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- Guidance for Building Agentic AI-Powered Hyper-Personalized Customer Experience on AWS
Guidance for Building Agentic AI-Powered Hyper-Personalized Customer Experience on AWS
Overview
This guidance demonstrates how to build an AI-powered hyper-personalization platform that delivers tailored product recommendations based on customer profiles and unique individual attributes. The solution showcases multi-agent collaboration, combining general e-commerce agents with domain-specific agents to enable hyper-personalized 1:1 search experiences and to execute actions on behalf of users, such as purchasing products. Leveraging Amazon Bedrock and OpenSearch, the application demonstrates keyword search, semantic search, and intelligent product discovery. While designed for healthcare retail, this architecture can be adapted to all digital retail industries like Automotive and CPG, featuring near real-time AI chat assistance powered by coordinated AI agents.
Benefits
Deploy multi-agent AI that continuously adapts recommendations, content, and interfaces in near real-time based on each customer's unique profile. Move beyond traditional collaborative filtering to create 1:1 personalized interactions that increase engagement and conversion rates.
Launch your hyper-personalization platform without managing infrastructure or capacity planning. Automatically handle demand fluctuations while reducing operational complexity and lowering total cost of ownership through pay-per-use pricing.
Adapt specialized AI agents from healthcare retail to automotive, CPG, and other sectors requiring individualized recommendations. Leverage semantic search and contextual analysis to deliver relevant product suggestions tailored to each customer's specific needs.
How it works
Solution Overview
This architecture diagram illustrates an AI-powered product recommendation solution that provides personalized product suggestions based on customer profiles, hyper-personal customer data, and intelligent search capabilities.
Infrastructure Architecture
This architecture diagram illustrates the key infrastructure components for the web application and data sources used to deploy the solution on AWS.
Agent Collaboration Framework
This architecture diagram illustrates the Amazon Bedrock multi-agent collaboration using the Strands Agents SDK for the entirecustomer experience workflow.
AgentCore Implementation
This architecture diagram shows alternative agent hosting on Amazon Bedrock AgentCore. Deploy secure, scalable AI agents on AWS with Amazon Bedrock AgentCore's purpose-built infrastructure, enabling complex workflows across tools and data sources while eliminating infrastructure management overhead.
Deploy with confidence
Ready to deploy? Review the sample code on GitHub for detailed deployment instructions to deploy as-is or customize to fit your needs.
Disclaimer
The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.
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