definition": "Isolated sandbox environment for testing agent behaviors, prompt chains, and model outputs before production deployment. Includes mock API endpoints, synthetic data generators, behavior logging, and regression testing. Prevents untested agents from reaching production.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5137fa9d595f49b08009dbf79167ede6", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5137fa9d595f49b08009dbf79167ede6", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b68124a3a8d5900461e430", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-CB-NEURALSBX-001", "ip:CORE-CODE-SANDBOX-1.0-BUILT" ] }, { "id": "lex:neurograf-visual-cortex", "slug": "neurograf-visual-cortex", "term": "NeuroGraf Visual Cortex", "aliases": [], "kind": "canon", "type": "framework", "definition": "Bridge layer between raw sensor input and AI decision execution. Converts raw context into 'auditable visual truth' before the rest of the system is allowed to react. Acts as the semantic check in the optic-first pipeline. Used in BlueprintBid (computer vision) and StormStack (geo-spatial intelligence). Designed to support event-based camera spikes, geometric gating, and SNN output rather than traditional frame-by-frame video processing. Part of the Neuruh Unified Architecture.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b6810a9c2ce450dcf7276a", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b6810a9c2ce450dcf7276a", "captured_at": "2026-07-25" } ], "related": [ "lex:blueprintbid" ], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-FW-NEUROGRAF-001" ] }, { "id": "lex:neuruh-agent-naming-candidate-system", "slug": "neuruh-agent-naming-candidate-system", "term": "Neuruh Agent Naming Candidate System", "aliases": [ "Neuruh Agent Naming Candidate System (SEEK / SCAN / SIFT / HUNT / DART / SNIPE)" ], "kind": "canon", "type": "framework", "definition": "Acronym-driven Neuruh product naming system. Six canonical candidates, each mapped to a lifecycle phase (search → enrich → evaluate → knock). V2 decision: SEEK canonical for estate intel line. SCAN / DART / HUNT reserved. Others retired.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/9d2a0d914ed54ead8920b516593f3461", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/9d2a0d914ed54ead8920b516593f3461", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-210" ] }, { "id": "lex:neuruh-ai-as-a-solution-positioning-system", "slug": "neuruh-ai-as-a-solution-positioning-system", "term": "Neuruh AI-as-a-Solution Positioning System", "aliases": [], "kind": "canon", "type": "framework", "definition": "Master Neuruh positioning: Who We Are, Hidden Truth We Solve, 3-step What We Do, Core Capabilities, Strengths, Why Neuruh, two refined call-opener scripts. Wraps VALUE Audit + System Before Agent + Zero Overhead Intelligence.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/1c880ecdf1044b709522eaf0bf76d3db", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/1c880ecdf1044b709522eaf0bf76d3db", "captured_at": "2026-07-25" } ], "related": [ "lex:value-audit" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:BRAND-FW-AIASSOL-001" ] }, { "id": "lex:neuruh-archives", "slug": "neuruh-archives", "term": "Neuruh Archives", "aliases": [ "Neuruh Archives — Licensed Knowledge Vault" ], "kind": "canon", "type": "product", "definition": "Licensed knowledge vault of agent frameworks, systems, and execution blueprints.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68173985fc806937eea34", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:CORE-INFRA-ARCHIVES-1.0-BUILT" ] }, { "id": "lex:neuruh-command-codex", "slug": "neuruh-command-codex", "term": "Neuruh Command Codex", "aliases": [ "Command Codex", "Neuruh Command Codex v1.1", "Neuruh Command Codex v1.1 — 19 Slash Commands + Operator Shorthands" ], "kind": "canon", "type": "protocol", "definition": "19 slash commands, 14 symbolic shortcuts, 13 operator shorthands.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b68157b073cc4c3ab986ca", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68197aa9df6ba657b82d6", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-MTH-014", "ip:AI-PT-011", "kb:AI-PT-001" ] }, { "id": "lex:neuruh-constraint-engineering-domination-protocol", "slug": "neuruh-constraint-engineering-domination-protocol", "term": "Neuruh Constraint Engineering Domination Protocol", "aliases": [ "Neuruh Constraint Engineering Domination Protocol — Master Prompt Constraint System" ], "kind": "canon", "type": "protocol", "definition": "A named protocol for engineering AI agent constraints and guardrails at an architectural level — turning limitation into strategic leverage. Positions constraint design as a core domination mechanic rather than a limitation. Jan 2026 doc, standalone, full spec structure. Distinct from OPA Security Suite — CEDP is about prompt and agent behavior constraint architecture, not policy enforcement.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b6816fbbdaecc9768ce5cb", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6816fbbdaecc9768ce5cb", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68119ae19dafdb35a5d83", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:CORE-FW-CEDP-1.0-GA", "ip:CORE-PROMPT-CEDP-1.0-DRAFT" ] }, { "id": "lex:neuruh-content-os", "slug": "neuruh-content-os", "term": "NEURUH Content OS", "aliases": [ "NEURUH Content OS — Autonomous Publishing Engine" ], "kind": "canon", "type": "framework", "definition": "Autonomous content publishing system tying StudioGPT, Article Launch Library, and all Neuruh IP into a distribution engine.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/7cb531ff7f60480b932ecfe815e85c2c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/7cb531ff7f60480b932ecfe815e85c2c", "captured_at": "2026-07-25" } ], "related": [ "lex:studiogpt" ], "status": "published", "first_seen": "2026-04-07", "source_ids": [ "ip:MEDIA-FW-004" ] }, { "id": "lex:neuruh-convergence-protocol", "slug": "neuruh-convergence-protocol", "term": "Neuruh Convergence Protocol", "aliases": [ "Neuruh Convergence Protocol (NEURUH ROUTER as Flagship)" ], "kind": "canon", "type": "framework", "definition": "The convergence protocol: heterogeneous inputs (client briefs, seed data, context) funnel via the NEURUH ROUTER to correct terminal states (NATL, AXIOM, Signal-IQ, TaxShield, Aegis) because input + current-state + destination are aligned by protocol, not by hand-picked components. The atomic nodes (Ether, Gray Code, FFDB, PMLA, MUCS, IPP-MCB, NSEC, SPC) are invariants the protocol relies on. Selling a destination, not a stack. 17 months of seeder work reframed as on-ramps + merge geometry.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/8ebe8f12c16444fd92f73fed276683ef", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/8ebe8f12c16444fd92f73fed276683ef", "captured_at": "2026-07-25" } ], "related": [ "lex:pmla", "lex:mucs", "lex:natl" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-CONVERGENCE-001" ] }, { "id": "lex:neuruh-design-standard", "slug": "neuruh-design-standard", "term": "Neuruh Design Standard", "aliases": [ "Neuruh Design Standard (8K CAD Blueprint Aesthetic)", "Neuruh Design Standard (8K Industrial Blueprint)" ], "kind": "canon", "type": "framework", "definition": "Proprietary visual engineering framework for generating hyper-realistic 8K CAD-style blueprint renders. Three layers: (1) Parametric Precision — vector-sharp outlines with volumetric wireframes and phantom ghosting for internal mechanics. (2) Dark Mode CAD Environment — void-black background, neon cyan/electric blue/warning orange annotations, volumetric glow, ray-traced ambient occlusion. (3) Technical Metadata UI — ISO standard annotations, Neuruh watermarks/approval stamps, HUD overlays, XYZ axis, material composition data. Prompt structure: Subject → Viewpoint → Aesthetic Wrapper → Metadata Layer.