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- 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.
- DAIVI is a reference solution with IAC modules to accelerate development of Data, Analytics, AI and Visualization applications on AWS using the next generation Amazon SageMaker Unified Studio. The goal of the DAIVI solution is to provide engineers with sample infrastructure-as-code modules and application modules to build their data platforms.
guidance-for-disaster-recovery-of-vmware-workloads-using-aws-elastic-disaster-recovery-service
PublicThis Guidance demonstrates how to implement disaster recovery for VMware workloads to AWS using AWS Elastic Disaster Recovery (AWS DRS). It helps organizations establish continuous replication and automated failover capabilities for both on-premises VMware environments and Amazon Elastic VMware Service (EVS).- 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 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.
- Comprehensive, scalable ML inference architecture using Amazon EKS, leveraging Graviton processors for cost-effective CPU-based inference and GPU instances for accelerated inference. Guidance provides a complete end-to-end platform for deploying LLMs with agentic AI capabilities, including RAG and MCP
- Guidance for Media2Cloud on AWS solution (formerly known as AWS Media2Cloud Solution) is designed to demonstrate a serverless ingest framework that can quickly setup a baseline ingest workflow for placing video assets and associated metadata under management control of an AWS customer.
- 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.
data-transfer-hub
PublicSeamless User Interface for replicating data into AWS.- 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.
- The AWS DeepRacer Event Manager (DREM) is used to run and manage all aspects of in-person events for AWS DeepRacer, an autonomous 1/18th scale race car designed to test reinforcement learning (RL) models by racing on a physical track.
- This guidance demonstrates how to deploy a comprehensive agentic application for advertising workflows using Amazon Bedrock AgentCore. The solution showcases advanced multi-agent collaboration across the entire advertising value chain - from strategic media planning and audience targeting to real-time bid optimization and publisher revenue manageme
- 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.