Data Management
Scaling AI Document Processing on Kubernetes with Ray & KubeRay
Scaling document AI pipelines for large PDFs requires more than bigger GPUs. By chunking documents and processing them in parallel across GPU workers using Ray and KubeRay on Kubernetes, teams can reduce processing time, avoid GPU memory bottlenecks, and use GPU infrastructure more efficiently. In production testing, this approach reduced end-to-end processing time for a 463-page document from 38 minutes to about 10 minutes (~3.8Ă— faster) while keeping overall GPU usage and cost comparable.
March 6, 2026
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