Artificial Intelligence

Category: Artificial Intelligence

How Benchling secured multi-tenant AI agents with Amazon Bedrock AgentCore

How Benchling secured multi-tenant AI agents with Amazon Bedrock AgentCore

Learn how Benchling built a defense-in-depth security architecture to run untrusted, AI agent-generated scientific code across thousands of life sciences tenants using Amazon Bedrock AgentCore Code Interpreter in VPC mode, combined with Amazon Route 53 Resolver DNS Firewall and VPC endpoint policies to block data exfiltration, including through DNS.

Reducing medical claims review time with AI on AWS: The EXL Medical IDP solution

Reducing medical claims review time with AI on AWS: The EXL Medical IDP solution

EXL built an AI-powered Medical intelligent document processing (IDP) solution on AWS, combining IDP with domain-specific large language models on Amazon SageMaker and Amazon Bedrock to extract, summarize, and query medical records at enterprise scale and cut claims review time from over 100 minutes per case.

Amazon SageMaker Inference: 2026 year-to-date launches in review

Amazon SageMaker Inference: 2026 year-to-date launches in review

Amazon SageMaker AI shipped 13 inference launches in year-to-date across two deployment paths: fully managed endpoints and Amazon SageMaker HyperPod Inference. This post reviews each launch, from inference recommendations and capacity-aware instance pools to tiered KV caching and disaggregated prefill and decode.

Migrating multi-model AI agents to Amazon Bedrock AgentCore runtime

Migrating multi-model AI agents to Amazon Bedrock AgentCore runtime

Migrate a multi-model healthcare AI agent from self-managed Amazon ECS with AWS Fargate to Amazon Bedrock AgentCore runtime, preserving triple-model orchestration and vector-enhanced knowledge retrieval while reducing infrastructure management. The framework-agnostic pattern applies across healthcare, financial services, and manufacturing.

The new AgentCore runtime: Elastic, optimized, and consistently fast starts

The new AgentCore runtime: Elastic, optimized, and consistently fast starts

Today we are announcing the new AgentCore runtime, a capability of Amazon Bedrock AgentCore built for the speed, flexibility, and cost efficiency that production agents demand. It reclaims memory as sessions release it and delivers consistent cold starts regardless of image size or concurrency.

Deploy Hugging Face models on Amazon SageMaker AI with coding agents

Deploy Hugging Face models on Amazon SageMaker AI with coding agents

Deploy production-ready Hugging Face models on Amazon SageMaker AI using six open-source agent skills. Point a coding agent at a model and get back a real-time endpoint with the right serving container, autoscaling, Amazon CloudWatch alarms, and a verified teardown path.

Selecting a vector store for Amazon Bedrock Knowledge Bases

Selecting a vector store for Amazon Bedrock Knowledge Bases

Choosing the right vector store for your Amazon Bedrock Knowledge Bases RAG application affects performance and cost. This post compares Amazon OpenSearch Service, Amazon Aurora PostgreSQL with pgvector, and Amazon S3 Vectors across three RAG use cases, with benchmarks and a practical selection framework.

A shared agentic platform for Wood Mackenzie, on Amazon Bedrock AgentCore

A shared agentic platform for Wood Mackenzie, on Amazon Bedrock AgentCore

Wood Mackenzie built APEX, a shared agentic AI platform on Amazon Bedrock AgentCore so every team can ship production agents without rebuilding runtime, identity, observability, and guardrails from scratch. Learn why they chose AgentCore, how APEX Studio operates it, and where multi-agent systems go next.