article thumbnail

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

AWS Machine Learning - AI

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.

article thumbnail

Build a contextual chatbot application using Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

One way to enable more contextual conversations is by linking the chatbot to internal knowledge bases and information systems. Integrating proprietary enterprise data from internal knowledge bases enables chatbots to contextualize their responses to each user’s individual needs and interests.

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

Deploy foundation models with Amazon SageMaker, iterate and monitor with TruEra

AWS Machine Learning - AI

By identifying the nature of these failure modes, our users are able to adapt their indexing (such as embedding model and chunking) and retrieval strategies (such as sentence windowing and automerging) to mitigate these issues. Groundedness After the context is retrieved, it is then formed into an answer by an LLM. on(Select.Record.calls[0].args.args[0]).on_output()

article thumbnail

Welcome to a New Era of Building in the Cloud with Generative AI on AWS

AWS Machine Learning - AI

delivers key capabilities for enterprises such as an industry-leading 200K token context window (2x the context of Claude 2.0), reduced rates of hallucination, and significant improvements in accuracy, even at very long context lengths. CRM or ERP applications), and write a few AWS Lambda functions to execute the APIs (e.g.,