Git Analytics That Doesn't Break the Bank

Transform your repository data into actionable insights. Measure developer productivity, optimize workflows, and ship better software faster—at a fraction of the cost.

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Enterprise-Grade Analytics. Startup-Friendly Pricing.

Engineering leaders need visibility into team performance, but enterprise tools like GitPrime cost thousands per month. Gitrolysis delivers the same powerful analytics at up to 70% lower cost—making data-driven engineering accessible to teams of all sizes.

For Engineering Managers

Stop guessing about team capacity. Get real-time insights into cycle time, throughput, and bottlenecks across your entire engineering organization.

For Development Teams

Identify blockers before they derail sprints. Track pull request velocity, code review patterns, and deployment frequency to continuously improve.

For Leadership

Make informed decisions with executive dashboards that connect engineering metrics to business outcomes. Prove ROI and optimize resource allocation.

Everything You Need to Optimize Engineering Performance

Comprehensive Repository Analytics

Connect GitHub, GitLab, Bitbucket, or Azure DevOps in seconds. Analyze commits, pull requests, code reviews, and deployment data from all your repositories in one unified dashboard.

Developer Productivity Metrics

Track DORA metrics, SPACE framework indicators, cycle time, throughput, and more. Understand where your team excels and where improvements matter most.

Real-Time Team Dashboards

Customizable dashboards for every role—from individual contributors to C-suite executives. Filter by team, project, or time period with intuitive visualizations.

Code Review Intelligence

Optimize your review process with insights into review time, comment patterns, approval rates, and reviewer workload. Eliminate bottlenecks and improve code quality.

Sprint & Project Tracking

Integrate with Jira, Linear, and other project management tools. Connect git activity to sprint goals and see how engineering work maps to business objectives.

Trend Analysis & Forecasting

Identify patterns over time with historical analytics. Predict delivery timelines, capacity constraints, and technical debt accumulation before they become problems.

Track the Metrics Top Engineering Teams Rely On

Cycle Time

How long from first commit to deployment.

Deployment Frequency

How often you ship to production.

Pull Request Size

Average lines changed per PR.

Review Time

Time from PR creation to merge.

Code Churn

Percentage of code rewritten within 3 weeks.

Work Distribution

Balance of new features vs maintenance.

Commit Patterns

When and how your team works best.

Collaboration Score

Cross-team knowledge sharing metrics.