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Lightweight MIT-licensed JavaScript chatbot UI widget for building support-agent chat interfaces on top of any LLM.
Trae AI-powered IDE for developer collaboration; notable ByteDance-backed dev product.
AI coding platform routing many agents and models through one encrypted, usage-based endpoint with CLI, IDE and multi-agent execution.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
AI app builder turning English prompts into full-stack apps with provisioned DB, auth and hosting; also hosts autonomous agents.
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
- ✦AI Agents
- ✦Tool Integration
- ✦Context Awareness
- ✦Smart Autocompletion
- ✦Local Data Storage
- ✦Secure Data Access
- ✦Unified encrypted inference endpoint
- ✦Multi-agent parallel execution
- ✦CLI, IDE, and API access
- ✦App builder and remote coding agents
- ✦Chairman LLM output evaluation
- ✦35+ IDE integrations
- ✦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
- ✦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
- →Adding an AI chat UI to web apps
- →Building LLM-powered support agents
- →Embedding chat widgets in existing products
- →Prototyping chatbot interfaces
- →Automating coding tasks with AI agents
- →Integrating external tools for enhanced functionality
- →Improving code accuracy with context-aware suggestions
- →Boosting coding speed with smart autocompletion
- →Building RAG apps without writing code
- →Automating refactors, tests, and migrations
- →Running competing AI coding agents
- →Building apps from prompts
- →Integrating agents into CI/CD
- →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
- →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
