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Lightweight MIT-licensed JavaScript chatbot UI widget for building support-agent chat interfaces on top of any LLM.
Developer APIs and SDKs to embed real-time voice, video, live streaming, and AI voice agents into web and mobile apps.
Open-source data-movement platform now adding a context/action layer for AI agents; 600+ connectors and flexible pricing.
Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
Human-friendly API testing client for terminal, desktop and web, known for readable syntax; the CLI is open source.
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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
- ✦Audio and video calling APIs and SDKs
- ✦Interactive live streaming APIs and SDKs
- ✦AI voice agent integration
- ✦Web and mobile platform support
- ✦Pay-as-you-go pricing with one-time $20 free credit
- ✦600+ data connectors
- ✦ELT replication and CDC
- ✦Open-source and managed cloud options
- ✦Airbyte Agents context store (MCP/SDK/CLI)
- ✦Capacity- and volume-based pricing
- ✦Governance: SSO, RBAC, encryption
- ✦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
- ✦Human-friendly command-line HTTP client
- ✦Web and desktop GUI apps
- ✦Simple, readable request syntax
- ✦Request export/import and history
- ✦Path parameters and 'copy as command'
- ✦Open-source terminal version
- →Adding an AI chat UI to web apps
- →Building LLM-powered support agents
- →Embedding chat widgets in existing products
- →Prototyping chatbot interfaces
- →Embedding video and audio calling into web and mobile apps
- →Adding interactive live streaming to a platform
- →Building AI voice agent experiences into products
- →Building data pipelines to warehouses
- →Syncing SaaS data for analytics
- →Giving AI agents live business context
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys
- →Testing REST APIs
- →Sending and inspecting HTTP requests
- →Debugging web services
- →Sharing API requests across a team