Moss

Moss is an AI Search Engines tool that delivers sub-10ms semantic search for conversational AI, voice agents, and copilots. It indexes and distributes data wherever an agent runs: in-browser, on-device, or in the cloud.

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At a glance

Pricing

Freemium · Paid · Enterprise · Usage-based

Free tier

Yes

API

Yes

Skill level

Technical

About

What is Moss?

Moss is a real-time semantic search runtime specifically designed for AI agents, voice agents, and copilots, offering sub-10ms lookups with zero infrastructure. Built in Rust and WebAssembly, Moss runs search locally within your agent's runtime, ensuring fast, private, and local context retrieval. It supports various environments including browsers, edge devices, on-device applications, and cloud deployments. Moss offers official SDKs for JavaScript/TypeScript and Python, enabling index creation, document management, and both semantic and hybrid search. Its local-first architecture allows for offline functionality, with data syncing automatically when connectivity is restored, and prioritizes privacy by keeping data on-device by default.

Best used for

Ideal for developers building conversational AI, voice agents, or copilots who need sub-10ms context retrieval and zero infrastructure. Especially valuable for creating offline-first, privacy-focused AI applications that run in-browser, on-device, or at the edge, ensuring rapid and local data access.

Common actions

implement semantic search

build AI agents

integrate real-time retrieval

develop offline AI

manage AI data

Capabilities

Key features

Sub-10ms semantic search
Zero infrastructure
Browser, edge, on-device
Rust and WebAssembly
JavaScript and Python SDKs
Hybrid search
Privacy by architecture

Target Audience

developerstartup founderproduct manager

Integrations

Not yet documented

Pricing & Plans

Freemium · Paid · Enterprise · Usage-based · Starting at USD 30.00

$30 / mo + usage costs

FAQs

How does Moss achieve sub-10ms search speeds?

Moss achieves sub-10ms lookups by running search locally within your agent's runtime, eliminating network round-trips common with traditional vector databases. This local execution, powered by Rust and WebAssembly, ensures retrieval is fast, private, and has no infrastructure to manage.

Can Moss be used offline or on-device?

Yes, Moss is built with a local-first architecture, allowing all queries to run entirely in-memory on the device once an index is loaded, requiring no network. It supports browsers via WebAssembly, mobile devices, desktop apps, and edge servers, with automatic data syncing when connectivity is restored.

What programming languages are supported by Moss?

Moss provides official SDKs for JavaScript/TypeScript (npm install @inferedge/moss) and Python (pip install inferedge-moss). Both SDKs offer comprehensive functionality, including index creation, document management, semantic search, hybrid search, and auto-refresh capabilities.

What types of search does Moss support?

Moss supports three search modes: pure semantic search (vector similarity), pure keyword search (BM25), and hybrid search that combines both. The 'alpha' parameter allows users to tune the blend between semantic and keyword search for optimal retrieval quality.

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Also listed in

This tool also appears in

AI Agents & Automation › Chatbots & Conversational AI AI Agents & Automation › RAG & Document AI AI Agents & Automation › Voice Agents

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