AI that runs
on the device.
Speech recognition, text-to-speech, and LLM inference — entirely on-device. No cloud calls. No latency. No data leaves the phone. Deploy to millions of Android and iOS devices with OTA model updates and real-time telemetry.
Complete privacy
Data never leaves the device. No cloud processing. GDPR/HIPAA friendly.
Zero latency
7× faster than real-time inference. No network round-trips. Instant responses.
Zero cloud cost
No per-token API bills. No usage metering. Models run free on-device.
Open source · Apache 2.0 · Production ready
Why DeviceAI
Enterprise-grade AI.
Zero cloud dependency.
Everything your team needs to ship on-device AI at scale — from a single SDK integration to fleet-wide model management.
Privacy by design
Audio, text, and prompts never leave the device. No cloud processing, no data collection, no compliance risk. GDPR/HIPAA friendly by default.
Measured on real mid-range hardware
On a 3.6 GB Redmi Note 9 Pro: Piper TTS synthesizes 3× faster than real time, Whisper transcribes 2 s of speech in 1.9 s, and SmolLM2 360M chats at ~14 tokens/s — all on the CPU, no network round-trip.
Works fully offline
No internet required after initial model download. Perfect for field workers, healthcare, aviation, or anywhere connectivity is unreliable.
Hardware-aware
SDK reports RAM, CPU, and SoC; the control plane assigns the right model per device tier — a flagship gets Llama 3.2 3B, a 4 GB phone gets SmolLM2 360M. Available memory, not total, decides what fits.
OTA model updates
Push new models to devices without app store updates. Canary rollouts, percentage-based targeting, and instant kill-switch if something goes wrong.
Production telemetry
Track inference latency, TTFT, tokens/sec, and model load times across your entire fleet. Network-aware batching. Custom analytics sink support.
How It Works
From zero to on-device AI
in five minutes
Add the SDK
One line in your build.gradle. Works with any Android app — Kotlin, Java, Compose, or XML.
Initialize
Two lines of code. The SDK auto-detects device hardware — RAM, CPU, SoC model, NPU availability. No manual configuration.
Run inference
Call the SDK. Speech recognition, text-to-speech, or LLM chat — all running locally on the device. Zero cloud calls.
Monitor performance
Inference latency, time-to-first-token, tokens/sec, and model load times stream to your dashboard. No prompts or audio collected — ever.
Push model updates
Deploy new models to specific device tiers without an app update. Canary to 5%, observe telemetry, roll out to 100% — or instant rollback.
Ready to ship AI that respects your users' privacy?
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