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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
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Free trial available
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦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
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦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
- ✦Automatic context-gathering from connected engineering sources
- ✦AI-generated code, tests and pull requests from tickets
- ✦Task planning that breaks complex work into subtasks
- ✦Auto-updating engineering documentation
- ✦Vector search over embedded project data
- ✦Multiple selectable AI models (GPT, Gemini, Claude, Llama, etc.)
- ✦Engineering productivity analytics dashboard
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from 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
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Engineering teams automating ticket-to-PR workflows
- →Developers wanting AI-assisted debugging and test generation
- →Engineering managers tracking AI-driven productivity gains
- →Teams centralizing documentation from scattered sources