Git AI is the vendor-agnostic, open standard for tracking AI-generated code through the entire SDLC. The Self-Hosted Enterprise Edition provides leading observability into your Agents and the code they write.
Track AI-lines through the entire SDLC
Git AI tracks AI-generated lines from any agent, preserving them through any Git operation — rebase, squash, cherry-pick, etc.—so attribution is never lost.
PR level token costs, time savings, % AI code
See how much each PR costs, what percentage of code is AI-generated, and how efficiently your team collaborates with Coding Agents on different kinds of work.
Understand the Full Lifecycle of AI code
Who generated it? Who approved it? How many incidents are tied to it? How long did it stay in the codebase before being removed or rewritten?
% AI Code
83%
▲ up from 63% 1mo ago
Code Durability
2x
AI code churns 2x faster · ▼ down from 4x
Token Efficiency
100 : 18
lines generated that make it to production
Incident Rate
1.2x
more incidents from AI-generated code
Median Developer
1.2
agents at a time
62%
AI code
1.8x
faster per storypoint
Agents are expanding codebases faster than ever—but developers still have to maintain these systems. Git AI securely stores prompts so developers and agents can understand what each line is doing and how it got there.
The “why” for every line
Git AI links AI-generated code to the prompts that created it. Intent, requirements, and decisions stay with the code—forever.
AI Blame
See which code was AI-generated and what it's supposed to do, in the IDE.
Own your prompts
Prompts are the new source code—don't let vendors own them. Git AI makes prompts portable and lets you store them on your own infrastructure.
Past Prompts Make Agents Smarter
When agents can read past prompts and understand what existing code is supposed to do, they make fewer mistakes and produce more maintainable code.
Tooling is 1% of the journey. Git AI helps your engineers prompt better and learn to manage multiple agents at once. Because we have observability into every interaction and the full lifecycle of AI-generated code, we can identify what works—and help you spread best practices faster.
Prompt analysis
Discover which prompting practices work best for the types of problems your team is solving.
Personal dashboards
Private dashboards help engineers track their progress, get tailored feedback, and learn from how others are using agents.
Real data on what works
Run evals on new MCPs, skills, and changes to your agent configs. Know whether each change leads to code that holds up in production.
Your Developer Dashboard
73% of your Code is written with AI
Code DurabilitySolid!
85% in prod after 3wks
Parallel AgentsGreat!
2.1 agents at once
Agent Thrash
141 generated lines : 1 to prod
PR Accepted Rate
72% (low)
Your Partners for this year's AI-initiatives
Accelerate your AI Journey with Data
This is the year to become an AI-native engineering org. Git AI can help you get there faster, without sacrificing quality, security, or maintainability.