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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.
Enterprise AI agent platform for building, deploying, and governing no-code agents across company knowledge and workflows.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
AI app builder turning English prompts into full-stack apps with provisioned DB, auth and hosting; also hosts autonomous agents.
No public pricing
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- ✦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
- ✦No-code visual agent builder
- ✦Company knowledge search across docs and wikis
- ✦Scheduled and recurring agent automations
- ✦Model-agnostic access to major AI models
- ✦Browser extension integration with 30,000+ apps
- ✦Data analysis of spreadsheets and reports
- ✦Enterprise SSO/SCIM/SAML and dedicated deployment
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Natural-language full-stack app generation
- ✦Auto-provisioned Postgres, auth, storage and hosting
- ✦Full code ownership with GitHub export
- ✦Managed hosting for autonomous AI agents
- ✦200+ bundled AI models
- ✦MCP and CLI tooling
- →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
- →Automating recurring reports and workflow tasks
- →Searching internal company knowledge with AI agents
- →Deploying AI copilots for sales, support, or legal teams
- →Running enterprise AI with strict data governance requirements
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Ship a SaaS without an engineering team
- →Build internal tools from a description
- →Deploy always-on AI agents quickly
- →Provide infra for AI-coded apps