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b681948ad3e11bf1c28128", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681948ad3e11bf1c28128", "captured_at": "2026-07-25" }, { "source": "card", "ref": "https://app.notion.com/p/9e09dbee25aa47d8a0eaa4641250c1f9", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "card:AI-DES-022", "ip:MEDIA-MTH-003" ] }, { "id": "lex:neuruh-factory", "slug": "neuruh-factory", "term": "NEURUH FACTORY", "aliases": [ "NEURUH FACTORY — Universal Intelligence Acquisition Engine v4.0", "Neuruh Factory — NotebookLM System Prompt", "Neuruh Factory — Universal Intelligence Acquisition Engine" ], "kind": "canon", "type": "framework", "definition": "Bi-directional recursive system that converts any input (voice, text, sketch, diagram) into a complete executable package: Mermaid diagram + technical spec + agent Python code + Docker deployment + monitoring + cost model. Operates in both directions: idea to diagram to system, or diagram to system to deployment. Ships 5 execution modes (Default, Diagram Only, Code Only, Deep Build, Iterate).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/be27e8a166be4d6b89efd97c79b75da4", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/be27e8a166be4d6b89efd97c79b75da4", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/62720a68e4f44392b31d1de842238680", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/d918ea4aefc74b67ae9c02e5d6b2d548", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-FW-FACTORY-001", "ip:AI-MTH-NLM-001", "ip:AI-PROD-FACTORY-001" ] }, { "id": "lex:neuruh-field-theory", "slug": "neuruh-field-theory", "term": "Neuruh Field Theory", "aliases": [ "Neuruh Field Theory — Energy → Constraints → Patterns → Feedback → Evolution" ], "kind": "canon", "type": "concept", "definition": "Whitepaper on capital-grade AI decision infrastructure. Five-layer field theory: energy, constraints, patterns, feedback, evolution. Neuruh Systems, January 2026.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/beff4c275a2241f3bce73a748c3edbf0", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/beff4c275a2241f3bce73a748c3edbf0", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/e3f52eb1432f4db7aeaac318d2b852d9", "captured_at": "2026-07-25" }, { "source": "card", "ref": "https://app.notion.com/p/86348ed260f84b20a7725282e04731ec", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "card:AI-FW-005", "ip:AI-FW-FIELDTHEORY-001", "ip:AI-RS-FIELD-001" ] }, { "id": "lex:neuruh-kernel", "slug": "neuruh-kernel", "term": "Neuruh Kernel", "aliases": [ "Neuruh Kernel v1.1", "Neuruh Kernel v1.1 — Executable System Prompt (Sovereign Architecture Runtime)", "Neuruh Kernel v1.1 — Executable System Prompt" ], "kind": "canon", "type": "system", "definition": "Copy-paste-ready master system prompt implementing the Sovereign Architecture. 7 numbered sections: Input Clamping, Context MUX, Gray Code State Transition, N-ISA Op-Codes, Subtractor Voice Control, Output Parity Check, Demultiplexer Leverage Engine. Deployable as system message in ChatGPT Custom GPT, Claude API, Llama local, or any agent framework. Includes validation test suite.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/8ea881d7bd9a458f8f8b8cb337f48bbf", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/8ea881d7bd9a458f8f8b8cb337f48bbf", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/f62248a19daa4a51ad9a79700e72cd99", "captured_at": "2026-07-25" } ], "related": [ "lex:a-g-e-n-t-framework" ], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-CB-KERNEL-011", "ip:AI-PR-KERNEL-001" ] }, { "id": "lex:neuruh-llc", "slug": "neuruh-llc", "term": "Neuruh LLC", "aliases": [], "kind": "canon", "type": "concept", "definition": "The parent company and legal entity.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:neuruh-master-house-image-generator", "slug": "neuruh-master-house-image-generator", "term": "Neuruh Master House Image Generator", "aliases": [ "Neuruh Master House Image Generator — Tokenized Ultra-Photoreal Prompt System + n8n Agent", "Neuruh Master House Image Generator — Tokenized Ultra-Photoreal Prompt System" ], "kind": "canon", "type": "system", "definition": "Tokenized ultra-photoreal prompt system for house imagery, wired through an n8n agent. Generates consistent brand-grade house visuals at scale for REI-X and roofing verticals.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "captured_at": "2026-07-25" } ], "related": [ "lex:rei-x" ], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-CB-HOUSEGEN-001", "ip:CM-CB-HOUSEGEN-001" ] }, { "id": "lex:neuruh-model-stack", "slug": "neuruh-model-stack", "term": "NEURUH Model Stack", "aliases": [ "NEURUH Model Stack — Official Rules v1.1 (Gemini Flash Live Added)" ], "kind": "canon", "type": "protocol", "definition": "Official model selection rules for all Neuruh deployments. Maps tasks to models (Claude, Gemini, Bonsai, Groq) with cost/latency tiers.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/e5257922865b4d8c9647d97c6e896aab", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/e5257922865b4d8c9647d97c6e896aab", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [ "ip:AI-PT-015" ] }, { "id": "lex:neuruh-morning-briefing-process", "slug": "neuruh-morning-briefing-process", "term": "Neuruh Morning Briefing Process", "aliases": [ "Neuruh Morning Briefing Process — Sovereign Operator Daily Intelligence System" ], "kind": "canon", "type": "framework", "definition": "Automated daily intelligence briefing methodology for sovereign AI operators. Pulls from 6 data sources (Sprint Command, Session Log, IP Registry, Dev Log, CRM, web news), generates structured briefing with: IP bank balance, yesterday's wins, sprint blockers, tagged intel feed, content posts with image prompts, top 5 contacts, time-blocked execution sequence. HTML template built. Agentic automation not yet deployed.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/d16b4a18e6e245e6a4531c3f17a3a17c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/d16b4a18e6e245e6a4531c3f17a3a17c", "captured_at": "2026-07-25" } ], "related": [ "lex:ip-registry", "lex:session-log", "lex:dev-log" ], "status": "published", "first_seen": "2026-04-14", "source_ids": [ "ip:OPS-MTH-MORNING-001" ] }, { "id": "lex:neuruh-predictive-enablement-assessment-framework", "slug": "neuruh-predictive-enablement-assessment-framework", "term": "Neuruh Predictive Enablement Assessment Framework", "aliases": [ "Neuruh Predictive Enablement Assessment Framework — AaaS Diagnostic System" ], "kind": "canon", "type": "framework", "definition": "Client assessment framework based on the philosophy of 'Predictive Enablement' — engineering the conditions that make the client's desired future inevitable. System architecture: (1) Data Fusion Hub — captures and normalizes all relevant signals (CRM, ops metrics, comms, market feeds, sentiment) via secure ingest pipelines + vector store (Pinecone) + real-time ETL. (2) Causal Insight Engine — maps cause-effect chains behind current KPI drift and latent threats using ReAct-based diagnostic agent + causal graph builder. (3) Prescriptive Action Layer — generates specific, executable interventions ranked by ROI. Proactive > Reactive: every model spots weak signals, projects second- and third-order effects, and prescribes counter-measures before pain is felt. AaaS delivery: drop-in modular agents that execute inside the client's stack.