🎤 Use Cases

Voice Intelligence

End-to-end conversational AI: multi-intent understanding, robust function calling, hyper-personalization, and persona voices — running on CPU with no cloud dependency.

1 model

E2E audio: speech in, speech out

100+

Functions via natural language

On CPU

Runs on existing edge hardware

A single end-to-end audio model replaces cloud voice stacks and rule-based NLU. LFM2.5-Audio-1.5B handles the entire pipeline natively: speech recognition, multi-intent understanding, robust function calling, and natural spoken responses with custom persona voices. Runs 100% offline on existing hardware. Zero marginal cost per device, no data leaves the edge.

1 specialist model

How It Works

One end-to-end audio model,
running the full voice pipeline on-device

Multi-Intent Conversation Replaces Rule-Based NLU

Rule-based NLU forces users 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 follow-up commands work without restating the full request. Real-time end-to-end audio — no separate STT, LLM, and TTS pipeline.

🎤

AUDIOCLOUD

AI Audio Assistant

Production-ready conversational AI for vehicles: multi-intent, function calling, and persona voices — running on CPU

Multi-intentRobust function callingMulti-turn context

GenAI multi-intent engine replaces rule-based NLU with natural conversation. 100% offline, real-time, runs on existing vehicle hardware.

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Robust Function Calling With Phonetic Matching

Keyword spotters understand 'set temperature to 72' but not 'it's freezing in here.' LFM maps natural language to function calls across 100+ device controls. Phonetic matching handles place names, addresses, and mispronunciations that break rule-based systems. The function schema is the only constraint — add new capabilities by extending the schema, not retraining the model.

Personalization and Custom Brand Voices

The model learns individual user preferences and adapts over time. Custom persona voices create distinctive brand identity — not a generic assistant. Multilingual support covers major global languages. All personalization data stays on-device: no cloud sync, no privacy trade-offs.

100% Offline — Zero Marginal Cost at Scale

Cloud voice AI breaks when connectivity drops and adds per-query cost that scales with adoption. On-device LFMs provide consistent interaction regardless of network state. All audio processing stays on the edge hardware. No data transmitted, GDPR/PIPL/CCPA compliant by design. Zero marginal cost per device — no cloud API calls, no subscription model needed.

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