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- This Guidance demonstrates how to securely run Model Context Protocol (MCP) servers on the AWS Cloud using containerized architecture. It helps organizations implement industry-standard OAuth 2.0 authentication while protecting server deployments with multiple security layers, including content delivery networks and web application firewalls.
- This Guidance demonstrates a scalable, serverless approach for automated document processing and information extraction using AWS services, such as Amazon Bedrock Data Automation and Amazon Bedrock foundational models. It combines generative AI and optical character recognition (OCR) to process documents at scale.
- The Game Analytics Pipeline solution helps game developers to apply a flexible, and scalable DataOps methodology to their games. Allowing them to continuously integrate, and continuously deploy a scalable serverless data pipeline for ingesting, storing, and analyzing telemetry data generated from games, and services.
- AWS HealthLake patient matching with AWS Entity Resolution.This Guidance shows how to use AWS Entity Resolution to perform patient entity resolution on healthcare data stored in AWS HealthLake.
- Stable Diffusion is a popular Open Source project for generating images using Gen AI. Building a scalable and cost efficient inference solution is a common challenge. This project shows how to use AWS serverless and container services to build an end-to-end scalable, secure and price effecient asynchronous image generation architecture.
- This Guidance demonstrates how to effectively orchestrate multiple specialized AI agents to solve complex customer support challenges through different coordination mechanisms on AWS. Modern customer service environments demand sophisticated handling of multi-step interactions, personalized responses, and seamless access to various data sources.
- Enables developers to build, deploy, and manage multiple specialized agents that work together to tackle complex workflows. Each agent focuses on a specific task, breaks down processes into manageable steps, assigns tasks to the appropriate agents, and ensures accurate, and reliable outcomes.
- This guidance provides code and instructions to create a multi Kubernetes cluster environment to host a match making and game server solution, integrating Open Match, Agones and Amazon Elastic Kubernetes Service (Amazon EKS), for a session-based multiplayer game.
- This Guidance shows how to automatically monitor and receive alerts on service quota usage across single or multiple AWS accounts. Effectively managing your AWS service quotas is crucial for maintaining operational continuity and preventing unexpected disruptions to your business-critical applications.
- This project demonstrates how to build a cost-effective Retrieval-Augmented Generation (RAG) solution using Amazon DynamoDB as a vector store for small use cases, enabling small businesses to implement AI personalization without the high costs typically associated with specialized vector databases.
- This demo provides an automated loan application that streamlines document submission, verification, underwriting and approval processes.
- A secure, browser-based chat application that connects to Amazon Bedrock Agents using AWS Amplify for hosting and Amazon Cognito for authentication, enabling organizations to quickly deploy AI-powered chat interfaces with enterprise-grade security.
- Enterprise-grade, production-hardened, serverless data lake on AWS
- This Guidance demonstrates how to deploy Cloud Intelligence Dashboards in your AWS environment using AWS CloudFormation templates or command line tools. These pre-built dashboards enable you to drive financial accountability, optimize costs, and track usage goals across their AWS infrastructure.
- This Guidance shows how to automate non-conformance review (NCR) disposition recommendations using generative AI and image analysis to reduce manufacturing delays. It demonstrates a multimodal recommender system that integrates with existing quality ticketing systems to accelerate quality engineering decisions.