11-12, August 2026 Seoul, South Korea View More Details & Registration Note: The schedule is subject to change.
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Agentic search lets you ask in Natural Language and have OpenSearch plan and execute retrieval. The Query Planner re-writes Natural Language to OpenSearch DSL using SOTA LLMs. This works amazingly well but not without important limitations:
1/ The biggest factor is added latency for remote inference. eCommerce Search demands sub-100ms response times. Even the best results when slow lead to search abandonment. 2/ We'll demo overcoming latency by hosting SLMs locally within OpenSearch nodes using vLLM/Ollama. This is faster & cheaper, but SLMs suffer quality decline in query re-writes. We'll explore fine-tuning with domain-specific data—proving fine-tuned SLMs beat SOTA LLMs. 3/ Relevance remains generic even with Agentic Search. We'll show how to improve it using user and business contexts with hybrid search and reranking.
This hands-on talk covers: 1/ Search Latency with Remote Inference 2/ Locally hosting SLMs using vLLM/Ollama 3/ Agentic search with SLM Local Inference 4/ Improving relevance with user and business contexts 5/ Fine-tuning SLMs for domain-specific query re-writing via Axolotl/LLaMA-Factory
Principal OpenSearch Specialist SA, Amazon Web Services
Cédric Pelvet is a Principal Specialist Solutions Architect at AWS, focusing on AI and near-realtime distributed systems for data like OpenSearch, Kafka and Flink.
Aswath Srinivasan is a Senior Search Engine Architect at Amazon Web Services currently based in Munich, Germany. With over 18 years of experience in various search technologies, Aswath currently focuses on OpenSearch. He is a search and open-source enthusiast and helps customers and... Read More →
