Moss
Moss is a high-performance runtime for real-time semantic search designed for conversational and multimodal AI.
Free + paidWeb
Visit websitemoss.dev
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Moss is a high-performance runtime for real-time semantic search designed for conversational and multimodal AI. It delivers sub-10ms retrieval, instant index updates, and zero infrastructure overhead, running natively in-browser, on-device, or in the cloud. Key features include offline capability, device-memory processing for privacy, and compatibility with any AI model without vendor lock-in. It is targeted at developers building copilots, voice agents, and intelligent applications. Specific pricing plans are not publicly listed on the site.
Key features
- Sub-10ms real-time semantic search retrieval
- Offline-first architecture running on-device or in-browser
- Zero infrastructure overhead with centralized management
Pros & cons
Collected from user feedback found in web search
Pros
- High-performance semantic search runtime with sub-10ms lookups
- Instant index updates with zero infrastructure overhead
- Founder with ML lead experience at Grammarly and Microsoft
- Already used in production conversational and voice AI applications
Cons
- Very technical product with limited enterprise sales traction
- Performance improvements may have diminishing ROI
- Limited disclosed funding and customer metrics
Pricing
Use cases
- Building real-time copilots and AI agents
- Private search in documentation and help centers
- On-device search for mobile and desktop apps
Who it is for
Developers building AI products
Integrations
OpenAIAnthropicGoogle GeminiLiveKitPipecatVercelGitHub
Tags
RAGAPI
How we verified this
Company, pricing, and feature details come from the primary sources below and our latest verification pass. When sources disagree, the official source and the most recent check win.
Last verified 09/02/2026Verified sources: 1
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