Artificial Intelligence

Category: Advanced (300)

Sweep thousands of leases for compliance using Amazon Quick and the Adjudicated Query pattern

Sweep thousands of leases for compliance using Amazon Quick and the Adjudicated Query pattern

The Adjudicated Query pattern pairs the Amazon Quick chat agent with a bounded MCP server over a deterministic rules engine to deliver provably complete, defensible compliance answers. This post walks through the reference architecture and a deployable AWS CDK sample, using lease compliance as the running example.

Fine-tune a search agent with multi-turn RL on Amazon SageMaker AI

Fine-tune a search agent with multi-turn RL on Amazon SageMaker AI

Fine-tuning teaches a small search agent your tools and environment, giving it the reliability of a frontier model at lower latency and cost. In this post, we fine-tune an LLM-powered search agent with multi-turn reinforcement learning (MTRL) on Amazon SageMaker AI and share the gains we measured in retrieval quality and reliability.

Scaling cloud migrations with agentic AI on Amazon Bedrock AgentCore

Scaling cloud migrations with agentic AI on Amazon Bedrock AgentCore

Learn how AWS Professional Services uses a multi-agent framework built on Amazon Bedrock AgentCore to automate enterprise cloud migrations end to end. Purpose-built AI agents handle discovery, infrastructure as code generation, portfolio governance, and post-migration operations, reducing IaC development time from weeks to minutes.

Build agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors

Build agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors

Learn how to use Amazon S3 Vectors as the persistent memory layer within the NVIDIA NeMo Agent Toolkit (NAT), deployed on Amazon Elastic Kubernetes Service (Amazon EKS). This post shows how NAT’s memory subsystem works and how to implement Amazon S3 Vectors as a custom memory provider, using a multi-agent investment research use case.

Query claims in natural language with Amazon Bedrock Knowledge Bases

Query claims in natural language with Amazon Bedrock Knowledge Bases

This technical how-to builds a conversational claims assistant on Amazon Bedrock Knowledge Bases that answers natural-language questions with citations. It covers ingesting claim documents from Amazon S3, querying with the AgenticRetrieveStream API, multi-turn follow-ups, metadata filters, and contextual grounding guardrails.

Build a multi-agent music production pipeline on Amazon Bedrock AgentCore Runtime Instances

Build a multi-agent music production pipeline on Amazon Bedrock AgentCore Runtime Instances

Amazon Bedrock AgentCore Runtime Instances gives multi-agent workflows AWS managed EC2 infrastructure with GPUs, persistent volumes, and multi-day sessions. In this post, we deploy a three-agent music production pipeline where the agents colocate on one GPU instance, share a filesystem, and hand work to each other to produce a finished track.

Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore

Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore

Manually extracting data from hundreds of vendor contracts doesn’t scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a contract intelligence platform on AWS that uses AI agents to extract and verify contract fields, then answers aggregate and single-contract questions through Amazon Quick analytics.

How Condé Nast built multimodal video discovery with Amazon Bedrock

How Condé Nast built multimodal video discovery with Amazon Bedrock

Condé Nast’s editorial teams spent an average of 250 minutes per task searching a library of more than 140,000 videos using only titles and descriptions. Working with the AWS Generative AI Innovation Center, they built a multimodal video discovery solution on Amazon Bedrock and Amazon OpenSearch Service that cut discovery time to under 2 minutes.