GitAI - 2026 Pricing, Features, Reviews & Alternatives

GitAI is a Git extension that records line-level attribution for AI-generated code directly in Git Notes, linking each AI-written line to the agent, model, and prompt that produced it. Attribution persists through all Git operations, including rebases, merges, squashes, cherry-picks, stash/pops, and resets, without requiring workflow changes, Git hooks, or wrapping the Git binary. Agents self-report the lines they wrote via checkpoint hooks, eliminating heuristics and secondary AI detection. Available as a free, open-source CLI that works offline with no login required, and a paid Teams tier deployable as managed cloud or fully self-hosted, with enterprise rollout supported via MDM across an entire engineering organization with no per-repo configuration.

GitAI targets software engineering teams of all sizes, from small development shops to Fortune 100 enterprises, that use AI coding agents and need structured visibility into AI code adoption, quality, and cost. Cross-agent observability covers Cursor, Claude Code, GitHub Copilot, Gemini, OpenCode, RovoDev, and OpenAI Codex from a single platform. Per-contributor, per-PR, per-repo, and org-wide dashboards surface token spend broken down by agent, model, commit, PR, repository, team, and individual. Code durability measurement tracks how long AI-written code survives before being rewritten or removed, and incident correlation connects production issues back to the exact agent session, model version, and prompt responsible.

Built on Git Notes as an open standard, GitAI avoids vendor lock-in and integrates with existing CI workflows and data warehouse exports. Agent Readiness scoring evaluates repository preparedness for AI-assisted development, and MCP configurations, skills, and agent rule changes can be assessed against real production outcomes. Token spend is tied to individual PRs, repos, and teams rather than monthly aggregates, giving engineering leaders the granular cost data needed to evaluate ROI across the full software development lifecycle, from prompt to production.