Vector search

Search AI 101: Lesson 3 of 4 - This hands-on learning will guide you through integrating your custom model to create vector embeddings, configuring Elasticsearch for vector search, and running similarity queries to retrieve contextually relevant results.

  • Import your model

    Upload your custom model to Elasticsearch

  • Prepare for data ingest

    Configure an Elasticsearch index with fields to store data

  • Generate embeddings

    Convert textual data into vector representations

  • Search using semantic query

    Perform queries and get contextually accurate results

Try Elastic Search free for 14 days to go deeper and test these capabilities.

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