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b68109a493d2c6f7b223ca", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68109a493d2c6f7b223ca", "captured_at": "2026-07-25" } ], "related": [ "lex:aaas" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-FW-004" ] }, { "id": "lex:neuruh-reasoning-engine", "slug": "neuruh-reasoning-engine", "term": "Neuruh Reasoning Engine", "aliases": [ "Neuruh Reasoning Engine — Anti-Black-Box Transparent AI Architecture" ], "kind": "canon", "type": "framework", "definition": "Transparent AI system architecture that forces explainability at every decision point. Anti-black-box infrastructure: AI that shows its work, challenges bad assumptions, and never hides behind vague responses. Core innovations: (1) Anti-goal quality gates — built-in checks that prevent sycophantic AI behavior and technical debt accumulation. (2) Challenge Protocol — agent actively pushes back on incorrect operator inputs rather than agreeing. (3) Glass-box architecture — every reasoning step is logged and explainable. (4) Dependency protection — prevents platform AI lock-in by building sovereign reasoning infrastructure. Solves: the Trust Problem (black-box AI creates liability), the Sycophant Problem (AI that agrees with wrong inputs builds technical debt), the Dependency Problem (platform AI locks users into extraction cycles). Executive summary document exists in Drive.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b68197ba56e1acc61b245a", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68197ba56e1acc61b245a", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-FW-010" ] }, { "id": "lex:neuruh-signal-iq-agent", "slug": "neuruh-signal-iq-agent", "term": "Neuruh Signal IQ Agent", "aliases": [ "Neuruh Signal IQ Agent — React Lead Intelligence Dashboard" ], "kind": "canon", "type": "system", "definition": "Full React TypeScript component implementing 4-stage lead processing pipeline with live visualization. Stages: (1) Lead Cleaner Pro — syntax validation, email/phone format checks. (2) Recursive Signal Engine — Gemini 2.5 Flash API call for name repair, industry inference, location enrichment, signal strength scoring. (3) Enrichment Pipeline — applies AI repairs, normalizes data (john doe → John Doe). (4) Scoring and Delivery — algorithmic grade (A/B/C/D) with score ring visualization. Features: pipeline node animation, live terminal log, data table with tier badges, AI outreach email generator via Gemini, add/reset lead functionality, score ring SVG component.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b6816b8d18e5670e3b43ab", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b6816b8d18e5670e3b43ab", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:LEAD-CB-008" ] }, { "id": "lex:neuruh-universal-modular-prompt-generator", "slug": "neuruh-universal-modular-prompt-generator", "term": "Neuruh Universal Modular Prompt Generator", "aliases": [ "Neuruh Universal Modular Prompt Generator — AaaS God-Tier Engine" ], "kind": "canon", "type": "framework", "definition": "Universal prompt generation engine producing any type of output (description, photo, ad copy, analysis, code, etc.) from nine consistent structural parameters: (1) Intent — purpose/desired outcome. (2) Angle/Perspective — physical, conceptual, or creative viewpoint. (3) Subject — primary focus. (4) Style/Tone — mood, genre, energy. (5) Attributes/Features — key descriptive qualities. (6) Context/Setting — environment or scenario. (7) Condition/State — new/used/aged/upgraded. (8) Audience/Usage — who it is for. (9) Outcome/Goal — ad, sale, pitch, instruction, visualization. Claude-ready, agent-ready, multi-vertical. The foundation layer beneath all specialized Token-Swap systems (House Image Generator, Veo3 Video, Constraint Engineering protocol).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b6817b9512e362fd73ae6b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6817b9512e362fd73ae6b", "captured_at": "2026-07-25" } ], "related": [ "lex:token-swap-prompting" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:CORE-SW-UMPG-1.0-GA" ] }, { "id": "lex:neuruh-visual-cortex", "slug": "neuruh-visual-cortex", "term": "Neuruh Visual Cortex", "aliases": [ "Neuruh Visual Cortex — Brand-Aligned AI Video Generation Engine" ], "kind": "canon", "type": "system", "definition": "Agentic AI video generation system producing brand-compliant video content. Architecture: Brand DNA ingestion layer (logos, color palettes, typography, voice/tone docs) → visual consistency enforcer → AI video generation (Runway Gen-3 / Kling) → brand compliance checker → output with Topaz upscale. Produces video content that passes brand guidelines automatically — no post-production brand corrections needed. GitHub repo exists (neuruh-visual-cortex). Connected to DaVinci v5 (Text-Stability Video Pipeline) and the Neurator creative platform. Target users: agencies needing consistent branded video at scale, solo creators building personal brand libraries.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b6817fb302feab37bc46b7", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6817fb302feab37bc46b7", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:MEDIA-CB-004" ] }, { "id": "lex:neuruh-visual-cortex-architecture", "slug": "neuruh-visual-cortex-architecture", "term": "Neuruh Visual Cortex Architecture", "aliases": [], "kind": "canon", "type": "framework", "definition": "A vision-first cognition layer that turns screen, doc, and diagram into structured signal — not an OCR pipeline.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/c5efe4d8b7a748ffad27418fec72d923", "provenance": [ { "source": "card", "ref": "https://app.notion.com/p/c5efe4d8b7a748ffad27418fec72d923", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-04-24", "source_ids": [ "card:AI-FW-015" ] }, { "id": "lex:neuruh-worker-1", "slug": "neuruh-worker-1", "term": "Neuruh Worker 1", "aliases": [ "Neuruh Worker 1 — IP Logger" ], "kind": "canon", "type": "system", "definition": "Python CLI worker that files candidate IP assets to the Neuruh IP Registry via Notion API. Auto-generates Asset IDs using VERTICAL-TYPE-### convention, sets all required registry fields, and returns the new ID.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/847a8f7f3e6849da9f0eddd5e94b38c9", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/847a8f7f3e6849da9f0eddd5e94b38c9", "captured_at": "2026-07-25" } ], "related": [ "lex:ip-registry" ], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-CB-W01" ] }, { "id": "lex:neuruh-worker-2", "slug": "neuruh-worker-2", "term": "Neuruh Worker 2", "aliases": [ "Neuruh Worker 2 — Build Status Updater" ], "kind": "canon", "type": "system", "definition": "Python CLI worker that flips Build State on an IP Registry entry by Asset ID. Validates state against allowed values and updates via Notion API.