Your agents ship code faster than anyone can read it. Derivein turns the whole system into a living map — every file, service, workflow, and the decisions behind them — so you always know what’s there, what changed, and why.
AI coding tools are session-first. The context lives in a conversation that evaporates the moment it ends — and your codebase keeps growing in the dark.
Each new agent re-scans your repo from scratch, rebuilds a shaky mental model, and still can’t tell you why anything is the way it is. The reasoning never got written down.
To understand what your own AI just shipped, you open files, trace calls, and grep for the thing that broke. You’re doing archaeology on code that was written an hour ago.
Derivein derives a structured graph from your repo and keeps it live as your agents build. Ask it what you need; it assembles the smallest map that answers you — center outward, expand on click. Not a hairball. A view.
Files, services, components, deps, people — and the WHYs behind them — linked by what calls what, what depends on what, and what broke what. The structure, not the file tree.
depends-on · calls · decided-by · brokeTrace a real chain from the button, through the API, into the service and back. See the path a feature actually takes across the system — the flow, highlighted, not the folders it happens to live in.
ui → api → service → dataThe same graph holds what was planned, what got built, and what’s live in production — and lights up exactly where they’ve drifted apart. Catch the gap before it becomes an incident.
planned · shipped · in prodPose a task in plain language. Get back the exact subgraph that matters, decisions attached — for you, or injected straight into your agent over MCP so it starts already knowing the system.
get_context_for_task( )One graph carries three views of the same system. Every node is addressable across all three.
Specs, PRDs and notes become planned nodes — the backbone architecture, derived before a line is written.
The crawler watches planned nodes come alive as your agents implement them — parsed straight from the repo.
The system as it truly runs — so the map is never a stale diagram, but a reflection of reality.
Point Derivein at a repo and watch the system assemble itself into a map you can actually hold in your head.