Connect your repositories, documentation and business data. GitMir turns them into a living source of truth — high-precision information models of how your systems actually work.
Visual for people. High-density, minimal context for AI agents and tools through MCP.
Current. Traceable. Updated with your systems.
GitMir has already built a reusable understanding of how Supabase Studio works — what it does, what depends on what, and what a change could affect. Normally, a person or AI agent has to reconstruct the relevant part of that understanding from implementation for every new task. Here, it already exists. We call this Product Intelligence. Ask Supabase Studio anything — or let me show you why that changes the workflow.
Claude Code, Cursor, Sourcegraph, Augment and the rest of your engineering stack already help people and AI reach the right implementation, dependencies and history. GitMir adds the understanding of how the product works that would otherwise have to be rebuilt for every new task.
For each new task, the relevant product understanding still has to be reconstructed from implementation context.
The product understanding is already there — for this task, the next task and the next person or agent.
Keep your tools. Give them the same understanding of the product.
GitMir turns that shared understanding into reusable Product Intelligence.
Claude Code · Cursor · Codex · Linear · Jira · Sourcegraph · Augment · CodeRabbit
See how GitMir works with your stackGit shows how the code changed. GitMir keeps those changes connected to the product. Across analyzed commits, you can see which product areas, behaviours, screens and customer paths each change reached. Implementation-only commits remain visible without being presented as product changes.
20 MOST RECENT COMMITS · 14 TOUCHED MODELLED BEHAVIOUR · 6 MOVED CODE ONLY · MODEL BUILT 2026-08-29
Explorer
notebooks data
applyNotebookOperation
1 file outside the current model — picked up on the next update.
AI Assistant
AI assistant core, AI endpoints
getAIDetails, generateAssistantResponse, aiGenerateHandler
AiOptIn
Project
projects data
getProjectDetail
Project
Project status flow
Each commit of Supabase Studio is mapped onto the model through the files the model was read from. The cabinet goes further on your own repository: every push updates the model, and the history compares two builds to say what was added, changed, renamed or removed.
MEASURED ON THE PUBLISHED SUPABASE SCOPE — APPS/STUDIO + PACKAGES/PG-META — AT THIS VERSION AND THIS QUESTION WORKLOAD.
Connect one repository. GitMir builds a reusable understanding of how your product works, so your people, AI agents and existing tools can work from the same product picture.
One understanding of your product. Reused by every person, agent and task that needs it.
3,000 STARTING INTELLIGENCE CREDITS INCLUDED
Tell us what you would want to ask, analyze, compare or understand next. We use this feedback to decide what capabilities to build next.
Most systems stop at files, functions, dependencies or tasks. GitMir can lift the same source reality into higher-order Intelligence — only as far as the person, AI or process needs.
Code, APIs, services, data, screens and technical relationships.
Business logic, behavior, entities, flows, dependencies, requirements and change impact.
Multiple products and repositories combined into shared operational, legal and organizational context.
Strategy, risk, validation, market comparison and proactive intelligence built on the same source of truth.
Get the answer, validation or visibility you need without reconstructing the underlying system yourself.
Serve sufficient high-density context instead of making every model rediscover meaning from raw implementation.
Connect existing workflows through MCP and let the same Intelligence support automation, monitoring and execution.
TRUSTED · CURRENT · SUFFICIENT · VERIFIABLE · UNDERSTANDABLE
The information usually exists. The expensive part is finding it, reconstructing it, checking it and making it understandable every time it is needed.
Human attention, senior engineering time and AI context are repeatedly spent recovering understanding that already existed somewhere in the company.
The Intelligence Layer stays available, evolves with the source and can be reused by the next person, model, workflow or automated process.
Not another tool to replace your stack. A better source of Intelligence for the work your people, AI and systems already do.
Ask what exists, how it works, what changed or what a requirement touches — without investigating the source manually.
Compare requirements, product logic and implementation to validate what was actually built.
Analyze impact, risk, market position, product gaps or company-wide questions from structured Intelligence.
Bring Intelligence into Claude, Codex, Cursor, internal agents and enterprise workflows through MCP.
Keep visibility into changes, autonomous work and product reality while reducing manual inspection and supervision.
Use GitMir Compute or your own agents to execute with sufficient context and less expensive reconstruction.
Accuracy is only useful when the Intelligence is also sufficient, compact and fast enough to reuse. We measure the result — and publish it.
| Input | Quality | Context | Cost |
|---|---|---|---|
| GitMir | 92% | 8.4K | $0.07 |
| Unblocked | 78% | 27.4K | $0.19 |
| Raw repository context | 58% | 61.3K | $0.41 |
Start with one repository. Keep your tools and workflow. Add a reusable source of Intelligence that can grow from implementation to product and company-wide context.
