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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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Devv.AI
✓ verifiedPaid
AI search engine for developers with code repo integration.
52K visits/mo4.2K saves
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Openclaw AI
✓ verifiedPaid
Managed cloud hosting and one-click deploy for the open-source OpenClaw personal AI assistant, on credit-based plans.
86K visits/mo
Pricing
No public pricing
Free: $0/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)
Historical Data Pack: $49.9
Base Plan: $14.9/month
Advanced Plan: $24.9/month
Enterprise Plan: $34.9/month
No public pricing
Starter: $19.99/mo (40,000 credits)
Professional: $39.99/mo (80,000 credits)
Ultimate: $199.99/mo (400,000 credits)
Core features
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦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
- ✦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
- ✦One-click managed cloud deployment
- ✦Self-hosting option on Mac mini, Windows or Linux
- ✦100+ app and messaging integrations
- ✦Choice of Claude, GPT, Gemini or local models
- ✦Credit-based monthly subscription plans
- ✦Modular skills/plugins
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →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
- →Run a hosted personal AI assistant without server upkeep
- →Connect an AI agent to messaging apps
- →Automate email, calendar and workflows
- →Self-host for full data control
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