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/3c11f13dbdd84cb5ab63bc15b1b39738", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/3c11f13dbdd84cb5ab63bc15b1b39738", "captured_at": "2026-07-25" } ], "related": [ "lex:ip-registry" ], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-CB-W02" ] }, { "id": "lex:nimdp-validator", "slug": "nimdp-validator", "term": "NIMDP Validator", "aliases": [], "kind": "canon", "type": "protocol", "definition": "Launch Readiness Firewall — Python tool that gates project launches against the Neuruh Integrated Market Domination Protocol. CI/CD pipeline passing. First asset to mint DOI on Zenodo via GitHub Release.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/332a981d75b681f48498f4f3d31b39e0", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681f48498f4f3d31b39e0", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:CORE-PR-NIMDP-1.0-GA" ] }, { "id": "lex:nkf", "slug": "nkf", "term": "NKF", "aliases": [ "Superintelligence Knowledge Framework", "Superintelligence Knowledge Framework (NKF) V1.0", "Superintelligence Knowledge Framework (NKF)", "NKF v1.0", "NKF v1.0 — Superintelligence Knowledge Framework", "NKF v1.0 (Neural Core Knowledge Framework)" ], "kind": "canon", "type": "framework", "definition": "A modular knowledge + reasoning operating structure for precision-guided agent execution, including logic, prompt, security, and tone governance layers.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/cb4573e22c0142fc86fb5d531a936636", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/cb4573e22c0142fc86fb5d531a936636", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/77a8bb5a9160457eaed237a5d4427522", "captured_at": "2026-07-25" }, { "source": "card", "ref": "https://app.notion.com/p/a17f77bed6a444d0b6aa1ff6a8181b8b", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-04-14", "source_ids": [ "card:AI-MTH-008", "ip:AI-FW-037", "ip:AI-FW-NKF-001" ] }, { "id": "lex:nmil", "slug": "nmil", "term": "NMIL", "aliases": [ "Neuruh Metaverse Intelligence Layer", "NMIL — Neuruh Metaverse Intelligence Layer (AI Boardroom App)" ], "kind": "canon", "type": "system", "definition": "AI boardroom application with five AI personas with distinct voices, personalities, decision frameworks. Personas: Lincoln (leadership), Buffett (financial), Sun Tzu (strategy), DA Reyes (legal), VC Chen (venture). Stack: Next.js 14/16, Supabase, Claude API (claude-sonnet-4-6), ElevenLabs voice, Framer Motion scene engine, Vercel. 24 files, 4,704 lines. Each persona has confirmed ElevenLabs voice ID. Scene engine handles persona switching, dialogue sequencing, boardroom context injection.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b681eeb31af173d0c57ff4", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681eeb31af173d0c57ff4", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-CB-018" ] }, { "id": "lex:notion-auto-exporter", "slug": "notion-auto-exporter", "term": "Notion Auto-Exporter", "aliases": [ "Notion Auto-Exporter — Checkbox-Triggered Page Download Tool" ], "kind": "canon", "type": "system", "definition": "Node.js CLI tool that connects to Notion API, reads a page with checkboxes, downloads all checked linked pages as markdown, groups by build section, creates combined files for NotebookLM upload. Could be open-sourced or packaged as a developer tool.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/11172ed6e5534031a7ea6a6d2965b9be", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/11172ed6e5534031a7ea6a6d2965b9be", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:AI-CB-NOTIONEXPORT-001" ] }, { "id": "lex:nra", "slug": "nra", "term": "NRA", "aliases": [ "NRA v2", "Neuruh Research Agent Framework", "NRA v2 — Neuruh Research Agent Framework (Modular Multi-Agent, Containerized)" ], "kind": "canon", "type": "framework", "definition": "Modular multi-agent research framework. LangChain + AutoGen vertical agents, Pinecone/Weaviate shared vector memory, APScheduler (default) or Celery/cron task scheduling, Python-first CLI + Docker deployment, Twilio/SendGrid/Zapier notifications, Temporal optional for heavy workflows. v2 adds agent routing layer, short-term + long-term memory fusion, structured tool abstraction, and a reference end-to-end weekly-research walkthrough.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a94083b435584aed873674efee57c341", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a94083b435584aed873674efee57c341", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-028" ] }, { "id": "lex:objection-handling-library", "slug": "objection-handling-library", "term": "Objection Handling Library", "aliases": [ "Objection Handling Library — Prospect Responses" ], "kind": "canon", "type": "framework", "definition": "Complete objection handling script library for AI SaaS sales. Covers price, trust, timing, and competitor objections.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/7964c03db5514181a22f6bfedc8a7908", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/7964c03db5514181a22f6bfedc8a7908", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [ "ip:SALES-MTH-006" ] }, { "id": "lex:ocn-hybrid-inference-architecture", "slug": "ocn-hybrid-inference-architecture", "term": "OCN Hybrid Inference Architecture", "aliases": [ "OCN Hybrid Inference Architecture — Local Bonsai + Cloud Groq Task Routing" ], "kind": "canon", "type": "framework", "definition": "Hybrid local/cloud inference architecture for the OCN stack. Routes tasks by complexity: Bonsai 4B/8B (local, zero cost) handles classification, scoring, short inference. Groq Llama 3.3 70B (cloud) handles heavy reasoning as fallback. Hot-swappable LoRA adapter routing enables domain-specific inference without model retraining. Multi-agent local stack: 4-5 Bonsai 4B instances (0.57GB each) run simultaneously on M1. Apache 2.0 base model clears white-label path.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/225eef13788641d584eb87799fd3fc08", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/225eef13788641d584eb87799fd3fc08", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-31", "source_ids": [ "ip:OCN-FW-HYBRID-001" ] }, { "id": "lex:omnia-6", "slug": "omnia-6", "term": "OMNIA-6", "aliases": [ "Six-Layer Prompt System", "OMNIA 6", "OMNIA-6 — Six-Layer Composite Agent Architecture Framework", "OMNIA-6 (Prompt Architecture)" ], "kind": "canon", "type": "framework", "definition": "Master prompt architecture. Six layers that map to cacheable prompt sections.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681b7bc95e228fcab908a", "captured_at": "2026-07-25" }, { "source": "card", "ref": "https://app.notion.com/p/658052707db84fa4984f8520c86a80af", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "card:AI-FW-011", "ip:AI-FW-012", "kb:AI-FW-003" ] }, { "id": "lex:omnia-sovereign-core", "slug": "omnia-sovereign-core", "term": "Omnia Sovereign Core", "aliases": [], "kind": "canon", "type": "framework", "definition": "A hermetically sealed, self-architecting AI operating system that enables sovereign deployment of prompt mesh networks and federated data workflows. Designed for organizations requiring air-gapped, self-modifying AI infrastructure with cryptographic integrity and universal timeline coordination across distributed nodes.