Connect your data once. Moss indexes, packages, and distributes it so semantic search runs where intelligence happens:
in-browser, on the edge, or in the cloud.
Get real-time retrieval inside apps, browsers, and enterprise agents — with centralized management, analytics, and scale built in.
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Moss is a high-performance runtime for real-time semantic search. It delivers sub-10 ms retrieval, instant index updates, and zero infrastructure overhead. It runs wherever your intelligence lives - in-browser, on-device or in the cloud - so search feels native and effortless.
Works with any AI model - no vendor lock-in.
Answers from device memory in <10 ms - no internet delay.
Fully managed hybrid cloud and on-device retrieval.
Runs offline, cloud powered sync and analytics.
Moss is for developers building conversational, voice, and multimodal AI - experiences where every millisecond shapes how human the interaction feels.
For real-time, offline-capable assistance.
Superfast search without sending data to others.
Tiny engine (<20kB) that fits anywhere.
Keeps code local, great for security audits.
Combine speed with optional analytics and rollouts.
Where teams are putting Moss to work today...
Recall user context instantly, even offline.
Fast, private search inside help centers.
Smart search in note apps or IDEs without sending data online.
Sub-10ms search on phones and AI-PCs — no lag even with bad network.
You bring your data. Moss powers the retrieval layer - indexing, packaging, and distributing it automatically, so semantic search runs close to where intelligence happens. It enables your application to:
Moss brings real-time semantic search to any environment - inside browsers, apps, or your own infrastructure - with sub-10 ms retrieval and no setup overhead.
Each user’s data can be embedded, searched, and updated locally, so experiences feel faster and more personal without sending data to the cloud.
A simple cloud dashboard manages analytics, policies, and updates - giving teams visibility and control without maintaining infrastructure.
Moss continuously improves search quality and syncs enhancements automatically. Built-in A/B testing for embeddings makes it easy to compare and tune indexes for the best retrieval results.
“We’re building the foundation for the next generation of AI-native software - systems that understand context, react in real time, and run wherever intelligence happens.
Our mission is to make intelligence ambient - empowering every interaction, in every environment, to feel instant, personal, and human.”
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Already powering production AI agents and multimodal applications.
<20 kB
Embeddable inside any browser, app, or edge environment - easy to integrate.
<10 ms
Sub-10 ms median retrieval - instant, human-like search experiences.
100%
Fully functional on-device, in hybrid mode, or in the cloud. No dependency on GPUs or network latency.
Users bounce when answers lag or miss the point! Let’s fix that...
We’ll plug in one of your data sources, index it, and show instant, on-topic answers in your conversational AI, voice and multimodal flows. We’ll also run a quick A/B on embedding indexes so you know what works best for your corpus.
Ready to see it on your data?