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What Is This?

You give it documents. It finds the ideas, connects them, and remembers what contradicts what.

The 30-Second Version

Feed the system your documents - research papers, notes, articles, reports. It reads them and extracts the key ideas. Then it connects those ideas: this concept supports that one, this claim contradicts that one, this cause leads to that effect.

Unlike a search engine that just finds keywords, this system understands meaning. Ask "what causes inflation?" and it finds concepts related to inflation's causes - even if those exact words don't appear in your documents.

Unlike a chatbot that makes things up, every idea traces back to its source. You can always ask "where did this come from?" and get a real answer.

The Real Point

This isn't just a search tool for humans. It's infrastructure for AI that can reason about what it knows.

Most AI "memory" is just similarity search - find things that look like what you asked for. This system tracks:

  • Grounding: How well-supported is this idea? One source or twenty?
  • Contradiction: Do sources disagree? Which ones?
  • Provenance: Where exactly did this idea come from?

That's the foundation for AI that doesn't just retrieve information but reasons about how reliable it is.

Current state: AI assistants can query the system via standard protocols (MCP). Future state: The knowledge graph becomes part of how AI thinks, not just something it queries.

What Can You Do With It?

As a human: - Search your documents by meaning, not just keywords - See how ideas connect across different sources - Find where your sources contradict each other - Trace any claim back to its origin

As an AI agent: - Query persistent memory that survives across sessions - Get grounded answers with confidence levels - Reason about contradictions and uncertainty - Build knowledge incrementally over time

Next Steps