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Developer APIs and SDKs to embed real-time voice, video, live streaming, and AI voice agents into web and mobile apps.
Managed ClickHouse platform giving developers hosted ingestion and query APIs to ship real-time analytics products fast.
Lightweight MIT-licensed JavaScript chatbot UI widget for building support-agent chat interfaces on top of any LLM.
Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
Free trial available
No public pricing
No public pricing
Free trial available
- ✦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
- ✦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
- ✦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
- ✦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
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- →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 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
- →Adding an AI chat UI to web apps
- →Building LLM-powered support agents
- →Embedding chat widgets in existing products
- →Prototyping chatbot interfaces
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
