Category: Amazon Bedrock Knowledge Bases

Learn how with Amazon Bedrock Knowledge Bases, you build an assistant that grounds answers in your trusted documents through Retrieval Augmented Generation (RAG).

This post introduces the Governed Intelligence Framework (GI Framework), giving you a defensible path from AI spending to quantifiable value without compromising governance rigor. Built on Amazon Bedrock by Amazon Web Services (AWS) as the implementation solution, the framework rests on a single argument: ROI, governance, and token optimization form a reinforcing system. None of them deliver results in isolation.

In this post, we explore a human-in-the-loop (HITL) framework in the form of architectural patterns teams can use to introduce agentic AI incrementally into eligibility workflows that are adapted to their programs, policies, and risk tolerances.

In this post, we walk through three extended capabilities of Amazon S3: Amazon S3 Metadata, Amazon S3 Vectors, and Amazon S3 Tables and explore how each maps to real challenges government agencies face today.

This blog share how if your agency is managing millions of unstructured documents, from eligibility records to case files, this post introduces how DMI Document AI, built on Amazon Bedrock, can help you automate document processing, reduce backlogs, and redirect your team toward higher-value mission work.

In this blog post, we demonstrate how public sector organizations can overcome the challenges that emerge when integrating Amazon Redshift and other AWS relational databases with Amazon Bedrock. You’ll learn how to utilize enterprise data to generate AI-powered analytical insights by using natural language queries through Amazon Bedrock Agents and Amazon Bedrock Knowledge Bases. This custom solution enables seamless connectivity between your structured data sources and generative AI applications, eliminating the need for data duplication and significantly reducing development effort.

In this post, we discuss how to use datasets in the Registry of Open Data on AWS with Amazon Bedrock Knowledge Bases. With Amazon Bedrock Knowledge Bases, you can give foundation models (FMs) and agents contextual information from private and public data sources to deliver more relevant, accurate, and customized responses.

Through a strategic collaboration with AWS and DailiTech Co., King Mongkut’s Institute of Technology Ladkrabang (KMITL) developed and delivered a prospective students virtual assistant “Knowva,” a generative AI application powered by Amazon Bedrock. Read this post to learn more about this

In this blog post, we explore the AI for Teaching & Learning Framework on AWS, and discuss how it is addressing the evolving needs of higher education in the digital age.

Personalized therapy for diseases such as cancer utilizes an individual’s unique genomic profile to guide treatment decisions. However, the effect and clinical significance of most genetic variants are uncertain. Accurate classification of the clinical significance of novel genetic variants requires extensive curation of peer-reviewed biomedical literature. In recent years, generative AI has demonstrated promising results in information extraction and text summarization. In this post, we explore how various AWS-native solutions can be used to create a secure, retrieval-augmented, and cost-effective biomedical chatbot designed to facilitate biocuration.