Category: Amazon Bedrock

Learn how AgentFlo built always-on AI sales agents on Amazon Bedrock AgentCore and the Strands Agents SDK. Part 1 covers three pillars of production-grade agents—velocity, standardization, and scalability—including recipe-based deployment, tool routing through AgentCore Gateway, and elastic, stateful commerce conversations.

Clario, part of Thermo Fisher Scientific, uses Amazon Bedrock and Amazon Textract to automatically detect protected health information (PHI) and personally identifiable information (PII) across thousands of DICOM image slices in clinical trials, covering both metadata tags and text burned into the image pixels.

AI agents built on Amazon Bedrock AgentCore help clinical trial teams make fast, accurate enrollment decisions while keeping clinicians in control. This post shows how to architect an eligibility and safety screening agent using AWS HealthLake, AgentCore, and AgentCore Evaluations.

Learn how to track generative AI costs by department using Amazon Bedrock application inference profiles and AWS cost allocation tags. Create tagged profiles for each team and view per-department cost breakdowns in AWS Cost Explorer.

Learn how parameterized query templates reduced Text2SQL latency by 80% and cut token consumption by over 50%. This post covers the architecture behind an intelligent caching layer that uses semantic similarity to match user questions to SQL templates, bypassing expensive LLM calls.

According to Siemens’ 2024 report The True Cost of Downtime, Fortune 500 companies lose an estimated $1.4 trillion annually because of unplanned downtime. This downtime is often worsened by a lack of skills to detect and resolve issues quickly. Generative AI offers a promising path to address this, but deploying these capabilities in industrial environments […]

This post walks you through a two-layer, defense-in-depth authorization pattern for granular, intra-tenant access control in RAG applications. Defense in depth is a security strategy that uses multiple independent layers of protection. Each layer operates independently. If one layer is misconfigured, the other layer still enforces access control. The pattern runs on Amazon Bedrock, a fully managed service that offers a choice of high-performing foundation models (FMs) from Amazon and AI companies through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Avanse Financial Services, India’s leading education loan providers, migrated to a cloud-native lakehouse architecture using Amazon SageMaker Unified Studio, which unified their data engineering, analytics, and artificial intelligence (AI) workflows in a single governed environment on AWS. In this post, we walk through their migration journey so you can adapt their approach to your own environment.

In this post, you learn how to build an automated, serverless pipeline that converts scanned PDF medical records into FHIR R4-compliant data using Amazon Bedrock Data Automation and AWS HealthLake. We walk through the architecture, explain how each AWS service connects to the next, show you what the pipeline looks like when it runs, and get you deployed in under 20 minutes.

In this post, we show you how Doczy.ai™ uses generative AI on AWS to automate contract intelligence at scale, transforming unstructured documents into structured, actionable insights, so organizations can automate critical business processes and unlock the full value of their data.