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GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.
VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Talent marketplace linking AI labs with 257,000+ vetted data labelers and trainers for RLHF, red-teaming and evaluation.
No public pricing
No public pricing
- ✦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
- ✦in-editor chat with OpenAI assistants
- ✦workspace source-code context sharing
- ✦support for custom, user-defined assistants
- ✦secure management of the user's OpenAI account
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦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
- ✦Network of 257,000+ pre-vetted AI data experts
- ✦AI-matched shortlists with skills tests and interviews
- ✦Bring talent into any annotation platform, no lock-in
- ✦Self-service or fully managed engagements
- ✦Job feed aggregating 20+ platforms for freelancers
- →Automating developer performance reviews
- →Spotting delivery bottlenecks
- →Generating retrospective insights
- →Motivating teams via gamification
- →getting coding help without switching out of VS Code
- →using a personalized OpenAI assistant tuned to a project
- →quick in-editor Q&A while writing code
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Sourcing experts for RLHF and model evaluation
- →Staffing red-teaming and data-labeling projects
- →Scaling annotation teams into existing tools
- →Finding AI training gigs as a freelancer