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devActivity
✓ verifiedFreemium
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
👁 52K/mo
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Gitmore
✓ verifiedFreemium
Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.
👁 7.6K/mo
Pricing
No public pricing
DEVELOPER: FREE
STARTER: $119 / month
GROWTH: $599 / month
ENTERPRISE: Starting at $1,800 / month
Historical Data Pack: $49.9
Base Plan: $14.9/month
Advanced Plan: $24.9/month
Enterprise Plan: $34.9/month
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
- ✦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)
- ✦Developer-first platform for AI-powered integrations
- ✦Secure, isolated sandboxes for running JavaScript/Python code
- ✦Automatic management of npm/PyPI dependencies
- ✦Built-in platform plumbing: secrets, webhooks, scheduling, logs, and audit
- ✦Yep Agent (prompt → runnable processes)
- ✦MCP Server/Tools (convert code into AI agent tools)
- ✦Serverless runtime (YepCode Run) and SDK access
- ✦Commits and Pull Requests Dashboard
- ✦Advanced Developer Skills Analysis
- ✦Strategic Investment Balance Monitoring
- ✦Collaborative Developers Map
- ✦Benchmarking Comparison with Other Teams
- ✦Smart Notifications
- ✦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
- ✦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
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Building complex API integrations that require custom code and logic beyond what no-code tools offer.
- →Safely running AI-generated scripts in isolated environments with secrets management.
- →Automating workflows that require large datasets, loops, branching, or custom dependencies.
- →Connecting AI agents to external databases, APIs, and services using MCP tools.
- →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
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →Keep stakeholders updated on what shipped
- →Replace manual status updates and standups
- →Give teams visibility into Git activity
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