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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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Open Source Database Designs
✓ verifiedFreemium
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
👁 27K/mo
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Labelbox
✓ verifiedFreemium
Data-labeling and RL data platform supplying training data, environments and evaluation for frontier AI labs and enterprises.
👁 1.1M/mo
Pricing
No public pricing
Free: $0/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)
No public pricing
No public pricing
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
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦Data labeling across modalities
- ✦RL environments and reward signals
- ✦Custom model evaluations and benchmarks
- ✦Human preference/annotation from an expert network
- ✦Recursion RL platform for enterprise agents
- ✦Robotics data (video, trajectories)
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
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Building training and evaluation datasets
- →Post-training and RLHF for models
- →Benchmarking model capability
- →Training enterprise specialist agents
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