GitMir gives existing AI systems better intelligence about the product, business and environment they work inside — without changing the models or workflows.
DEVELOPED BY GITMIR RESEARCH · RESULTS PUBLISHED · METHOD PROPRIETARY
The same Intelligence, read by whatever is doing the work — the agent that changes your product, and the agent that runs it.
Engineering teams and coding agents understand a complex product before they change it: what a change touches, what depends on it, and what will break.
Support, billing and sales agents act on what is true right now: the customer, the plan, the entitlement, the rules and the current state.
One repository, fifty questions in natural English, the model and its settings held constant, answers graded blind. 92% correct against 78% for the strongest alternative, on a third of the context.
Read the benchmark →Whether a coding agent given the same human-language task actually completes it correctly — measured as successful implementation rather than as a graded paragraph.
Not yet publishedWhat a production agent workload costs per completed customer outcome, measured across a full run rather than a single request.
Not yet publishedA BENCHMARK APPEARS HERE WHEN IT HAS BEEN RUN, NOT WHEN IT HAS BEEN PLANNED.
People describe what they want in terms of products, customers, behavior and outcomes — not files, functions and dependencies. GitMir gives AI intelligence closer to the level of the original human intent, reducing the work required to reconstruct meaning from raw technical context.
Connect a GitHub repository. GitMir continuously updates intelligence as your software changes.
Source code stays in your environment. The GitMir Local Connector processes permitted sources locally and securely synchronizes derived Intelligence with GitMir.
Everything stays inside your boundary. Private GitMir deployment, private MCP, and VPC, on-prem or air-gapped options.
GitMir's intelligence technology is proprietary. We publish benchmark methodology and measurable outcomes without publishing the internal representation or interpretation system.