On-Device
On-Device and Edge Semantic Search
Semantic search that runs where your app runs. Built in Rust and compiled to WebAssembly for browsers, mobile, desktop, and edge. No cloud infrastructure required. Works offline.
<10ms
on-device retrieval
100%
offline capable
0
cloud infrastructure needed
The Bottom Line
Semantic search that runs where your app runs. Built in Rust and compiled to WebAssembly for browsers, mobile, desktop, and edge. No cloud infrastructure required. Works offline.
The Problem
Not every search query should leave the device
Cloud vector databases assume every query travels over the network. But for mobile apps, desktop tools, browser extensions, and edge deployments, that assumption adds latency, cost, and privacy risk. Users on slow connections wait seconds for results. Users on no connection get nothing at all. And every query sent to a cloud service is a data point you no longer control. On-device search solves all three problems at once.
Solution
How Moss Solves This
Runs everywhere via WebAssembly
Moss compiles to WASM and runs in browsers, Electron apps, React Native, mobile WebViews, and edge servers. One runtime for every deployment target.
Offline-first architecture
Once loaded, the index lives in-memory. All queries execute locally with zero network dependency. Data syncs automatically when connectivity returns.
Lightweight runtime
The Moss WASM runtime is compact enough for mobile and edge deployments. No heavy dependencies, no GPU requirements, no infrastructure to manage.
from moss import MossClient, QueryOptions
client = MossClient(PROJECT_ID, PROJECT_KEY)
# Load the index into memory for offline use
await client.load_index("product-catalog")
# Queries run locally in <10ms — no network needed
results = await client.query(
"product-catalog", "waterproof hiking boots",
QueryOptions(top_k=10)
)
# Works offline, syncs when connected
# results.time_taken_ms -> 3FAQ