On-demand webinar

Semantic Search with Jina AI on Elastic Inference Service

Hosted by:

Ugo Sangiorgi

Ugo Sangiorgi

Principal Product Marketing Engineer

Elastic

Ranjana Devaji

Ranjana Devaji

Principal Product Marketing Manager

Elastic

Overview

Join us to discover how to build superior AI-driven search experiences using Elasticsearch vector database and Jina AI models. In an era of agentic AI, the cost of poor relevance compounds across every step of a task-based loop; getting retrieval right is now more critical than ever. This hands-on session focuses on transforming unstructured, siloed data into actionable information by leveraging Elastic as your core data platform for AI.

We will walk through a live demo using Elastic Cloud Serverless to show you how to implement semantic search with ease. You will learn how the Elastic Inference Service abstracts away the complexity of model deployment and maintenance, allowing you to use native Jina AI models for text embeddings and re-ranking.

Highlights

  • Elasticsearch Vector Database: See how Elasticsearch vector database helps you deliver high precision search and scalable AI experiences with embeddings, vector search, hybrid retrieval, filtering and reranking in one platform.
  • Search Methodologies Demystified: Compare the precision of lexical search (BM25) with the intent-based understanding of vector search and the combined power of hybrid search.
  • Elastic Inference Service: Learn how to use this service to point fields to specific models without the burden of manual scaling or maintenance.
  • Get hands-on: Spin up an Elastic Cloud Serverless project and configure Jina AI models for high-precision embeddings and re-ranking.
  • Native Jina AI Integration: See how Jina AI's state-of-the-art, multilingual models provide superior performance for embeddings and re-ranking.
  • Semantic Text Simplified: Discover the semantic_text field type, which automatically generates embeddings for your data, enabling search across different languages and complex natural language queries.

Additional resources

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