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Devv.AI
✓ verifiedPaid
AI search engine for developers with code repo integration.
52K visits/mo4.2K saves
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devActivity
✓ verifiedFreemium
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
52K visits/mo
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Watsonx.data
✓ verifiedFree trial
IBM's open, hybrid data lakehouse that connects, governs and optimizes enterprise data to make it AI-ready across clouds and on-premises.
Pricing
Historical Data Pack: $49.9
Base Plan: $14.9/month
Advanced Plan: $24.9/month
Enterprise Plan: $34.9/month
No public pricing
No public pricing
Free: $0/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)
No public pricing
Free trial available
Core features
- ✦Commits and Pull Requests Dashboard
- ✦Advanced Developer Skills Analysis
- ✦Strategic Investment Balance Monitoring
- ✦Collaborative Developers Map
- ✦Benchmarking Comparison with Other Teams
- ✦Smart Notifications
- ✦GitHub Mode for repository search
- ✦Web Mode for web-based information retrieval
- ✦Chat Mode for direct AI interaction
- ✦Model selection (GPT, Claude, Gemini)
- ✦Student discount program
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- ✦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
- ✦Open hybrid data lakehouse
- ✦Connects data across clouds and on-prem
- ✦Governance, lineage and access controls
- ✦Business-context enrichment
- ✦AI-ready data for analytics and models
Use cases
- →Visualize historical graphs of code evolution
- →Assess development team performance using RSI and EMA
- →Understand developer skills and identify areas for improvement
- →Categorize commits by type (fixes, refactoring, etc.) to analyze investment balance
- →Identify individual and collective contributors within the team
- →Compare team performance with industry benchmarks
- →Receive weekly and monthly reports with AI-extracted insights
- →Writing API reference documentation
- →Brainstorming SEO strategies
- →Enhancing code functionality
- →Gaining insights into open-source projects
- →Resolving complex code issues
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- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →Unifying fragmented enterprise data
- →Governing data for AI workloads
- →Moving AI pilots to production
- →Powering analytics with trusted data
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