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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
No public pricing
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
- ✦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
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- ✦Persistent, structured memory built as a knowledge graph
- ✦Sub-300ms hybrid retrieval (RAG) with reranking
- ✦Native filesystem mount for agent memory access
- ✦Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
- ✦Automatic extraction from PDFs, images, and audio
- ✦User profile and behavior tracking across sessions
- ✦Chat with your documents (RAG)
- ✦Runs locally and offline for privacy
- ✦Supports any LLM (local or cloud)
- ✦Built-in AI agents
- ✦Handles PDFs, Word, CSV, codebases
- ✦No-code setup
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Developers adding long-term memory to AI agents
- →Teams building agents that need to sync with existing tools
- →Individuals wanting one memory layer shared across multiple AI assistants
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app