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Lightweight MIT-licensed JavaScript chatbot UI widget for building support-agent chat interfaces on top of any LLM.
Managed ClickHouse platform giving developers hosted ingestion and query APIs to ship real-time analytics products fast.
Side-by-side arena to compare AI coding models and build multi-file apps, with a public leaderboard and battle mode.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
AI co-pilot for technical diagrams and design docs, with diagram-as-code and integrations for engineering teams.
No public pricing
No public pricing
- ✦MIT-licensed and free to use
- ✦Lightweight (~65kb) JavaScript widget
- ✦4 message display modes plus typewriter effect
- ✦Markdown support and chat history
- ✦Backend hook to integrate any LLM
- ✦Responsive, mobile-friendly, read-only mode
- ✦Managed, hosted ClickHouse database
- ✦Sub-second SQL query APIs
- ✦Kafka and other data connectors
- ✦Safe, zero-downtime schema migrations
- ✦Git-based branching with zero-copy prod data
- ✦SOC 2 Type II enterprise security
- ✦Head-to-head model comparison
- ✦Battle mode matchups
- ✦Public model leaderboard
- ✦Multi-file app generation
- ✦File uploads as input
- ✦Modern terminal rebuilt for agentic coding workflows
- ✦Warp Agent with multi-agent orchestration and model routing
- ✦Oz platform for launching agents into the cloud via SDK, CLI, or terminal
- ✦Codebase indexing and granular permission controls
- ✦Team-wide usage visibility and spend/credit caps
- ✦Open-source terminal core
- ✦AI-generated diagrams from prompts
- ✦Diagram-as-code editing
- ✦Markdown design docs
- ✦Eraserbot auto-updating codebase diagrams
- ✦Integrations: GitHub, Notion, Confluence, VS Code
- ✦Export to PNG/SVG/PDF/MD and MCP server
- →Adding an AI chat UI to web apps
- →Building LLM-powered support agents
- →Embedding chat widgets in existing products
- →Prototyping chatbot interfaces
- →Building real-time analytics dashboards
- →Powering in-app usage or event analytics
- →Streaming Kafka topics into query-ready tables
- →Letting AI coding agents build and deploy analytics
- →Choosing the best coding model
- →Benchmarking AI code quality
- →Prototyping small apps
- →Developers who want an AI-assisted terminal for daily coding
- →Teams orchestrating multiple coding agents (Claude Code, Codex) together
- →Engineering orgs needing governance over agent-driven development
- →Companies moving agent workflows from local machines to the cloud
- →Create architecture and cloud diagrams fast
- →Write and maintain design docs
- →Keep codebase diagrams up to date
- →Embed live diagrams in Notion/Confluence
