AWS ML Blog

Building Intelligent Search with Amazon Bedrock and Amazon OpenSearch for hybrid RAG solutions

1 min read
#rag#agenticworkflows#bedrock#compute
Level:Intermediate
For:ML Engineers, Data Scientists, AI Product Managers
TL;DR

This article demonstrates the implementation of a generative AI agentic assistant that leverages both semantic and text-based search capabilities using Amazon Bedrock and Amazon OpenSearch, enabling hybrid Retrieval-Augmentation-Generation (RAG) solutions. By integrating these technologies, developers can build more intelligent search systems that combine the strengths of different search paradigms.

⚡ Key Takeaways

  • Amazon Bedrock and Amazon Bedrock AgentCore can be used to build generative AI agentic assistants with advanced search capabilities.
  • The integration of Strands Agents with Amazon Bedrock enables the creation of more sophisticated search systems.
  • Amazon OpenSearch provides a powerful text-based search engine that can be combined with semantic search capabilities for hybrid RAG solutions.

Want the full story? Read the original article.

Read on AWS ML Blog

Share this summary

𝕏 Twitterin LinkedIn

More like this

Build AI-powered employee onboarding agents with Amazon Quick

AWS ML Blog#deployment

Accelerate agentic tool calling with serverless model customization in Amazon SageMaker AI

AWS ML Blog#agentic workflows

From isolated alerts to contextual intelligence: Agentic maritime anomaly analysis with generative AI

AWS ML Blog#agentic workflows

National Robotics Week — Latest Physical AI Research, Breakthroughs and Resources

NVIDIA Blog#rag