Vector search powers the next generation of search experiences
Vector search provides the foundation for implementing semantic search for text or similarity search for images, videos, or audio. Retrieve relevant context of your data by relying on machine learning to encode your data, and apply generative AI to create more human-like experiences.
AI Playground
Prototype away
Experiment with cutting-edge AI search features using your own data. Test and swap models easily. Discover how to build RAG systems on the platform of your choice, using LLMs from OpenAI, Amazon Bedrock, and Anthropic.
Multimodal search
Perform similarity search
Find visually similar images, video clips, and audio that match specific styles or samples. Similarity search enables applications such as reverse image search, image recommendation, and video and audio matching.
Personalization
Personalize search
Model user behaviors and profiles, and find items similar to the ones a user has shown interest in. This lets you personalize recommendations for consumer products, movies, music, and more, and dynamically adapt any user experience to individual or cohort of users.
Natural language processing
Use NLP effortlessly
Modern natural language processing (NLP) lets you enrich search experiences. Use vector search to retrieve a configurable subset of relevant documents. In a second step, identify the paragraph answering a specific question using a question-answer transformer, extract named entities (NER), or determine emotional content by applying sentiment analysis.
GENERATIVE AI
Transform search experiences
Leverage large language models (LLMs) on business-specific information from your organization's private data (not just publicly trained data). Use Elasticsearch for high relevance context windows that draw on your proprietary data to improve LLM output and deliver the information in a secure, concise, actionable and conversational experience.
Industry Applications
How vector search is used across industries
Deliver innovative user experiences, automate processes, accelerate root cause analysis, and gain insight leveraging learned vector representations and LLM.
Customer Spotlights
Our customers reap the benefits
Elastic's vector search lets you responsibly implement the next generation of ML/AI-powered search experiences, at scale, and at enterprise-grade. See how our customers have used vector search to achieve their business outcomes!
Semantic search on educational content
"With vector search in Elasticsearch, we can better understand the user's intent and return courses that are tailored to their industry, organization, and role."
Jon Ducrou, Senior Vice President of Engineering, Go1
Fast search of multimedia assets
"It's extremely valuable that Elastic processes data on ingestion so that it is automatically ready for our AI systems. There are also vector and embedding features that we can use as building blocks for our machine learning operations."
Director of Engineering, Fortune 500 Multimedia and Creativity Software Company
Legal e-discovery search
"I'm thrilled about the benefits we can bring to customers through our investments to harness Elasticsearch within RelativityOne. We're excited about the potential to deliver powerful, AI-augmented search results to our customers."
Chris Brown, Chief Product Officer, Relativity
Streamline customer service
"Feedback from our engineers is extremely positive. They now use Topic Search to solve 90% of service requests. They can deliver a better customer experience by easily finding on-target information and fixing issues much faster than before."
Sujith Joseph, Principal Enterprise Search & Cloud Architect, Cisco Systems
