Moss

Retrieval, vector search and RAG · by Moss

Real-time semantic search runtime for AI agents with sub-10ms lookups, zero infrastructure.

What it does

Real-time semantic search runtime for AI agents with sub-10ms lookups, zero infrastructure. Runs in-browser, on-device, at edge, or in cloud. Built in Rust and WebAssembly.

  • Sub-10ms semantic search for conversational AI
  • Voice AI agent context retrieval
  • AI copilot grounding
  • Internal and customer-facing document search
  • On-device and edge offline-first search
Category
Retrieval, vector search and RAG
Users
Software developers building production AI systems, Teams building voice AI, copilots, and real-time applications
Public API
Not offered

Not yet disclosed: deployment options, platforms, languages and support channels.

Product insights

Evidence for this product in each industry and task.

#3 · access data and knowledgeView ranking →

Documented feature

“docsPythonTypeScriptfrom moss import MossClient client = MossClient(PROJECT_ID, PROJECT_KEY) docs = [{ "text": "How do I track my order?" }] await client.add_docs("my-index", docs)IntegrationsBuilt for modern AI stacksView…”

Read product documentation
  • docsPythonTypeScriptfrom moss import MossClient client = MossClient(PROJECT_ID, PROJECT_KEY) docs = [{ "text": "How do I track my order?" }] await client.add_docs("my-index", docs)IntegrationsBuilt for modern AI stacksView…
    Read source · www.moss.dev ↗

Pricing

  • Free plan$0
  • Subscription$5/month
    • Free credits on Developer plan
  • EnterpriseCustom
    • Quoted by their sales team

Prices as published by Moss, checked Nov 2026.

Security and compliance

No security details published yet

Moss hasn't published certifications or security practices for Moss that we could find. Ask their team for audit reports.

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