GenAI hallucinations plague production apps, but OpenSearch's vector search and hybrid retrieval turn unreliable LLMs into precision engines. This talk unveils battle-tested RAG pipelines that slash errors by 80%+, drawing from semantic search and real-time analytics use cases.

Discover hands-on strategies:
- Ingesting embeddings at scale with neural ranking and k-NN plugins for sub-second queries.
- Hybrid BM25 + vector fusion to ground responses in enterprise knowledge bases and logs.
- Live demos: RAG over petabyte traces, chunking optimizations, and eval frameworks benchmarking recall.

Packed with code snippets, failure autopsies, and deployment blueprints for Kubernetes. Ideal for ML engineers and architects building trustworthy GenAI, escape the hallucination trap and deploy survival-ready search today!