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Liquid AI’s efficient, multimodal models redefine what’s possible on the road.
Automakers struggle to deploy rich in-vehicle AI assistants because their hardware can't run large models locally, cloud connectivity introduces reliability latency and privacy concerns, and existing voice systems remain too rigid to handle natural, multimodal interactions across the cabin.
One size doesn’t fit all. We work directly with your team to design, build and deploy the solution that’s right for your hardware, use case and data. So you get powerful, fast, efficient AI fit for your business.
AI models tuned for low memory budgets in both CPUs and NPUs, delivering sub-second responses for infotainment, navigation, and safety prompts on existing SoCs.
End-to-end audio models + vision-language models understand intent, emotion, and cabin context and call hundreds of your vehicle functions naturally.
Architectures that combine the best of both edge and cloud AI. Automakers own and determine which AI features run at the edge versus the cloud, and how they run on their vehicles.
