Moss
Real-time semantic search for AI agents.
Moss is a semantic search layer for conversational AI, voice agents, and copilots. It indexes connected data and runs retrieval in-process — in the browser, on edge, on device, or in the cloud — so queries return without an external vector database or network hop on the critical path. It compiles to WebAssembly, runs queries in memory, and can index and query offline, syncing indexes when connectivity returns.
Moss offers SDKs for Python and TypeScript, with integrations across agent frameworks (LangChain, DSPy), AI SDKs (Vercel AI SDK), voice platforms (LiveKit, Pipecat, VAPI, ElevenLabs), docs platforms (VitePress), web frameworks (Next.js), and an MCP Server for AI coding assistants. It also offers Founding Agent, a voice AI agent for websites that answers questions, qualifies buyers, and books meetings. Use cases include voice AI, AI copilots, in-app search, and on-device AI.
Moss is for teams building real-time AI systems where retrieval latency affects user experience. Pricing is packaged as a free Developer plan with usage costs, plus paid Hobbyist, Start-Up, and Enterprise tiers with increasing storage, ingest, egress, session minutes, and support; Enterprise adds SSO, SOC 2 and HIPAA compliance, and data residency options.
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