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CodeGPT
✓ verifiedFreemium
IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
👁 262K/mo
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Runcell - Jupyter AI Agent
✓ verifiedFreemium
Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
👁 170K/mo♥ 5.5K
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devActivity
✓ verifiedFreemium
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
👁 52K/mo
Pricing
No public pricing
Historical Data Pack: $49.9
Base Plan: $14.9/month
Advanced Plan: $24.9/month
Enterprise Plan: $34.9/month
Free: $0/mo (BYOK, 30 free interactions)
AutoComplete Add-on / BYOK Pro: $8/mo per seat ($6.67 annual)
No public pricing
Free: $0/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)
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)
- ✦Commits and Pull Requests Dashboard
- ✦Advanced Developer Skills Analysis
- ✦Strategic Investment Balance Monitoring
- ✦Collaborative Developers Map
- ✦Benchmarking Comparison with Other Teams
- ✦Smart Notifications
- ✦BYOK access to 15+ model providers
- ✦Agentic planning-then-build mode
- ✦AI autocomplete
- ✦MCP connections to external systems
- ✦Custom rules and live context tracking
- ✦Local models via Ollama/LM Studio
- ✦VS Code and JetBrains plugins
- ✦Cross-session project memory recalling prior decisions and state
- ✦Autonomous execution of long, multi-step notebook tasks
- ✦Reads cell outputs (plots, tables, metrics), not just code
- ✦In-notebook cell-level assistance and error fixing
- ✦Installs directly into existing JupyterLab via pip, no new editor
- ✦Concept explanations with runnable example cells
- ✦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
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →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
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign
- →Data scientists running multi-week model iteration projects
- →Domain experts (e.g. risk/fintech) who know the problem but not deep Python
- →Researchers wanting an agent that remembers project context across days
- →Analysts needing help understanding unfamiliar algorithms or libraries
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
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