Knowledge Graphs for AI Coding Assistants
Graphify turns code, docs, PDFs, screenshots, diagrams, and transcripts into one queryable graph so your assistant can answer architecture questions with structure instead of guesswork.
Sign in → Upload ZIP → Explore graph (graphify.homes)Mixed corpus benchmark from the official project examples.
Tree-sitter parsing across modern programming languages.
graph.html, graph.json, and GRAPH_REPORT.md stored in your account.
Open-source, commercial-friendly, telemetry-free by default.
Architecture at a glance
Imports, calls, classes, docstrings, and rationale comments stay attached to the same graph.
Query the graph weeks later without rereading the entire repository from scratch.
Share a human-readable report with teammates or load the graph into your own tooling.
Built for the messy reality of modern codebases
Keyword search can locate files. Graphify explains how those files, decisions, and artifacts connect.
Multimodal extraction
Read code, docs, PDFs, screenshots, diagrams, transcripts, and rationale in one pass.
Structure-first graph build
Combine AST edges, semantic links, and design notes into a queryable NetworkX graph.
Community clustering
Leiden clustering groups subsystems by topology, not by another embedding layer.
God nodes and surprises
Surface architectural gravity wells and unexpected cross-file connections worth investigating.
Web-first workflow
Upload a project ZIP and explore the graph in the browser—no local Python install required for the cloud product.
Secure-by-design
Strict input validation, bounded downloads, path containment, and escaped output labels.
Query the why, not just the where
Graphify uses static analysis for hard structure, then enriches the corpus with semantic edges, rationale, and multimodal context. Instead of pushing every question through a fresh vector retrieval loop, it gives your assistant a durable graph of the system.
That means path explanations, community views, god nodes, and surprise edges are first-class outputs, not accidental artifacts of one lucky prompt.
Detect
Collect code, prose, visual references, and media into one corpus.
Extract
Use Tree-sitter and semantic extraction to produce nodes, edges, and rationale.
Build
Merge everything into a persistent graph instead of a disposable prompt context.
Cluster
Reveal subsystems with Leiden communities and highlight graph centers.
Explain
Answer graph queries, path lookups, and architectural why-questions.
Export
Ship graph.html, graph.json, GRAPH_REPORT.md, and incremental cache artifacts.
Graph intelligence, not another pile of chunks
Build a graph without a local install
Upload a ZIP from the Build page. We extract it safely, run Graphify on our servers, and keep graph.html, graph.json, and GRAPH_REPORT.md in your account. You do not need Python or pip install in the browser workflow.
Sign in → Upload ZIP → Explore graph (graphify.homes)Self-hosted CLI installs are only for contributors or IDE integrations—not required for this product.
Straight answers for technical buyers
How do I use Graphify on this site?+
Sign in with Google, upload a ZIP of your project from the Build page, and we run Graphify in the cloud. You get graph.html, graph.json, and GRAPH_REPORT.md saved to your account—no local install required.
Does Graphify send raw source code to a third-party model?+
The upstream Graphify pipeline may call your configured model for semantic passes; see the official project for details. This product runs builds on our servers with credentials you configure in deployment.
Can I still use assistants like Claude Code locally?+
Yes. The open-source Graphify project integrates with Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and other assistants. graphify.homes focuses on the hosted ZIP workflow.
What artifacts do I get back?+
A visual graph, a durable graph.json, a human-readable report, and a cache that makes repeat runs cheaper.