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Lightweight MIT-licensed JavaScript chatbot UI widget for building support-agent chat interfaces on top of any LLM.
Atlassian's Git repository hosting for teams with built-in CI/CD pipelines and tight Jira integration for code review and deployment.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
No public pricing
No public pricing
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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
- ✦Git repository hosting
- ✦Bitbucket Pipelines CI/CD
- ✦Pull requests and code review
- ✦Native Jira integration
- ✦Branch permissions and access controls
- ✦IP allowlisting and security features
- ✦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
- ✦Single OpenAI-compatible API for 500+ models
- ✦Chat, image, video and audio models
- ✦Discounted per-request pricing
- ✦One dashboard for keys, quotas and usage
- ✦Multi-region routing and failover (99.9% uptime)
- ✦Multiple payment methods incl. crypto
- →Adding an AI chat UI to web apps
- →Building LLM-powered support agents
- →Embedding chat widgets in existing products
- →Prototyping chatbot interfaces
- →Source code management
- →CI/CD automation
- →Team code review
- →DevOps for Jira-based teams
- →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
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys