We Don't Index Content.
We Build Cognitive Architecture.
The Master Graph Extraction Protocol
A 4-week systematic process to transform tacit knowledge into permanent intellectual infrastructure.
The Difference Between Tools and Assets
Cheap chatbots are tools—you rent them monthly. A Master Graph is infrastructure—you own it permanently. The difference isn't just ownership. It's architectural sophistication.
Standard AI Tools (Vector RAG)
Search engines with conversational interfaces
How They Work:
- • Upload your content (books, PDFs, transcripts)
- • AI converts text to mathematical vectors
- • User asks question → AI finds "similar" text chunks
- • AI summarizes what it found
What This Enables:
- • FAQ answering
- • Basic content retrieval
- • Keyword-based responses
What This Cannot Do:
- • Multi-hop reasoning across concepts
- • Temporal understanding (how thinking evolved)
- • Semantic mapping (connecting different terminology)
- • True cognitive fidelity
Business Implication: Tools for basic support. Not infrastructure for empire-building.
Master Graph Architecture (GraphRAG)
Structured cognitive infrastructure
How It Works:
- • Extract mental models through proprietary interviews
- • Map conceptual relationships, not just content
- • Build custom ontology for your domain
- • Create traversable knowledge architecture
What This Enables:
- • Multi-hop reasoning ("How does X connect to Y through Z?")
- • Temporal coherence (evolution of thinking over time)
- • Semantic intelligence (concept matching beyond keywords)
- • True cognitive fidelity (thinks like you, not echoes you)
Business Implication: Infrastructure that powers subscription products, licensing programs, and legacy systems simultaneously.
Real-World Difference: Side-by-Side
Question: “How would you handle a market downturn?”
Vector RAG Response:
Searches for “market” + “downturn” → Returns text chunks mentioning those words → Generic business advice
GraphRAG Response:
Traverses graph → Finds your framework “The Winter Harvest” (which never uses word “downturn”) → Connects to your 2021 refinement on interest rates → Synthesizes your specific strategy using your reasoning
The Outcome: Vector RAG sounds like generic AI. GraphRAG achieves Cognitive Fidelity—it thinks like you, not just echoes you.
Cognitive Fidelity is the standard. Not "close enough." Not "good enough." But genuine intellectual precision—capturing your reasoning, your logic, your unique way of connecting ideas.
This is what justifies premium investment. This is what protects your reputation. This is why empire builders choose infrastructure over tools.
The Hallucination Shield
Your Reputation. Your Liability. Your Protection.
Standard AI tools are liability risks. They "fill in gaps" when uncertain—inventing facts, fabricating quotes, generating content that could damage your reputation or expose you to legal risk.
The Problem:
- •Generic AI hallucinates when it doesn't know
- •No audit trail for where responses come from
- •Your brand reputation depends on unverified outputs
- •Legal liability for AI-generated misinformation
The Master Graph Solution:
1. Evidence-Based Architecture
Every entity in your Master Graph includes supporting quotes—your actual words from verified sources. Every AI response traces back to specific nodes. Complete audit trail.
2. Constrained Generation
Your Cognitive Asset only generates responses that connect to verified nodes in your Graph. If it can't find a logical path through your actual thinking, it acknowledges uncertainty—it doesn't invent.
3. Quality Assurance Layer
During the 90-day optimization period, you flag anything misaligned. We trace it to the Graph and fix the source logic. The improvement applies to all future responses automatically.
4. Permanent Verification
Unlike subscription AI tools that change models without notice, your Master Graph is stable. What worked yesterday works tomorrow. No surprise hallucinations from model updates.
You can trust your Cognitive Asset with your reputation. It won't invent credentials you don't have, claim expertise you haven't developed, or generate content inconsistent with your worldview.
This is infrastructure-grade reliability—not rental-tool risk.
Building Cognitive Infrastructure
This isn't content collection. It's systematic excavation of how you think—the frameworks you use unconsciously, the connections you make intuitively, the logic beneath your expertise.
Cognitive Archaeology
The Objective: Extract your unconscious competence—the patterns you use without naming them.
