Graphify-Labs / graphify

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 Cut agent token spend by 80%. Graphify Cloud is always-on memory that governs your agents, keeps code quality high, and proves correctness with formal verification. Start a free 14-day trial → 
Type `/graphify` in your AI coding assistant and it maps your entire project (code, docs, PDFs, images, videos) into a **knowledge graph** you can **query instead of grepping** through files.
- **Code maps for free, fully local.** Code is parsed with tree-sitter AST: deterministic, no LLM, nothing leaves your machine. (Docs, PDFs, images and video use your assistant's model, or a configured API key, for a semantic pass.)
- **Every edge is explained.** Each connection is tagged `EXTRACTED` (explicit in the source) or `INFERRED` (resolved by graphify), so you can tell what was read directly from what was inferred.
- **Not a vector index.** No embeddings, no vector store: a real graph you traverse. Ask a question, trace the path between two things, or explain one concept.
> [!NOTE]
> **Want this always-on?** Graphify Cloud keeps the graph live across your entire SDLC: monorepo and cross-repo support, formal verification, and code review with a bird's-eye view of your SDLC, plus connectors for Sentry, Jira, and more so incidents and tickets sit in the same graph as your code. **Start a free 14-day trial at app.graphify.com**.
 The FastAPI codebase mapped by graphify. Every node is a concept, colors are detected communities, and the whole thing is clickable in graph.html. 
**Get started** (30 seconds). Needs Python 3.10+ and uv (or pipx):
 [code] 
Then, in your AI assistant:
 [code] 
That's it. You get **three files**:
 [code] 
The persisted graph includes `graph.schema_version` so integrations can detect
incompatible format changes, plus `graph.graphify_version` identifying the
Graphify release that produced it.
**One install, any assistant, any OS.** Claude Code, Cursor, Codex, Gemini CLI, GitHub Copilot, and 20+ more, on macOS, Linux, and Windows: pick your platform.
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## See it in action
Once the graph is built you query it instead of reading files. Real output, graphify run on the FastAPI codebase shown above:
 [code] 
Every edge carries a **confidence tag** (`EXTRACTED` = explicit in the source, `INFERRED` = derived by resolution), so you can tell what was read directly from what was inferred. `graphify query " "` returns a scoped subgraph for a plain-language question, and `graphify path A B` traces how any two things connect.
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## What it does
What you get out of the box:
| Capability | What you get |
|---|---|
| **God nodes** | The most-connected concepts, so you see what everything flows through |
| **Comm