OpenSearchCon Europe 2025

Search engines take in a query and return a set of results that best satisfy the need of the searcher. Words from a text box, user interface facets, and some user identity information have been the clues for good retrieval. Today, Large Language Models (LLMs) produce vectors with semantic information that augments or replaces lexical information for retrieving best results. OpenSearch's low-level APIs can connect with and use LLMs as part of an overall search solution. A full solution still requires some higher-level coding to take full advantage of these APIs. In this talk, we’ll cover some theory on similarity, and how and where vectors can help you retrieve better results. We’ll dive deep on opensearch-ml-quickstart (https://github.com/Jon-AtAWS/opensearch-ml-quickstart), an open-source example set for managing connections with OpenSearch, local models, and vector embeddings. We’ll walk through examples and code to help you get started quickly with OpenSearch’s vector capabilities: exact nearest-neighbor matching, dense vector embeddings, and sparse vectors. You’ll leave with a great tool in opensearch-ml-quickstart, along with the knowledge of how to apply it.

Unlock the insights hidden within unstructured PDF documents! Many PDFs contain multimodal elements like text, tables, and images, and relying solely on text-based processing risks overlooking critical information. This session explores two powerful approaches to address this challenge: building specialized pipelines that integrate OCR and ML models for handling diverse modalities, and leveraging cutting-edge Vision-Language Models like ColPali to represent multimodal data in a unified format. Join us to discover how both methods can be applied to build an intelligent conversational search application using open-source technology, OpenSearch by leveraging it's powerful search and ingest pipelines. The session includes a live demonstration to showcase practical implementations, empowering you to choose the approach that best fits your needs!

There are lots of statistics we can calculate for search relevance: NDCG, precision, MAP, …. OpenSearch 3.0 calculates and displays them for you.

But metrics don’t tell the whole story. In particular, NDCG can’t give you the qualitative analysis that one algorithm is great for author names, and a different one is good for shapes and sizes. For that, you need eyeballing, that is, human intuition and judgment.

That’s why we’ve built tools to help you dig deeper into your search results. The Search Comparison tool in OpenSearch 2.11 is just the starting point – in 3.0, it lets you define search configurations and test sets of multiple queries and determine which queries’ results have changed the most… and then zoom in to the individual cases. You can integrate data on judgments and query frequency from User Behavior Insights for deeper analysis.

In this talk, we’ll discuss how traditional statistical metrics are complemented by eyeballing, how the new tools in OpenSearch 3.0 support disciplined eyeballing, and how you can use them to improve the quality of your search results.

Efficient data analysis and visualization heavily rely on the performance of aggregations in Opensearch. However, optimizing the performance of aggregations in the multi-phase and distributed nature of search queries poses significant challenges. In this session, we delve into the inner workings of the OpenSearch query engine, uncovering insightful examples and code walkthroughs that empower you to unlock the true potential of aggregation processing.
Discover clever techniques for identifying performance bottlenecks and gain a comprehensive understanding of smart query rewriting techniques like cardinality filtering, range slicing, early collection termination, and multi-range traversal. These advanced techniques offer a remarkable peek into the query engine's inner workings, enabling you to significantly enhance the speed and efficiency of data aggregation in Opensearch.
Prepare to revolutionize your data analysis workflows as you harness the power of these optimization strategies, propelling your aggregation performance to new heights. Experience the unprecedented speed and responsiveness of Opensearch, accelerating your data analysis and visualization tasks by an astounding 100x