Search

Elastic's built-in search analytics and visualization builder, Kibana, lets you access all of your search data in shareable dashboards that help your team monitor performance, pinpoint issues, track patterns, identify trends, and optimize the search experience.

Use the latest advancements in machine learning and generative AI with a powerful set of search tools such as a vector database, semantic search, text classification, data annotation, PyTorch, and Hugging Face to train models for your datasets. Have existing NLP transformer models? Integrate them directly into Elasticsearch to get started quickly.

Use native connectors for databases and connector clients for popular SaaS applications, a web crawler, JSON file uploads, or our extensible APIs to ingest all your other data, regardless of its structure or location. Plus, use out-of-the-box features with data that's already stored in Elasticsearch.

Use the Elasticsearch Relevance Engine to apply industry leading advanced relevance ranking features and build AI search apps. Optimize contextual relevance and personalization in real time with precision tuning, weights, boosts, and automated search result promotions powered by machine learning.

With more than 50 regions (and counting) on AWS, Microsoft Azure, or Google Cloud, your data can be right where you need it. Choose to run on-prem, multi-cloud, or in a hybrid cloud environment that suits your needs, all without compromising on functionality or performance.

Quickly build custom or embedded search experiences using prebuilt, open code components. Put a ready-to-use search bar, auto-suggest, filters, faceting, and natural language search to work to give users the modern ease of use they've come to expect.