Building remarkable multimodal search applications with Pinecone and AWS

Multimodal search with a vector database like Pinecone enhances information retrieval by integrating diverse data types—text, images, audio, and video—into a shared embedding space, enabling richer and more contextual analysis.

• Deep Dive into Multi-Modal Search Understand the value of using a purpose-built vector database like Pinecone for multi-modal search applications.
• Multi-Modal Use Cases Explore applications including text-to-image search, image-to-image search, and text-to-audio search.
• Reference Architecture and Notebook Get a detailed guide on building a multi-modal search application using Pinecone serverless and AWS services such as Amazon Bedrock, Amazon Textract, Amazon Sagemaker, and more.

Learn how to add multimodal search capabilities with Pinecone serverless and AWS to get the freshest and most relevant results. Download the whitepaper now.