Less AI rework.
More engineering capacity.
GitMir reads your product's business logic straight from your code. Every task is audited automatically, and rework hotspots are mapped to the business logic that caused them — so AI changes stop surprising you late.
Rework gets an address.
Rework gets an address
Every correction loop is traced to the business-logic area that caused it — not to a vague "the agent got it wrong".
Both prices of every change
Before code is written you see what a change touches and what it will cost — in engineering time and in risk.
Nothing to change to get it
Your developers keep Claude Code, Codex or Cursor. GitMir plugs into the workflow you already run.
The expensive area names itself
Rework concentrates in specific parts of the product. The map shows exactly where your money goes.
Late discoveries stop surprising you
Hidden dependencies and impacted invariants surface before the change ships, not in production.
A number you can act on
Rework share, validation time and acceptance rate — measured continuously on your own workload.
What the model of your product changes.
| Metric | Without GitMir | With GitMir |
|---|---|---|
| Rework share of change | 69% | 22% |
| Changes accepted per quarter | 100 | 138 |
| Minutes to validate an agent task | 45 min | 8 min |
| Weekly rework hours per engineer | 6.5 h | 2.4 h |
| Minutes before writing code | 90 min | 20 min |
| Days to first accepted change | 21 days | 4 days |
| PM hours to size one change | 16 h | 0.3 h |
ILLUSTRATIVE MODEL AS PUBLISHED ON IDE.GITMIR.COM — YOUR BASELINE IS MEASURED ON YOUR OWN WORKLOAD.
The product, drawn from the code.
Product map
Entities, modules and their relations — the system as objects, not files.
Business processes
Journeys and lifecycles reconstructed end to end, with every step traceable to source.
Data flows
What moves where — across services, events and integrations.
Change impact
The reach of a change computed from the graph before the first line is written.
Lifecycles
Status flows made explicit: which transitions are legal, which are forbidden.
Ownership
Who owns which part of the logic — visible to people and to agents.
PLUGS INTO: CLAUDE CODE · CODEX · CURSOR · GITHUB ACTIONS · GITLAB CI · LINEAR · JIRA · SLACK · PULL REQUESTS
Where the hours come back.
The agent reads the rules, the states and the dependencies instead of guessing at them — so the second pass stops being where the work is.
What it touched and what it reached is on the model, so review is a look rather than an archaeology.
The blast radius is computed from the model in both directions — the answer is a screen instead of three meetings.
The business logic is drawn — the objects, the rules, the states — so the reading is minutes, not an afternoon.
A person or an agent starts from the object context rather than from the repository and whoever is free to explain it.
The answer is on a screen both people are looking at, so the question stops being asked.
The same team, the same hours — less of them spent recovering understanding somebody already had.
The model lands in the tools you already open.
We wire the model into the agents, the pipeline, the tracker, the review and the chat — so nobody has to visit a new place to get the answer. You keep every tool; they just stop asking each other what the product does.
Claude Code, Codex and Cursor — one local MCP per machine. No new editor and no new subscription.
The model rebuilds on merge, so the map is never a branch behind the code.
A ticket arrives carrying what it will reach, and the model's ids travel with it to the PR.
Impact in both directions, the rules it touches and the checks it owes — posted on the change itself.
The collision and the late discovery land in the channel at the moment they are found — not at review.
Start at zero.
Open Source
- Full product model on your codebase
- Run it locally, inspect everything
Connect
- The whole team sees what is being built
- Shared object context, no code upload
Team & Enterprise
- Private deployment and integrations
- Outcome-based engagements