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.

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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

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

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.

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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.

  • Retail

    Upgrade your product search from lexical (keyword) to semantic search. Customize shopping experiences based on user behavior and preferences. Express intent multimodally — not just using text, but also using other modalities.

  • Financial services

    Improve modeling of risk and detection of fraud, personalize banking experiences, and provide more relevant and faster customer support.

  • Customer Service

    Boost productivity and improve customer service with targeted search. Search multimedia libraries for educational content that meets your needs.

  • IoT

    Continuously monitor sensors, equipment logs, and historical maintenance records in real time to identify patterns and anomalies that may indicate potential inventory issues or equipment failures.

  • Pharma

    Analyze genetic and chemical sequences to accelerate drug discovery. Suggest therapeutic approaches matching patient records and past cases. Deobfuscate novel aspects in patent research using aggregations.

  • Media and entertainment

    Retrieve videos and images, identify similar user-generated content, and provide recommendations for gaming.

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