Docs
Enzyme compiles content into a concept graph — under 15 seconds for 1,000+ documents. Queries run on-device in ~8ms. No conversation history needed. These pages explain how the engine extracts cross-cutting connections, what the agent receives, and why it works whether the content is a personal vault or a product's user corpus.
Setup
Install, point at your notes, explore.
How it works
The compile step: from content corpus to searchable concept graph.
Arriving knowing the room
The LSP analogy: what it means when your agent has structural understanding before the conversation starts.
Catalysts
Pre-computed questions that cut across your content — the search layer that keyword and vector search can't reach.
The guide
A weight map that tells enzyme what to focus on.
Apply
Project your concept graph onto an unfamiliar corpus. Your lens, their content.
How memory compounds
Temporal structure, questions over conclusions, and what happens when agents write back.
In practice
Short clips from real work sessions where enzyme changed what the agent found.