PViz compresses any repository into a structured analysis bundle that fits within your LLM's context window — so Claude, GPT, or Cursor understands your full architecture, not just fragments.
Dependency graphs, cycle detection, architectural metrics, and LLM-ready bundles for Python, TypeScript, JavaScript, Go, Java, and Rust — in minutes.
Large codebases exceed LLM context limits. You paste partial files, get partial answers, and make decisions based on incomplete context.
PViz generates a compressed structural bundle of your entire repo — architecture, dependencies, and metrics — sized to fit your context window.
PViz generates a complete structural analysis bundle and optional AI report so you can orient, assess risk, and plan changes with confidence.
Build a cross-repo graph of modules, packages, and dependencies to understand architecture at a glance.
Organize large repositories into meaningful zones so you can reason about systems, boundaries, and change impact.
Get a clear breakdown of code size by language, directory, and hotspots to prioritize attention.
Identify dependency cycles and high-coupling areas that may slow refactors and increase change risk.
Ask up to 5 questions and receive answers grounded in the PViz bundle — plus a concise evidence appendix.
Export your compressed bundle directly into Claude, GPT, or Cursor for accurate, whole-codebase conversations.
Browse our FastAPI longitudinal analysis — 9 versions, full dependency graphs, and architectural metrics generated by PViz.
