article thumbnail

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

The Lambda function interacts with Amazon Bedrock through its runtime APIs, using either the RetrieveAndGenerate API that connects to a knowledge base, or the Converse API to chat directly with an LLM available on Amazon Bedrock. If you don’t have an existing knowledge base, refer to Create an Amazon Bedrock knowledge base.

APIs 124
article thumbnail

Automate the insurance claim lifecycle using Agents and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

You can now use Agents for Amazon Bedrock and Knowledge Bases for Amazon Bedrock to configure specialized agents that seamlessly run actions based on natural language input and your organization’s data. Knowledge Bases for Amazon Bedrock provides fully managed RAG to supply the agent with access to your data.

APIs 140
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

This post explores the new enterprise-grade features for Knowledge Bases on Amazon Bedrock and how they align with the AWS Well-Architected Framework. AWS Well-Architected design principles RAG-based applications built using Knowledge Bases for Amazon Bedrock can greatly benefit from following the AWS Well-Architected Framework.

APIs 127
article thumbnail

Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and AWS CloudFormation

AWS Machine Learning

An end-to-end RAG solution involves several components, including a knowledge base, a retrieval system, and a generation system. Solution overview The solution provides an automated end-to-end deployment of a RAG workflow using Knowledge Bases for Amazon Bedrock. On the AWS CloudFormation console, create a new stack.

Scripts 126
article thumbnail

6 Killer Applications for Artificial Intelligence in the Customer Engagement Contact Center

If Artificial Intelligence for businesses is a red-hot topic in C-suites, AI for customer engagement and contact center customer service is white hot. This white paper covers specific areas in this domain that offer potential for transformational ROI, and a fast, zero-risk way to innovate with AI.

article thumbnail

Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. If you want more control, Knowledge Bases lets you control the chunking strategy through a set of preconfigured options.

APIs 136
article thumbnail

Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

One of the most critical applications for LLMs today is Retrieval Augmented Generation (RAG), which enables AI models to ground responses in enterprise knowledge bases such as PDFs, internal documents, and structured data. These five webpages act as a knowledge base (source data) to limit the RAG models response.

Benchmark 103