What Happens:
- • 8-10 hours of structured interviews (3-4 sessions)
- • Proprietary framework for extracting tacit knowledge
- • Processing of all source material (books, courses, transcripts, recordings)
- • Initial pattern recognition across your body of work
Your Involvement:
- • Active participation in interviews (we ask questions you've never considered)
- • Review of source material processing
- • Validation of initial framework identification
What You Receive:
Semantic chunks with rich metadata • Initial framework map showing your conceptual structure • First glimpse of patterns you use unconsciously
In the Vitale project: 177 semantic chunks with 94.4% content coverage from 34 source files.
Ontological Architecture
The Objective: Design the custom schema that will house your cognition.
What Happens:
- • Custom ontology design for your domain
- • Node type definition (concepts, methods, frameworks, principles, beliefs)
- • Relationship type mapping (enables, contradicts, evolves, supersedes, requires)
- • Entity extraction and classification from Week 1 material
Your Involvement:
- • Review the ontology blueprint
- • Validate how concepts connect in your worldview
- • Approve the architectural schema before construction
What You Receive:
Complete ontology documentation • Schema visualization (how your thinking is structured) • Entity classification system
In the Vitale project: 21 custom node types and 60+ relationship types designed for consciousness and manifestation concepts.
Graph Construction
The Objective: Build the actual Master Graph from architectural plans.
What Happens:
- • Entity resolution and deduplication across sources
- • Relationship building between all concepts
- • Cross-chunk discovery (finding implied connections)
- • Evidence attachment (your exact words supporting each node)
- • Temporal property assignment (when you believed what)
Your Involvement:
- • Minimal (automated construction phase)
- • Available for clarifying questions on ambiguous connections
What You Receive:
Complete Master Graph • Technical documentation package • Initial query testing results
In the Vitale project: Cross-chunk discovery found 72.8% more connections than initial extraction—545 total relationships from 408 entities.
Cognitive Calibration
The Objective: Ensure perfect fidelity—it must think like you, not approximate you.
What Happens:
- • Comprehensive stress testing across all response types
- • Voice preservation tuning (cadence, vocabulary, tone)
- • Query routing optimization (balancing speed and depth)
- • Edge case handling (what happens when it doesn't know?)
- • First deployment implementation (your chosen application)
Your Involvement:
- • Active testing (“Does this sound like me?”)
- • Feedback on any response that feels off
- • Approval before any deployment
What You Receive:
Production-ready Master Graph • Your first strategic deployment • 90-day optimization support begins
We don't ship until you approve. Every response is tested against: “Would I say this this way?” Cognitive fidelity is non-negotiable.
Explore a Real Extraction
This is a portion of Joe Vitale's Master Graph—408 nodes, 535 relationships, extracted from his complete body of work on manifestation and spiritual awakening.
Loading knowledge graph...
408 nodes • 535 relationships
Explore a portion of Joe Vitale's Master Graph. This is the foundation that powers his AI mentor, assessment tools, marketing and content generation systems.
Why GraphRAG Wins
For the technically sophisticated: here's why Master Graph architecture outperforms commodity AI across every meaningful dimension.
Multi-Hop Reasoning
The Challenge: "How does your view on entrepreneurship connect to your philosophy on conscious parenting through the lens of your 2021 writing on systems thinking?"
Why Vector RAG Fails:
Retrieves three separate chunks. Can't traverse relationships across concepts. Attempts to stitch together unrelated fragments.
How GraphRAG Solves:
Follows relationship paths: entrepreneurship → influenced_by → systems_thinking(2021) → applies_to → conscious_parenting. Returns integrated answer showing how concepts genuinely connect in your worldview.
Business Value: Complex questions get sophisticated answers. This is what $197/month subscribers pay for—not keyword search.
Semantic Intelligence
The Challenge: You call your approach "The Winter Harvest." User asks about "recession strategies."
Why Vector RAG Fails:
Keyword mismatch. Vector similarity might not connect your unique terminology to generic questions. Returns irrelevant results or generic content.
How GraphRAG Solves:
Semantic relationships: winter_harvest is_type_of market_strategy addresses_problem recession. Finds your framework even when terminology differs.
Business Value: Your unique frameworks get deployed correctly—even when users don't know your terminology. This is cognitive fidelity at scale.
Temporal Coherence
The Challenge: Your 2015 book recommended X. Your 2023 book recommends Y (which contradicts X). Which is current?
Why Vector RAG Fails:
Treats all content equally. No concept of evolution or supersession. Might blend contradictory advice.
