Case Study: a global automotive manufacturer validates multilingual audio AI deployment with LILT

Global Automotive Manufacturer benchmarks multilingual ASR with Lilt under 100 concurrent requests

The global automotive manufacturer faced the challenge of deploying multilingual speech recognition (ASR) and voice activity detection (VAD) capabilities for in-vehicle voice features. They needed to determine which cloud infrastructure could meet real-time latency targets under high load and what the actual inference costs would be before committing to a production launch. They engaged Lilt as an engineering partner to answer these critical infrastructure questions.

Lilt implemented a rigorous benchmarking program, stress-testing the audio models across Azure and AWS environments, including GPUs and specialized accelerators, under a load of 100 simultaneous requests. The solution provided the customer with validated deployment configurations and clear, quantified data on speed, capacity, and cost differences. This gave the global automaker a data-backed deployment plan and reproducible assets, enabling them to confidently select a platform for their scaled rollout.

Global Automotive Manufacturer