Automotive Voice Intelligence
Private, real-time, agentic AI running natively on existing vehicle hardware. Multi-intent conversation, robust function calling, hyper-personalization, and persona voices — on CPU.
A single end-to-end audio model replaces rule-based NLU and cloud voice stacks. LFM2.5-Audio-1.5B handles the entire pipeline: speech recognition, multi-intent understanding, robust function calling across 100+ vehicle controls, and natural spoken responses with custom persona voices. 100% offline, zero marginal cost per vehicle, no data leaves the cabin. Deploys on existing vehicle hardware without costly upgrades.
1 specialist model
How It Works
One end-to-end audio model,
running the full voice pipeline on existing vehicle hardware
Multi-Intent Conversation Replaces Rule-Based NLU
Rule-based NLU forces drivers into rigid, single-command interactions. LFM2.5-Audio handles compound requests naturally: 'Turn on heated seats and navigate home' resolves both intents in a single pass. Multi-turn context means 'actually, make it warmer' works without restating the full command. The GenAI engine understands natural conversation, not just keyword patterns.
Robust Function Calling Across 100+ Vehicle Controls
Keyword spotters understand 'set temperature to 72' but not 'it's freezing in here.' LFM maps natural language to function calls across HVAC, media, navigation, windows, seats, and lighting. Phonetic matching handles place names, addresses, and mispronunciations that break rule-based systems. The function schema is the only constraint — add new controls by extending the schema, not retraining the model.
Hyper-Personalization and Custom Brand Voices
The assistant learns individual driver preferences for climate, music, and routing. Persona voices let OEMs create a distinctive brand identity — not a generic assistant voice. The model adapts to each driver over time while running entirely on-device. No driver data transmitted to the cloud, no privacy trade-offs, no per-query costs at fleet scale.
100% Offline — Works in Tunnels, Garages, and Rural Roads
Cloud voice AI breaks when connectivity drops: tunnels, underground parking, rural areas. Subscription-based cloud inference adds per-user cost that makes AI hard to monetize post-sale. LFM runs the full voice pipeline on existing vehicle SoCs with zero cloud dependency. Consistent experience everywhere, zero marginal cost, GDPR/PIPL/CCPA compliant by design — cabin data never leaves the vehicle.
Try each model
All Demos
Ready to deploy in your environment?