Case Study: Global Automaker Company achieves real-time in-car AI with Liquid AI

Global Automaker Company - Customer Case Study

A global automaker company wanted to deploy real-time voice and vision AI in its vehicles but was blocked by performance bottlenecks. Off-the-shelf vision-language models ran too slowly on its mid-tier in-car CPUs, creating an unacceptable user experience and hardware limitations that prevented deployment without costly upgrades.

Liquid AI addressed this by delivering a hardware-optimized vision-language model through its Edge SDK. The solution resulted in a model that was 50% smaller with no loss in accuracy and ran 10x faster on the automaker's existing hardware. Liquid AI enabled real-time AI interactions and slashed the deployment timeline from months to just one week.