Artificial Intelligence

Category: Amazon Bedrock

Secure AI agents with Amazon Bedrock AgentCore Identity on Amazon ECS

AI agents in production require secure access to external services. Amazon Bedrock AgentCore Identity, available as a standalone service, secures how your AI agents access external services whether they run on compute platforms like Amazon ECS, Amazon EKS, AWS Lambda, or on-premises. This post implements Authorization Code Grant (3-legged OAuth) on Amazon ECS with secure session binding and scoped tokens.

Intelligence-driven message defense and insights using Amazon Bedrock

In this post, you will learn how you can use Amazon Nova Foundation Models in Amazon Bedrock to apply generative AI techniques for both business protection and enhancement. You can identify obvious and disguised attempts at direct contact while gaining valuable insights into customer sentiment and service improvement opportunities.

Introducing agent quality optimization in AgentCore, now in preview

Generate recommendations from production traces, validate them with batch evaluation and A/B testing, and ship with confidence. AI agents that perform well at launch don’t stay that way. As models evolve, user behavior shifts, and prompts get reused in new contexts they were never designed for. Agent quality quietly degrades. In most teams, the improvement […]

Process flow diagram showing LLM migration workflow from source models (OpenAI, Mistral, Llama, Claude) to Amazon Bedrock target models, including evaluation, comparison, and deployment phases.

AWS Generative AI Model Agility Solution: A comprehensive guide to migrating LLMs for generative AI production

In this post, we introduce a systematic framework for LLM migration or upgrade in generative AI production, encompassing essential tools, methodologies, and best practices. The framework facilitates transitions between different LLMs by providing robust protocols for prompt conversion and optimization.

Sun Finance automates ID extraction and fraud detection with generative AI on AWS

In this post, we show how Sun Finance used Amazon Bedrock, Amazon Textract, and Amazon Rekognition to build an AI-powered identity verification (IDV) pipeline. The solution improved extraction accuracy from 79.7% to 90.8%, cut per-document costs by 91%, and reduced processing time from up to 20 hours to under 5 seconds. You’ll learn how combining specialized OCR with large language model (LLM) structuring outperformed using either tool alone. You’ll also learn how to architect a serverless fraud detection system using vector similarity search.

Configuring Amazon Bedrock AgentCore Gateway for secure access to private resources

In this post, you will configure Amazon Bedrock AgentCore Gateway to access private endpoints using Resource Gateway, a managed construct that provisions Elastic Network Interfaces (ENIs) directly inside your Amazon VPC, one per subnet. You will explore two implementation modes (managed and self-managed) and walk through three practical scenarios: connecting to a private Amazon API Gateway endpoint, integrating with a MCP server on Amazon Elastic Kubernetes Service (Amazon EKS), and accessing a private REST API.

Extracting contract insights with PwC's AI-driven annotation on AWS

Extracting contract insights with PwC’s AI-driven annotation on AWS

This post was co-written with Yash Munsadwala, Adam Hood, Justin Guse, and Hector Hernandez from PwC. Contract analysis often consumes significant time for legal, compliance, and procurement teams, especially when important insights are buried in lengthy, unstructured agreements. As contract volumes grow, finding specific clauses and assessing extracted terms can become increasingly difficult to scale. […]

Organizing Agents’ memory at scale: Namespace design patterns in AgentCore Memory

In this post, you will learn how to design namespace hierarchies, choose the right retrieval patterns, and implement AWS Identity and Access Management (IAM)-based access control for AgentCore Memory.