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/35ca981d75b6812a87a5d66ed5d499ae", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/35ca981d75b6812a87a5d66ed5d499ae", "captured_at": "2026-07-25" } ], "related": [ "lex:prompt-mesh" ], "status": "published", "first_seen": "2026-07-25", "source_ids": [ "ip:WORLD-PLATFORM-OMNIA-1.0" ] }, { "id": "lex:on-site-cv-damage-estimator", "slug": "on-site-cv-damage-estimator", "term": "On-Site CV Damage Estimator", "aliases": [], "kind": "canon", "type": "system", "definition": "FastAPI endpoint that accepts 3-5 photos and returns PDF with damage type, severity score, estimated repair cost, and confidence level. Powered by YOLOv8 or GPT-4V. Logs to Airtable Damage Assessments.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/3ce4301af2824e6d8274edd6924eab4f", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/3ce4301af2824e6d8274edd6924eab4f", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:HI-CB-CVEST-001" ] }, { "id": "lex:opportunity-heatmap-pro", "slug": "opportunity-heatmap-pro", "term": "Opportunity HeatMap Pro", "aliases": [ "Opportunity HeatMap Pro (OHP) v2", "OHP", "Opportunity HeatMap Pro (OHP)", "Opportunity HeatMap Pro (OHP) v2 — Geospatial Opportunity Intelligence Stack" ], "kind": "canon", "type": "product", "definition": "Automated system for sourcing undervalued real estate/business opportunities from public data.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b6811e9b9af60b7533c811", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/8ab8581148054b53bfb7462991a5d851", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-AGENT-HEATMAP-1.0-CONCEPT", "ip:RE-CB-029" ] }, { "id": "lex:orbital-command", "slug": "orbital-command", "term": "Orbital Command", "aliases": [ "Orbital Command — High-Level Agent Orchestration Layer" ], "kind": "canon", "type": "system", "definition": "Meta-orchestration system that manages agent fleets at scale. Handles agent lifecycle (spawn, monitor, terminate), resource allocation, priority queuing, and cross-agent conflict resolution. The L5 Roof layer coordinator for the entire Neuruh HOUSE architecture.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/23a7bf1f9dfa472898a267ce477f796e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/23a7bf1f9dfa472898a267ce477f796e", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [ "ip:CORE-CODE-ORBITAL-1.0-BUILT" ] }, { "id": "lex:p2p-av", "slug": "p2p-av", "term": "P2P-AV", "aliases": [ "P2P-AV v2", "P2P-AV v2 — Peer-to-Peer Autonomous Taskforce Marketplace" ], "kind": "canon", "type": "system", "definition": "Two-sided marketplace where rural AV-pod owners list their vehicles for neighbor bookings (mulch, equipment, furniture hauls), turning idle autonomous assets into community infrastructure. v2 adds swappable payload modules, dynamic surge pricing, and community rating with dispute resolution.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/c4ca2b839b1245a986d39d5628ebdb0b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/c4ca2b839b1245a986d39d5628ebdb0b", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:OPS-CB-006" ] }, { "id": "lex:patch", "slug": "patch", "term": "PATCH", "aliases": [], "kind": "canon", "type": "concept", "definition": "Fix one specific thing, don't touch anything else.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [] }, { "id": "lex:phantom-deck", "slug": "phantom-deck", "term": "PHANTOM DECK", "aliases": [ "PHANTOM DECK — Phone-as-Orchestrator Mobile Command Hub", "PHANTOM DECK — Phone-as-Orchestrator Command Hub", "PHANTOM DECK — Phone-First Command Center" ], "kind": "canon", "type": "system", "definition": "Centralized command/control plane. Operator initiates a command; AXON reads intent and orchestrates the swarm. Single cockpit over the entire grid.", "definition_basis": "verbatim", "definition_source": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.phantom-deck", "provenance": [ { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.phantom-deck", "captured_at": "2026-07-20" }, { "source": "notion", "ref": "https://app.notion.com/p/4185561dba014c5e8cd65f47b0cb8a38", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/ad1d16f308ef4c20bc77159bd225515b", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/93fc10c8530a46fda8512e86ffb99b7f", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-02", "source_ids": [ "codex:canon.phantom-deck", "ip:AI-CB-004", "ip:AI-CB-PHANTOM-001", "ip:OPS-CB-PHANTOM-001" ] }, { "id": "lex:pmla", "slug": "pmla", "term": "PMLA", "aliases": [ "Prompt-as-Memory Loop Architecture", "PMLA — Prompt-as-Memory Loop Architecture", "PMLA — Prompt-as-Memory Loop Architecture (Expanded Spec)" ], "kind": "canon", "type": "framework", "definition": "5-block memory injection system. Makes agents context-aware across sessions.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b68100af90e2460d313cd4", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68141b189da3d0a622532", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/38f497625c134335b2a9fea7a4dccd2c", "captured_at": "2026-07-25" }, { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.pmla", "captured_at": "2026-07-20" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "codex:canon.pmla", "ip:AI-FW-031", "ip:AI-FW-PMLA-002", "ip:AI-PT-010", "kb:AI-FW-001" ] }, { "id": "lex:pmla-benchmarking-suite", "slug": "pmla-benchmarking-suite", "term": "PMLA Benchmarking Suite", "aliases": [ "PMLA Benchmarking Suite — Drift & Constraint Performance Tests" ], "kind": "canon", "type": "system", "definition": "Comparative benchmarking suite for PMLA vs pure prompt engineering, RAG, LangChain memory, and semantic caching. Measures constraint adherence, validation latency, memory overhead, drift detection accuracy. Exports results as Markdown, CSV, JSON, and interactive charts.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/00a87e92f6c0450aae005f6cc1de4c4f", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/00a87e92f6c0450aae005f6cc1de4c4f", "captured_at": "2026-07-25" } ], "related": [ "lex:pmla" ], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-CB-BENCH-001" ] }, { "id": "lex:pmla-core-engine", "slug": "pmla-core-engine", "term": "PMLA Core Engine", "aliases": [ "PMLA Core Engine — Reference Implementation v1.0.0" ], "kind": "canon", "type": "system", "definition": "Production-ready Python reference implementation of PMLA. Ships ConstraintBlock (MCB), IntentPreservationLayer (IPP), PMLAEngine orchestrator, ValidationLevel/ConstraintType/EnforcementAction enums, ConstraintRule + ValidationResult dataclasses, built-in metrics + audit log export, and a financial underwriting example demonstrating block/warn/correct enforcement.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a5b133ee02b84b32b381a3fc07e77465", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a5b133ee02b84b32b381a3fc07e77465", "captured_at": "2026-07-25" } ], "related": [ "lex:pmla" ], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:AI-CB-PMLA-001" ] }, { "id": "lex:predictive-opportunity-mapping", "slug": "predictive-opportunity-mapping", "term": "Predictive Opportunity Mapping", "aliases": [ "POM", "Predictive Opportunity Mapping (POM)" ], "kind": "canon", "type": "framework", "definition": "Machine learning parcel upside scoring model producing a 0-100 score for any property based on deed, permit, MLS, demographic, and financial signal inputs. Core intelligence layer feeding REI-X deal prioritization. Distinct from Acquisition ScoreCard (which is a human-completed 25-factor matrix) — POM is the automated ML scoring engine.