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@usemoss

Moss

Real-time Semantic Search for Conversational AI

👋 Welcome to Moss

We build real-time semantic search infrastructure for conversational and agentic AI.


Why Moss

AI interfaces are changing. Voice agents, copilots, and multimodal apps all share the same hard requirement:

retrieval must happen at the speed of thought.

But today’s search stacks are:

  • too slow for real-time interaction
  • overly cloud-dependent
  • painful to integrate and scale

Moss exists to fix that.


What We’re Building

Moss is a real-time search runtime designed for AI-native applications:

  • Sub-10ms semantic + hybrid retrieval
  • 🌍 Runs anywhere — browser, edge, on-device, or cloud
  • 🧠 Built for agents — memory, personalization, context
  • 🧩 Simple APIs that feel like using a database
  • 🚀 Developer-first: easy to start, hard to outgrow

Think of Moss as the search layer modern AI apps should have had from day one.


What It’s Used For

Teams use Moss to power:

  • Voice AI agents that can’t afford latency
  • Conversational copilots with long-term memory
  • Multimodal systems blending text, voice, and context
  • Real-time personalization for AI-driven products

If retrieval is on your critical path, Moss is built for you.


Where We’re Going

We’re building the foundation for real-time AI-native applications — infrastructure that matches how users actually interact with AI.

We’re early, but already working closely with teams pushing this space forward.


If you’re building fast, interactive AI systems — welcome.

Popular repositories Loading

  1. moss-samples moss-samples Public

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  2. pipecat pipecat Public

    Forked from pipecat-ai/pipecat

    Open Source framework for voice and multimodal conversational AI

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  3. .github .github Public

  4. moss-gemini-pipecat-demo moss-gemini-pipecat-demo Public

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  5. moss-image-search-demo moss-image-search-demo Public

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  6. agents agents Public

    Forked from livekit/agents

    A powerful framework for building realtime voice AI agents 🤖🎙️📹

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