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GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
Text-to-SQL tool that writes dialect-aware queries and gives AI agents governed, read-only database access.
Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.
Free open-source VS Code fork letting developers connect directly to any AI model without a proxy, for privacy-focused coders.
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦Contribution and work-quality analytics
- ✦Automated, AI-powered performance reviews
- ✦Retrospective insights
- ✦Operational bottleneck alerts
- ✦Gamification with XP, levels and leaderboards
- ✦Uses Git metadata without accessing source code
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- ✦Natural-language to SQL
- ✦Semantic schema layer
- ✦Governed MCP/REST gateway
- ✦Read-only query enforcement
- ✦7 database connectors
- ✦SQL explain, optimize and format
- ✦AI-summarized commit and PR reports
- ✦Daily and weekly scheduled digests
- ✦Slack and email delivery
- ✦One-click OAuth or webhook setup
- ✦GitHub, GitLab and Bitbucket support
- ✦Templates for standups and reports
- ✦Tab-key autocomplete suggestions
- ✦Inline quick-edit on selected code
- ✦Chat with agent, gather, and normal modes
- ✦Direct connections to any LLM provider, no proxy backend
- ✦One-click import of VS Code themes and settings
- ✦Checkpoints to track and revert LLM-made changes
- ✦Lint error detection
- ✦Fast apply designed for large, 1000+ line files
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
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- →Generating SQL without coding
- →Giving agents safe DB access
- →Explaining and fixing queries
- →Querying live databases
- →Keep stakeholders updated on what shipped
- →Replace manual status updates and standups
- →Give teams visibility into Git activity
- →Switching from Cursor or Windsurf while keeping data private
- →Running local open models like DeepSeek or Llama instead of paying per API call
- →Connecting directly to frontier models such as Claude or Gemini
- →Editing and refactoring large codebases with AI help