
Part 2: Scaling Translation Inference: +82% Throughput
How we improved vLLM inference throughput by 82% using AsyncLLMEngine and right-sized continuous batching
Insights, tips, and updates from VoicePing
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How we improved vLLM inference throughput by 82% using AsyncLLMEngine and right-sized continuous batching
Identifying architectural bottlenecks in FastAPI + multiprocessing setup preventing efficient GPU utilization


Startup Island TAIWAN works to revitalize Taiwan's startup ecosystem and support market entry into Japan. VoicePing provided real-time translation services at their matching events.

As international construction projects continue to increase, communication within multinational teams has become increasingly important. In this case study, we interviewed Michael and Kim from the Management Division at Tekken Construction Co., Ltd., who have implemented VoicePing for multilingual meetings in their international projects.

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