Use Cases
Built for real-time AI applications
From voice agents to AI copilots, Moss gives your product <10ms semantic retrieval without managing vector infrastructure.
Built by teams shipping production AI products
Voice AI
Keep conversations flowing with
instant context retrieval
When voice agents pause, users notice. Moss retrieves context in milliseconds so conversations stay natural.
Examples
- AI phone agents
- Customer support bots
- Scheduling assistants
AI Copilots
Give your AI product memory that
feels instant
Power copilots that retrieve relevant user context, documentation, and history without lag.
Examples
- Coding assistants
- Internal copilots
- Research assistants
In-App Search
Replace keyword search with
semantic understanding
Help users find what they mean — not just what they typed.
Examples
- Documentation search
- Knowledge bases
- SaaS product search
Edge / On-Device
Run retrieval where your app runs
Deploy Moss locally for privacy-sensitive, offline, or latency-critical experiences.
Examples
- Browser apps
- Desktop apps
- Mobile experiences
- Offline AI
Why Teams Choose Moss
<10ms
Query latency
Zero Infra
No vector infra to manage
Runs Anywhere
Cloud, browser, edge, device
Production Ready
Built for real workloads
Traditional semantic search slows real-time AI down
| Capability | Traditional Vector DBs | Moss |
|---|---|---|
| Query latency | 50–300ms+ | <10ms |
| Infrastructure management | Required | None |
| Cloud dependency | Yes | Optional |
| Voice AI readiness | Weak | Strong |
| Browser deployment | No | Yes |
| On-device support | Rare | Yes |
Ready to ship faster AI products?
Moss gives you production-ready semantic retrieval without infrastructure complexity.