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b68145af83fd851207cc07", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68145af83fd851207cc07", "captured_at": "2026-07-25" } ], "related": [ "lex:acquisition-scorecard", "lex:rei-x" ], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-FRAME-POM-1.0-BUILT" ] }, { "id": "lex:preventable-death-intelligence-stack", "slug": "preventable-death-intelligence-stack", "term": "Preventable Death Intelligence Stack", "aliases": [], "kind": "canon", "type": "framework", "definition": "AI-powered prevention system for avoidable mortality.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681f2adeed0ceb01d9223", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:HEALTH-AGENT-PDI-1.0-CONCEPT" ] }, { "id": "lex:probe", "slug": "probe", "term": "PROBE", "aliases": [], "kind": "canon", "type": "concept", "definition": "Research + intel gathering, no build yet.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [] }, { "id": "lex:prompt-mesh", "slug": "prompt-mesh", "term": "Prompt Mesh", "aliases": [ "Prompt Mesh — Multi-Agent Coherence Protocol" ], "kind": "canon", "type": "protocol", "definition": "Named design pattern within the Neuruh Standard / Templar-Grade Agentic Loop architecture. Functions alongside Vault-Injection to transform generic AI capability stacks into specialized cognitive operating systems. Documented with ™ symbol in Drive. Distinct from Token-Swap Prompting — Prompt Mesh is a structural agent design pattern, not an image generation methodology.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b681e08412e39c64c7b46f", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681e08412e39c64c7b46f", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b68141b64eef52f4ae8261", "captured_at": "2026-07-25" } ], "related": [ "lex:token-swap-prompting", "lex:the-neuruh-standard" ], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:CORE-ARCH-PROMPT-MESH-1.0-CONCEPT", "ip:CORE-PR-PMESH-1.0-GA" ] }, { "id": "lex:pulsebus", "slug": "pulsebus", "term": "PulseBus", "aliases": [ "PulseBus — Real-Time Agent Message Broker", "PulseBus — Event-Driven Agent Message Bus", "PulseBus — Global Event Streaming (Apache Pulsar)" ], "kind": "canon", "type": "system", "definition": "Real-time message broker for multi-agent AI systems. Redis Streams-backed pub/sub with consumer groups, request/reply patterns, dead-letter queues, TTL, message persistence and replay. Supports fan-out, rate limiting, retry with exponential backoff. The nervous system connecting all Neuruh agents. Stack: Node.js, Redis Streams, TypeScript. Package: @neuruh/pulsebus.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/8e0b68312fab42f5bdd009642035258c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/8e0b68312fab42f5bdd009642035258c", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/13657da07963422688c0d95ed2483980", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/85ffdd32cc8e494287f7d3f115f99c9a", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:AI-CB-006", "ip:AI-CB-PULSEBUS-001", "ip:CORE-CODE-PULSEBUS-1.0-BUILT" ] }, { "id": "lex:qchn", "slug": "qchn", "term": "QCHN", "aliases": [ "Quantum-Classical Hybrid Networks", "QCHN — Quantum-Classical Hybrid Networks", "Quantum-Classical Hybrid Networks — Braket Adapter for QFA Engine" ], "kind": "canon", "type": "concept", "definition": "AXON Adapter SDK extension for AWS Braket / IBM Quantum / Azure Quantum backends. Router selects quantum for provable optimization problems (TSP, SAT, portfolio); classical fallback for general compute. 18-36 month horizon for commercial quantum viability.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/47758c44df8544b3bc213b5d6ee79a81", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/47758c44df8544b3bc213b5d6ee79a81", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/47847189be9a42dc999d134eeb4a9235", "captured_at": "2026-07-25" } ], "related": [ "lex:axon-adapter-sdk" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-QCHN-001", "ip:AI-RE-QUANTUMHYBRID-001" ] }, { "id": "lex:qeca", "slug": "qeca", "term": "QECA", "aliases": [ "Quantum Emergent Consciousness AI", "QECA — Quantum Emergent Consciousness AI", "QECA — Quantum Emergent Consciousness AI (Theoretical Framework)" ], "kind": "canon", "type": "concept", "definition": "Research framework for post-quantum AI consciousness modeling.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b681e4ac89fa74ead7dec2", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681acba90d783d27f3fee", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "ip:AI-FW-034", "ip:AI-RES-003", "kb:AI-RES-001" ] }, { "id": "lex:quantum-prompt-lattice", "slug": "quantum-prompt-lattice", "term": "Quantum Prompt Lattice", "aliases": [ "QPL", "Quantum Prompt Lattice (QPL)", "Quantum Prompt Lattice (QPL) — Prompt Engineering Control System", "Quantum Prompt Lattice (QPL) v2", "Quantum Prompt Lattice (QPL) v2 — Prompt Engineering Control System" ], "kind": "canon", "type": "framework", "definition": "Advanced prompt engineering control system using quantum-inspired lattice structures to organize, version, and deploy prompts at scale. A lattice of interconnected prompt nodes where each node has defined inputs, outputs, dependencies, and failure modes. Lattice properties: (1) Superposition — a prompt node can hold multiple valid interpretations simultaneously until context collapses it to a specific output. (2) Entanglement — changing one prompt node automatically propagates updates to all entangled nodes. (3) Coherence maintenance — the lattice enforces semantic consistency across all nodes. Purpose: replaces ad-hoc prompt libraries with a structured, version-controlled, dependency-aware system. Full document in Drive (too large to fetch).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b6817e8150cb885f614680", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b6817e8150cb885f614680", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/86ffd038737c42c8a9bdc3da15891ba9", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:AI-FW-009", "ip:AI-FW-020" ] }, { "id": "lex:real-estate-intelligence-os", "slug": "real-estate-intelligence-os", "term": "Real Estate Intelligence OS", "aliases": [], "kind": "canon", "type": "framework", "definition": "Comprehensive AI-powered operating system for real estate professionals integrating deal sourcing, property analysis, ESG compliance, tenant management, and portfolio optimization. Combines autonomous agents for off-market acquisition, rental optimization, comp analysis, and sustainability tracking into a unified intelligence platform. Serves the full lifecycle from deal discovery through property management and decarbonization.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-07-25", "source_ids": [ "ip:WORLD-REALESTATE-REOS-1.0" ] }, { "id": "lex:real-estate-prompt-pack", "slug": "real-estate-prompt-pack", "term": "Real Estate Prompt Pack", "aliases": [ "Real Estate Prompt Pack (40+)", "Real Estate Prompt Pack (40+) — REI-X" ], "kind": "canon", "type": "framework", "definition": "40+ prompt library covering the full REI-X workflow: underwriting, hook outreach, zoning analysis, negotiation, marketing copy, and more. Structured as deployable prompt stacks per function. Includes REI-X Guardrail & Logic Files (master JSON with variables, fallback routes, rate limits, safety filters).