Category: HAQM OpenSearch Service

Today, we are happy to announce the availability of Binary Embeddings for HAQM Titan Text Embeddings V2 in HAQM Bedrock Knowledge Bases and HAQM OpenSearch Serverless. This post summarizes the benefits of this new binary vector support and gives you information on how you can get started.

This post explores a solution that uses the power of AWS generative AI capabilities like HAQM Bedrock and OpenSearch vector search to perform damage appraisals for insurers, repair shops, and fleet managers.

In this post, you will learn how to extract key objects from image queries using HAQM Rekognition and build a reverse image search engine using HAQM Titan Multimodal Embeddings from HAQM Bedrock in combination with HAQM OpenSearch Serverless Service.

In this post, we will explore building a reusable RAG data pipeline on LangChain—an open source framework for building applications based on LLMs—and integrating it with AWS Glue and HAQM OpenSearch Serverless. The end solution is a reference architecture for scalable RAG indexing and deployment.

Agentic workflows are a fresh new perspective in building dynamic and complex business use- case based workflows with the help of large language models (LLM) as their reasoning engine or brain. In this post, we set up an agent using HAQM Bedrock Agents to act as a software application builder assistant.

In this post, we show how to create a multimodal chat assistant on HAQM Web Services (AWS) using HAQM Bedrock models, where users can submit images and questions, and text responses will be sourced from a closed set of proprietary documents.

In this post, we dive deep into the vector database options available as part of HAQM Bedrock Knowledge Bases and the applicable use cases, and look at working code examples.

This post explores how Accenture used the customization capabilities of Knowledge Bases for HAQM Bedrock to incorporate their data processing workflow and custom logic to create a custom chunking mechanism that enhances the performance of Retrieval Augmented Generation (RAG) and unlock the potential of your PDF data.

This post provides an overview of a custom solution developed by the AWS Generative AI Innovation Center (GenAIIC) for Deltek, a globally recognized standard for project-based businesses in both government contracting and professional services. Deltek serves over 30,000 clients with industry-specific software and information solutions. In this collaboration, the AWS GenAIIC team created a RAG-based solution for Deltek to enable Q&A on single and multiple government solicitation documents. The solution uses AWS services including HAQM Textract, HAQM OpenSearch Service, and HAQM Bedrock.

Information retrieval systems have powered the information age through their ability to crawl and sift through massive amounts of data and quickly return accurate and relevant results. These systems, such as search engines and databases, typically work by indexing on keywords and fields contained in data files. However, much of our data in the digital […]