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AWS Solutions Library

Guidance for Personalized Ecommerce Recommendations Using Amazon Bedrock Agents

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Overview

This Guidance demonstrates how to implement personalized ecommerce recommendations using Amazon Bedrock Agents. The Guidance leverages advanced natural language processing to analyze customer preferences and behavior, providing tailored product suggestions that enhance the shopping experience. Integrating Amazon Bedrock Agents into ecommerce systems can help you boost customer engagement, increase conversion rates, and optimize recommendation strategies. Built on a robust foundation of cloud services, this Guidance illustrates how to create scalable, efficient recommendation agents while maintaining security and cost optimization.

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

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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. 

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Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

DynamoDB and Lambda streamline data management and backend processing tasks. DynamoDB delivers high availability and low-latency access with automated backups, monitoring, and security features that minimize manual intervention. Lambda executes code in response to events without infrastructure management, automatically scaling to match demand.

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AWS Identity and Access Management (IAM) and Amazon OpenSearch Serverless establish robust security controls for data access and user management. OpenSearch Serverless implements fine-grained access control for precise user permissions over search and analytics data. Through seamless integration with IAM, authentication and authorization mechanisms help ensure data remains protected while maintaining stringent access controls.

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Lambda and DynamoDB create a foundation for consistent, uninterrupted operations. Lambda distributes workloads across multiple Availability Zones, providing built-in fault tolerance and automatic scaling for varying demands. DynamoDB enhances this reliability through multi-Region replication, automatic scaling, and comprehensive backup capabilities so that data remains accessible and protected even during system failures.

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Lambda and DynamoDB deliver optimal performance through intelligent resource utilization. Lambda executes backend logic only when triggered, eliminating idle resource consumption. DynamoDB provides fast data access through built-in caching and indexing, enabling rapid retrieval of information while automatically scaling to match user demand patterns.

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OpenSearch Serverless eliminates unnecessary spending through dynamic resource allocation. By automatically scaling OpenSearch Compute Units based on actual usage patterns, resources are provisioned only when needed. This approach prevents overprovisioning while maintaining responsiveness during peak traffic periods.

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Amazon S3 Intelligent-Tiering reduces environmental impact through smart data storage management. The automated movement of data between storage tiers based on access patterns optimizes energy consumption without compromising accessibility. When data becomes less frequently accessed, it automatically transitions to lower-energy tiers, minimizing the carbon footprint of long-term data storage.

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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.