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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
An AI lab building compact Liquid Foundation Models that run on-device on phones, laptops and cars rather than in the cloud.
Vibe-coding builder creating full-stack apps by chatting with AI.
No public pricing
No public pricing
- ✦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
- ✦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
- ✦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
- ✦Liquid Foundation Models (LFMs) for on-device use
- ✦Variants sized to run on phones, laptops and cars
- ✦Broad runtime support (llama.cpp, MLX, ONNX, CoreML, vLLM)
- ✦On-device reasoning, vision and retrieval models
- ✦Enterprise and embedded deployment partnerships
- ✦CodeFlying enables full-stack app creation via chat in minutes
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →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
- →Run private AI locally on consumer hardware
- →Embed intelligence in cars and edge devices
- →Deploy tool-calling agents without the cloud
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