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Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
Undetectable desktop AI assistant that feeds real-time answers during coding and technical interviews.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
High-performance open-source vector database for production AI retrieval and RAG, for teams needing scale, hybrid search, or self-hosting.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦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
- ✦AI coding IDE with agent orchestration
- ✦Run and manage multiple agent sessions
- ✦Task, artifact and collaboration tools
- ✦Bring-your-own AI subscription or API keys
- ✦Cloud-scale agent execution
- ✦Real-time AI answers during technical interviews
- ✦Invisible to screen sharing and recording
- ✦Hidden from dock, tray and activity monitor
- ✦Click-through overlay
- ✦Live audio capture and transcription
- ✦Lifetime unlimited access license
- ✦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
- ✦Hybrid dense and sparse vector search (BM25, SPLADE, miniCOIL)
- ✦Advanced metadata filtering applied during search traversal
- ✦Multivector support for multimodal retrieval
- ✦Reranking with score boosting and late-interaction models (ColBERT, MMR)
- ✦Flexible deployment: cloud, hybrid, private, or edge
- ✦Rust-based engine optimized for low-latency, high-scale search
- →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
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →Getting live help on coding interview problems
- →Answering technical questions in real time
- →Avoiding detection during screen-shared interviews
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Building retrieval-augmented generation (RAG) pipelines
- →Powering AI recommendation and semantic search systems
- →Enterprises needing on-prem or hybrid deployment for compliance
- →AI agent platforms needing fast contextual retrieval at scale