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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.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Long-standing provider of human-labeled, expert-validated training data and model evaluation services for building frontier AI.
Vibe-coding builder creating full-stack apps by chatting with AI.
No public pricing
Free trial available
No public pricing
No public pricing
- ✦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
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Frontier alignment data (RLHF, SFT, red teaming)
- ✦Speech and audio data
- ✦Multimodal / VLM annotation
- ✦Physical AI data (LiDAR, robotics, sensor fusion)
- ✦Model integrity, bias and hallucination audits
- ✦1M+ vetted contributors, 500+ locales
- ✦SOC2 and ISO 27001 certified
- ✦CodeFlying enables full-stack app creation via chat in minutes
- →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
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Source training data for AI models
- →Evaluate and benchmark models
- →Annotate multimodal and sensor data
- →Run safety and bias audits
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