Search
Build innovative AI search experiences
The industry's most-used vector database, plus out-of-the-box semantic search, advanced relevance and data retrieval, and flexible deployment options — including serverless. All on the Elastic Search AI Platform.
Use Cases
Search optimized for GenAI
Search applications
For developers, by developers
Build search applicationsMillions of developers rely on the speed, scale, and relevance of Elasticsearch for building their most important search functionality.
Website search
Your ticket to better site search
Get website searchFast, relevant search improves customer engagement and website performance. Index website content easily. Create a search engine to engage and convert users.
Customer support search
Deliver outstanding support with search
Learn about customer supportResolve customer issues and improve satisfaction with intuitive, self-service knowledge base search that serves up the right answer in record time.
Add speed, scale, and relevance with the power of search
CAPABILITIES
Level up your search AI toolkit
Relevance tuning
Personalized search, unparalleled relevance
Explore relevance tuningBuild search that helps users find exactly what they need. Tune relevance and personalize with RAG optimized for GenAI.
Machine learning and vector search
Take search to the next level with machine learning
Do more with ML and vector searchFlexible capabilities for any development team. Implement next-gen search and NLP apps with textual, vector, hybrid, and semantic search.
Deployment flexibility
Unparalleled performance on an open platform
Go serverlessDiscover boundless scale, decoupled compute and storage — all on Elastic Cloud Serverless.
See Elastic Search in action
Elastic transforms enterprise search for the world’s most innovative companies.
Customer spotlight
Cisco resolves customer issues faster with search AI experiences
Customer spotlight
Labelbox enables its customers to capitalize on the possibilities of AI
Customer spotlight
CogStack unlocks and harnesses valuable healthcare data
Frequently asked questions
Are Elastic Search and Elasticsearch different?
Elastic Search is Elastic’s search solution, built on Elasticsearch. Elastic Search includes advanced capabilities that save development and search management time including machine learning, audit logging, role and attribute based security controls, searchable snapshots, cross-cluster replication, and cross-cluster search as well as flexible deployment options, including serverless.
Do I need separate Elastic products for text, vector, and hybrid search?
No. Elastic’s BM25 textual search algorithm, its scalable vector database, semantic search, and reciprocal rank fusion (RRF) hybrid scoring all come ready to use with Elastic Search. Elastic even has its own semantic search model, the Elastic Learned Sparse Encoder, that can be used out-of-the-box.
Is Elastic a vector database?
Yes. Elastic is the world's most used, scalable vector database that lets developers create, store, and search vector embeddings. But that's not all. Elastic Search solution also contains everything you need to build outstanding search experiences including aggregations, filtering and faceting, auto-complete, multiple retrieval methods, and the flexibility to integrate with your own or third-party transformer models.
Why do I need a search product if I use a large language model in my app?
You need a search product if you use a large language model because it's a cost and time efficient approach for achieving more accurate results in your generative AI experience. By searching over your domain-specific data, you can minimize hallucinations from the large language model by providing highly relevant search results as additional context and limit the time it takes to fine tune the model. Using retrieval augmented generation (RAG), Elastic lets you query proprietary data to get more accurate, real-time results, requiring fewer compute and storage resources. Elastic also controls search access with its document-level security.
Where can I find code examples for implementing search?
If you're a developer, one of the best places to get technical and practical information about implementing Elastic is through blogs, examples, and tutorials featured in Elastic Search Labs. This resource is created and maintained by the technologists who work at Elastic for the technologists who use Elastic. Visit Elastic Search Labs to learn about the latest in generative AI, vector search, and machine learning research.
What is Search AI Lake?
Elastic's Search AI Lake is optimized for real-time, low-latency applications, making it an ideal architecture for your AI-driven future. It revolutionizes data lakes by offering low-latency querying and the powerful search and AI relevance capabilities of Elasticsearch. Search AI Lake powers a new Elastic Cloud serverless deployment — removing all operational overhead so your teams can start innovating.
Discover everything you can do with Elastic
