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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Marketplace that matches vetted human experts with AI labs to produce training data and model evaluations.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦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)
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦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
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦Curated roles across many expert domains
- ✦Expert vetting and matching to AI projects
- ✦Hourly-paid contract work for specialists
- ✦APEX benchmarks and off-the-shelf datasets
- ✦Enterprise data partnerships and evaluations
- ✦Daily payouts to contributors
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Source expert human data for AI training
- →Run domain-expert model evaluations
- →Find paid remote work as a domain specialist
- →Build custom datasets for AI labs