Artificial Intelligence

Automating customer retention workflows in Amazon Quick

Automating customer retention workflows in Amazon Quick

Learn how to build a no-code customer retention pipeline in Amazon Quick that detects at-risk customers from call transcripts and CSAT data, scores them by retention priority with a custom MCP Action, and generates personalized retention letters, reducing response time from days to minutes.

How AgentCore Gateway supports the MCP 2026-07-28 spec

How AgentCore Gateway supports the MCP 2026-07-28 spec

The Model Context Protocol (MCP) published its 2026-07-28 specification, the largest revision since launch: MCP is now stateless, with a governed extensions system and hardened authorization. Learn what changed and how to enable the new version on Amazon Bedrock AgentCore Gateway with a single UpdateGateway call.

Market surveillance agent with LangGraph and Strands on AgentCore

Market surveillance agent with LangGraph and Strands on AgentCore

Learn how to architect and deploy a production-ready multi-agent AI system using LangGraph for workflow orchestration and Strands for agent reasoning on Amazon Bedrock AgentCore. This post walks through a market surveillance example with state-driven orchestration, checkpoint-based recovery, and AgentCore memory and observability.

Beyond RAG: Task-aware knowledge compression for enterprise AI on AWS

Beyond RAG: Task-aware knowledge compression for enterprise AI on AWS

Traditional RAG hits a ceiling on analytical tasks that span hundreds of documents. This post shows how to use task-aware knowledge compression (TAKC) on AWS to pre-compress entire knowledge bases into task-specific representations, cache them at multiple fidelity tiers, and route each query to the right tier, with an open-source implementation you can deploy.

Deepgram enhances Amazon SageMaker AI support with AWS IAM Temporary Delegation

In this post, we cover why Deepgram built on IAM temporary delegation, how the integration works end-to-end, and what it unlocks for customers running Deepgram speech models on SageMaker AI. With this integration, Deepgram has reduced the time for initial investigation on a SageMaker AI support ticket from days to minutes.

Build an explainable next-best-product recommendation system for banking on AWS

Build an explainable next-best-product recommendation system for banking on AWS

Learn the architecture and design decisions behind an explainable next-best-product recommendation system for banking, built with Amazon SageMaker AI and PyTorch. A multi-tower neural network with learned attention delivers accurate, per-customer recommendations while providing the explainability that banking regulators require.

Get started with OpenAI GPT-5.6 Sol, Terra, and Luna on Amazon Bedrock

Get started with OpenAI GPT-5.6 Sol, Terra, and Luna on Amazon Bedrock

OpenAI GPT-5.6 Sol, Terra, and Luna are now generally available on Amazon Bedrock. Learn how to select a model, run inference through the Responses API on the bedrock-mantle endpoint, reduce cost with prompt caching, connect the OpenAI Codex coding agent, and plan for quotas and scaling.

Best practices for applying Amazon Bedrock Guardrails to code generation workflows

Best practices for applying Amazon Bedrock Guardrails to code generation workflows

In this post, we explain how Amazon Bedrock Guardrails can be configured for code generation workflows with coding assistants to overcome these constraints. With these best practices, you can build an efficient blueprint helping you with effective capacity planning with robust safety coverage.