ArticleHomepage Featured8 min readSep 27, 2026

From Prototype to Production: The 2026 MLOps & RAG Playbook

By David Chen, Principal MLOps Engineer
From Prototype to Production: The 2026 MLOps & RAG Playbook

“A deep dive into reducing vector retrieval latency while maintaining strict accuracy across high-volume production retrieval pipelines.”

Building a proof-of-concept RAG application takes an afternoon. Taking it to 10,000 queries per second with sub-50ms latency and 99.8% precision requires a disciplined engineering discipline.

In this technical playbook, BritAI engineers outline real-world benchmarks comparing hybrid dense-sparse search, contextual re-ranking, and model quantization.

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