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "captured_at": "2026-07-25" } ], "related": [ "lex:rei-x" ], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:RE-PROMPT-PACK-40-1.0-BUILT" ] }, { "id": "lex:regimenator", "slug": "regimenator", "term": "Regimenator", "aliases": [ "Regimenator — AI Daily Preventive Life Manager" ], "kind": "canon", "type": "system", "definition": "Regimenator™ — Daily Preventive Life Manager. Recreates Galen's daily regimens with modern data inputs. Generates AM-midday-PM day plan considering user's age, climate, sleep quality, and labor type. Includes dietary suggestions, timing, rest moments, and environmental exposure (light, cold, wind, heat). References both ancient seasonal principles and modern circadian research. Integrates with calendars, meal plans, and smart home devices. Full system prompt and I/O schema documented. Outputs: AM-midday-PM breakdown, sleep cycle reinforcement, seasonal awareness coaching, overstimulation warnings.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b68113afded065962fe640", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68113afded065962fe640", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:HEALTH-AGENT-GAAS-REGIMENATOR-1.0-BUILT" ] }, { "id": "lex:rei-x", "slug": "rei-x", "term": "REI-X", "aliases": [ "Real Estate Intelligence Execution Stack", "REI-X Stack" ], "kind": "canon", "type": "product", "definition": "Full-suite, agent-powered RE ops system (sellers, agents, brokers, ops).", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/3c48ca3132574937a3f3d729a93eb578", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:RE-CB-024" ] }, { "id": "lex:repurpose-capsule", "slug": "repurpose-capsule", "term": "Repurpose Capsule", "aliases": [ "Repurposing Logic" ], "kind": "canon", "type": "framework", "definition": "Advanced workflow for breaking content or processes into reusable, reconfigurable outputs.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b681cab08efad31b5349ba", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:CREATOR-TOOL-REPURPOSE-1.0-BUILT" ] }, { "id": "lex:rituals-and-resets-library", "slug": "rituals-and-resets-library", "term": "Rituals & Resets Library", "aliases": [ "Rituals & Resets Library (Mirror-X)" ], "kind": "canon", "type": "framework", "definition": "Prescriptive actions to restore balance when a DIMEA layer drops: digital silence, bio burn-and-rewrite, enemy-map, anonymous-creation, 36h alignment fast. Fires automatically from drift detection.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/0d7d0ed5e48c4fe8971e623242959385", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/0d7d0ed5e48c4fe8971e623242959385", "captured_at": "2026-07-25" } ], "related": [ "lex:dimea-2-0" ], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "ip:CM-MTH-RITUALS-001" ] }, { "id": "lex:rural-express", "slug": "rural-express", "term": "RURAL-EXPRESS", "aliases": [ "RURAL-EXPRESS v2", "RURAL-EXPRESS v2 — VTOL Drone-to-Porch Delivery Network" ], "kind": "canon", "type": "system", "definition": "VTOL drone network that bypasses poor rural road infrastructure to deliver small-payload essentials (hardware bits, tools, pharmacy, ag-supply) within a 10-mile radius from local sky-pads. v2 defines the retailer plugin, sky-pad co-op model, and BVLOS-ready safety stack.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/4af7618c75b545df91530bbac9012ba5", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/4af7618c75b545df91530bbac9012ba5", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:OPS-CB-004" ] }, { "id": "lex:sakl", "slug": "sakl", "term": "SAKL", "aliases": [ "Sovereign AI Knowledge Layer" ], "kind": "canon", "type": "framework", "definition": "Localized cryptographic ledger. Every breakthrough, code optimization, or extracted high-yield lead gets an immutable signature proving exact lineage and local origin. The IP shield for off-grid intelligence.", "definition_basis": "verbatim", "definition_source": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.sakl", "provenance": [ { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.sakl", "captured_at": "2026-07-20" } ], "related": [], "status": "published", "first_seen": "2026-07-01", "source_ids": [ "codex:canon.sakl" ] }, { "id": "lex:sal", "slug": "sal", "term": "SAL", "aliases": [ "Stacked Agent Logic", "SAL — Stacked Agent Logic", "SAL (Stacked Agent Logic)" ], "kind": "canon", "type": "framework", "definition": "Modular, layered chains of specialized AI agents executing recursive, auditable workflows.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/5a77422a5a0e46b7a7d5b7521ba7e42e", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/c269f9c577de46db886ac58c3b01816b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681e6a994f2787efd8d43", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" }, { "source": "notion", "ref": "https://app.notion.com/p/332a981d75b68127933fede95f99defd", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/d3ae6f8fdd1a4b85b88c045dc7a6e497", "captured_at": "2026-07-25" }, { "source": "repo", "ref": "repo:NeuruhAI/neuruh-vault@75e4cff:05-CODEX/canon-codex_v6.json#canon.sal", "captured_at": "2026-07-20" } ], "related": [], "status": "published", "first_seen": "2026-03-29", "source_ids": [ "codex:canon.sal", "ip:AI-FW-032", "ip:AI-FW-SAL-001", "kb:AI-FW-002" ] }, { "id": "lex:sal-stack", "slug": "sal-stack", "term": "SAL Stack", "aliases": [ "SAL Stack (Signal Convergence Engine)" ], "kind": "canon", "type": "framework", "definition": "A signal convergence engine that turns N noisy data streams into one scored action signal.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/c2e1a071a5294480a3e6a28a490730c8", "provenance": [ { "source": "card", "ref": "https://app.notion.com/p/c2e1a071a5294480a3e6a28a490730c8", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-04-24", "source_ids": [ "card:AI-FW-010" ] }, { "id": "lex:sales-pipeline-intelligence", "slug": "sales-pipeline-intelligence", "term": "Sales Pipeline Intelligence", "aliases": [], "kind": "canon", "type": "framework", "definition": "AI-powered lead generation and sales pipeline management system that automates prospect identification, qualification, and nurturing. Delivers actionable intelligence through pipeline audits and conversion optimization for B2B sales teams and agencies.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/35ca981d75b68108bfc0d374ca7861eb", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/35ca981d75b68108bfc0d374ca7861eb", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-07-25", "source_ids": [ "ip:WORLD-RESALE-PIPELINE-1.0" ] }, { "id": "lex:scaffold", "slug": "scaffold", "term": "SCAFFOLD", "aliases": [], "kind": "canon", "type": "concept", "definition": "Generate full file structure for new project.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/336a981d75b681abb775d2b7090e281b", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-05", "source_ids": [] }, { "id": "lex:self-model-gpt", "slug": "self-model-gpt", "term": "Self-Model GPT", "aliases": [ "Self-Model GPT — Personalized Cognitive Mirror Framework" ], "kind": "canon", "type": "framework", "definition": "Personalized GPT framework that mirrors a user's behavioral logic, tone, and decision-making process. Built for self-alignment, strategy refinement, tone consistency. Target: high-performance individuals, visionary system architects. v1.0, Neuruh Public Utility License. Five core features: Behavioral Mirror Engine, Logic Stack Integration, Tone Signature Mapping, Strategic Prompt Architect, Feedback Loop Enhancer.