NEXT-GEN AI SEARCH FOR
InferEdge Moss is an edge-native search engine that answers in <10 ms on-device, then syncs to the cloud for fleet-wide learning - so every interaction feels instant, private, and infinitely scalable.
A Minimal On-Device Semantic Search with Cloud Control Plane.
Bring your own embedding model from HuggingFace or custom source – we handle the vector DB, similarity search, distribution, and fleet learning.
$WHY MOSS ?
Moss is a lightweight, client-first semantic-search runtime—vector storage, on-device real-time embeddings, and SIMD-accelerated similarity—backed by a cloud control plane for index and model delivery.
MODEL-AGNOSTIC
Works with any AI model - no vendor lock-in.
ZERO-HOP LATENCY
Answers from device memory in <10 ms - no internet delay.
ZERO INFRA OVERHEAD
Fully managed hybrid cloud and on-device retrieval.
OFFLINE-FIRST, CLOUD-SMART
Runs offline, cloud powered sync and analytics.
WHO IS IT FOR?
Moss is for those building AI tools that should be fast and private.
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.
COMMON USE CASES
Where teams are putting Moss to work today...
Copilot Memory
Recall user context instantly, even offline.
Docs Search
Fast, private search inside help centers.
Desktop Productivity
Smart search in note apps or IDEs without sending data online.
AI-Native Apps
Sub-10ms search on phones and AI-PCs — no lag even with bad network.
HOW WE DELIVER?
We provide the full retrieval layer as the managed service. You bring your preferred embedding model, and MOSS powers the rest. It enables your application to:
Edge-Native Core:
Hybrid semantic search runs seamlessly with no infra to manage.
Instant Personal Index:
Embeds and retrieves user data locally in sub-10 ms, private by default.
Cloud Control Plane:
Manages indexing, policy, sync, and analytics without dev overhead.
Fleet Intelligence Loops:
Cloud improves relevance and distributes updates across all devices.
OUR MISSION
“We're building a unified, edge-native AI infrastructure for the next generation of AI-native applications — powered by a SIMD-accelerated vector engine, model-agnostic embedding pipelines, on-device RAG, and a managed cloud control plane for analytics, policy and rollouts.
To unleash a new era of ambient, adaptive software — where intelligence runs alongside every user, everywhere.”
PROVEN EDGE-NATIVE PERFORMANCE
5 →
PRODUCTION ROLLOUTS
Already running in real-world environments.
<20 kB
Runtime SIZE
Lightweight & easy to integrate.
<10 ms
MEDIAN QUERY LATENCY
Ultra-fast local search.
100%
OFFLINE CAPABILITY
Runs fully on-device.