How GraphRAG Solves:
Temporal properties: belief_X(2015) superseded_by belief_Y(2023) reasoning: [new evidence]. Always returns current position while showing evolution.
Business Value: Your thinking evolves. Your Graph reflects that evolution accurately. Users get current you, not averaged you.
Holistic Synthesis
The Challenge: "What's your overall philosophy on leadership?"
Why Vector RAG Fails:
Searches for "leadership" → Returns text fragments → AI stitches them together → Creates false coherence from unrelated pieces.
How GraphRAG Solves:
Aggregates relationships: leadership → connects_to → 12 principles, 3 case_studies, 2 core_beliefs, 1 counter_example. Synthesizes from structure, not fragments.
Business Value: Holistic questions get coherent answers that reflect your integrated worldview—not a patchwork of fragments.
Evidence Traceability
The Challenge: User asks: "Where did this advice come from?"
Why Vector RAG Fails:
Black box. Can't trace reasoning back to sources. "The AI said it" is the only answer.
How GraphRAG Solves:
Every entity includes evidence quotes—your exact words. Every response traces back to specific nodes. Complete audit trail.
Business Value: Trust. Users see that responses come from your actual thinking, not AI confabulation. This is critical for premium positioning.
What You Own
At the end of 4 weeks, you receive permanent intellectual infrastructure—not a subscription service.
Asset 1: Your Master Graph
.JSON Knowledge Graph File
A structured database of your cognition—entities, relationships, temporal properties, evidence quotes, and semantic mappings.
- • Format: Platform-agnostic .JSON file
- • Size: Typically 400-500 entities, 500-600 relationships
- • Ownership: Yours permanently. No licensing, no subscriptions.
Hosting Options: We host (recommended) | You host (for technical teams) | Hybrid
Asset 2: Technical Documentation
Complete Schema Documentation
Complete schema documentation enabling future development and integration.
- • Ontology blueprint (your conceptual architecture)
- • Entity type definitions (what each node represents)
- • Relationship type catalog (how concepts connect)
- • Integration API documentation
- • Query pattern examples
Why This Matters: Your Graph can integrate with future platforms, AI models, or applications. You're never locked to our implementation.
Asset 3: First Strategic Deployment
Your Chosen Revenue Stream
We don't just deliver the Graph—we deploy it into your chosen revenue stream.
- • Subscription AI Mentor (recurring revenue product)
- • Content Multiplication Engine (marketing infrastructure)
- • Licensing Infrastructure (practitioner network backbone)
- • Institutional Intelligence (team leverage system)
- • Custom deployment (aligned with your strategy)
Included: Implementation code • User interface • System integration • Launch support
Asset 4: 90-Day Evolution Support
Continuous Optimization
Continuous optimization as you deploy and learn.
- • Unlimited refinement sessions
- • Response quality monitoring
- • Edge case handling
- • Voice preservation tuning
- • New relationship discovery
- • Query optimization
Why This Matters: The first deployment reveals usage patterns we couldn't predict. We optimize based on real-world performance.
Why Ownership Beats Rental
Most AI tools are subscriptions. Your Master Graph is infrastructure you own.
Subscription Model (Standard AI Tools)
- Pay $50-$500/month indefinitely
- Locked to vendor's platform
- Features change at vendor's discretion
- Data extraction often impossible
- If you stop paying, you lose everything
Ownership Model (Master Graph)
- One-time extraction investment
- Platform-agnostic architecture
- Full control over features and deployment
- Complete data portability
- Asset appreciates as you add to it
Future-Proof Architecture
The AI Landscape Changes:
- • New models emerge (GPT-6, Claude 5, etc.)
- • New platforms launch
- • New deployment options appear
- • New regulations affect vendors
Your Response:
Your Master Graph plugs into whatever comes next. The cognitive infrastructure is separate from the implementation layer.
Today: Deploy on OpenAI's GPT-4
Tomorrow: Switch to Anthropic's Claude
Next year: Use whatever model leads
Forever: Your Graph remains constant
Because You Own the Infrastructure:
Subscription tools can't do any of this.
Ready to Build Your Cognitive Infrastructure?
We extract your mental model into permanent intellectual assets—not temporary tools. If you're building empire, not renting software, let's talk.