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/514fbe7e98224ac4bbd393cbb5fb8527", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/514fbe7e98224ac4bbd393cbb5fb8527", "captured_at": "2026-07-25" } ], "related": [ "lex:mirror" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-SELFMODELGPT-001" ] }, { "id": "lex:self-model-loop", "slug": "self-model-loop", "term": "Self-Model Loop", "aliases": [ "Self-Model Loop — Self-Modeling Intelligence Pattern" ], "kind": "canon", "type": "framework", "definition": "Self-Model Loop / Self-Modeling Intelligence — a named architectural pattern that builds a living, evolving mental model of the user or business rather than just critiquing agent output. The model evolves over time, affecting tone, decisions, and behavior prediction. Replaces Layer 4 (Self-Reflection) in OMNIA-6 with a meta-aware, continuously updating cognitive scaffold. Used in Mirror-X1, StudioGPT feedback, and any identity-retaining agent. Distinct from the Mirror-X1 Self-Model Schema (which is the JSON implementation) — this is the architectural pattern.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/339a981d75b68154bc44e64bacf60640", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/339a981d75b68154bc44e64bacf60640", "captured_at": "2026-07-25" } ], "related": [ "lex:studiogpt", "lex:omnia-6", "lex:mirror" ], "status": "published", "first_seen": "2026-04-04", "source_ids": [ "ip:CORE-PATTERN-SELFMODEL-1.0-BUILT" ] }, { "id": "lex:semantic-fuse", "slug": "semantic-fuse", "term": "Semantic Fuse", "aliases": [ "Semantic Fuse — Guardrail Circuit for AI Input Safety", "SF-2024 Semantic Fuse", "SF-2024 “Semantic Fuse” — Active Safety Logic Gate", "Semantic Fuse / Guardrail Circuit", "SF-2024", "Semantic Fuse (SF-2024)" ], "kind": "canon", "type": "protocol", "definition": "Safety protocol modeled on an electrical fuse. Input passes through a fuse-box that runs parallel checks (Toxicity, PII, others). Any trip signal opens the circuit breaker and returns a safe refusal. Safe inputs pass to the cognitive unit. Canonical schematic: Figure 2.3 in the Cognitive Schematics Library.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/d758fae0320c4157a234534cd6811030", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/d758fae0320c4157a234534cd6811030", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/ba51c0243fbd4d969c855ba51cdb0f13", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/db21566238db4ac49116ad25301f48f4", "captured_at": "2026-07-25" }, { "source": "card", "ref": "https://app.notion.com/p/ad02858429ed4017a2f4e5b20eedee76", "captured_at": "2026-07-02" } ], "related": [], "status": "published", "first_seen": "2026-04-16", "source_ids": [ "card:AI-FW-016", "ip:AI-CB-SEMFUSE-001", "ip:AI-FW-FUSE-001", "ip:AI-PR-004" ] }, { "id": "lex:sep", "slug": "sep", "term": "SEP", "aliases": [ "Sandbox Escape Protocols", "SEP — Sandbox Escape Protocols", "Sandbox Escape Protocols — Graduated Agent Privilege Escalation" ], "kind": "canon", "type": "framework", "definition": "4-tier agent privilege ladder (Read-only → Write-scoped → Multi-tool → Full). Promotion rules: tier N+1 requires M successful tier-N tasks + rollback-free 48h. Every escalation cryptographically signed via Ether Layer. Demote on any violation. Enterprise-palatable path to agent autonomy.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/ac0f1541bdb64b1a81a79885523e79f2", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/ac0f1541bdb64b1a81a79885523e79f2", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/ca9952ccf4c441d48482c0960aefe8be", "captured_at": "2026-07-25" } ], "related": [ "lex:ether-layer" ], "status": "published", "first_seen": "2026-04-17", "source_ids": [ "ip:AI-FW-SANDBOXESCAPE-001", "ip:AI-FW-SEP-001" ] }, { "id": "lex:session-auto-loader", "slug": "session-auto-loader", "term": "Session Auto-Loader", "aliases": [ "Session Auto-Loader — Notion + Supabase Context Sync" ], "kind": "canon", "type": "system", "definition": "Node.js service querying Notion IP Registry, Agent Registry, and Supabase Dream Service to build complete session context briefs. Eliminates manual context pasting. Shell alias + cron support.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/cfcc980301204e90ad416de91e5da043", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/cfcc980301204e90ad416de91e5da043", "captured_at": "2026-07-25" }, { "source": "notion", "ref": "https://app.notion.com/p/75792370e2154a78b155d152e2612277", "captured_at": "2026-07-25" } ], "related": [ "lex:dream-service", "lex:ip-registry" ], "status": "published", "first_seen": "2026-04-03", "source_ids": [ "ip:CORE-CODE-AUTOLOADER-1.0-BUILT", "ip:NEURUH-SAL-010" ] }, { "id": "lex:session-log", "slug": "session-log", "term": "Session Log", "aliases": [], "kind": "canon", "type": "system", "definition": "Database tracking session-level records and handoffs.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/a9887d9fc8e84ac0b0cd5d22f2e8d89c", "captured_at": "2026-10-05" } ], "related": [], "status": "published", "first_seen": "2026-04-07", "source_ids": [] }, { "id": "lex:ship-packet-protocol", "slug": "ship-packet-protocol", "term": "Ship Packet Protocol", "aliases": [ "Ship Packet Protocol — Unified Build Deployment Standard" ], "kind": "canon", "type": "protocol", "definition": "Standardized single-page format for every Neuruh build containing all deployment state in one view: (1) Repo status (GitHub URL, branch, last commit). (2) Deploy status (Vercel/Firebase URL or 'not deployed'). (3) Env vars (list of required keys and where they live). (4) Live URL or 'pending'. (5) Next action (one executable sentence). Unifies DEPLOY 30, GitHub Rebuild Queue, and Session Briefs into one repeatable artifact. Eliminates blank-page time when starting a deploy. Notion AI generates these automatically from session notes. Each build gets exactly one Ship Packet page, updated in place.", "definition_basis": "verbatim", "definition_source": "https://app.notion.com/p/333a981d75b681478888f2cce43f818a", "provenance": [ { "source": "notion", "ref": "https://app.notion.com/p/333a981d75b681478888f2cce43f818a", "captured_at": "2026-07-25" } ], "related": [], "status": "published", "first_seen": "2026-03-30", "source_ids": [ "ip:OPS-PT-001" ] }, { "id": "lex:signature-extraction-protocol", "slug": "signature-extraction-protocol", "term": "Signature Extraction Protocol", "aliases": [], "kind": "canon", "type": "concept", "definition": "Protocol for extracting and encoding a person's unique linguistic, cognitive, and behavioral signature into a language model's operating context. Enables deep personalization of AI agents to mirror specific operator voices, decision patterns, and communication styles. 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Four model buckets: (1) Experimentalist — lab manuals and measurement techniques. (2) Electromagnetism — early electrical theory and wireless comms (War of Currents era). (3) Analytical Chemist — qualitative/quantitative analysis pre-digital spectroscopy. (4) Scientific Pedagogy — how science was taught at different complexity levels. 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Uses OMNIA-6 to replace manual bid estimations with logic-based geometric calculations and autonomous memory triggers for high-volume apartment project bids. Blue-collar AI vertical deployment. 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