GitMir vs Greptile
Greptile reviews a pull request against a graph of the codebase. GitMir reviews what the commit changed in the business logic of the product.
The same repository, questions
and AI model for both.
Fifty questions in the words work is assigned in, the same model and settings for every system, answers graded blind.
Greptile works with the code
and its sources. GitMir works
with the business logic.
Greptile
Review-time reasoning over files, functions, classes and dependencies, scoped to the change in front of it.
Reviews pull requests against a graph of the codebase, catching what a diff alone hides. The reasoning happens at review time and is scoped to the change; the understanding it builds is spent on that PR rather than accumulated as a product model.
GitMir
Features, rules, customer paths and how they connect, built from your code and kept current with every commit.
GitMir establishes what a product does once, from the repository, and serves each task only what it needs — with every statement traceable to the source it came from.
Understanding built for one pull request is spent on that pull request. The next change starts from nothing again, and so does the next agent.
| Dimension | Greptile | GitMir |
|---|---|---|
| Primary layer | Code Review | Meaning / Product |
| What it understands | Files, functions, classes, dependencies | What the product does and how it behaves |
| Relationships | Code graph | Business + technical |
| AI agent context | Review agents | Established product knowledge |
| Change impact | PR / code impact | Product-logic level |
| Primary buyer | Engineering teams | CTO / VP Eng / Product / AI |
Positioning per each vendor’s own public description. Nothing here says a tool is bad at what it is built for.
Keep Greptile. Add the business logic.
Code review and business-logic review answer different questions about the same commit, and a team can run both.
Asked before choosing.
Code review and business-logic review answer different questions about the same commit, and a team can run both.
Benchmark 001: one repository, fifty questions in the words work is actually assigned in, the same AI model and settings for every system, answers graded blind. GitMir answered 92% correctly against 66% for Greptile, on 8.4K tokens of context per question against 42.7K. The full method and every number are published.
Understanding built for one pull request is spent on that pull request. The next change starts from nothing again, and so does the next agent. GitMir builds the business logic of the product once — features, rules, customer paths and how they connect — keeps it current with every commit, and gives the part a task touches to people and to AI.
GitMir vs Unblocked →GitMir vs Augment Code →GitMir vs Sourcegraph →GitMir vs Qodo →