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AWS Solutions Library

Guidance for a Retail Pricing Agent on AWS

Overview

This Guidance demonstrates how to transform complex retail pricing decisions into data-driven recommendations by coordinating specialized AI agents that analyze demand forecasts, competitor pricing, and profit margins. Three AI agents work in parallel—one forecasting market demand using historical data, another monitoring real-time competitor pricing, and a third ensuring profitability targets are met. A supervisor agent coordinates these specialized agents through AWS Step Functions, with Amazon Bedrock powering the AI capabilities and Amazon SageMaker Canvas handling demand predictions. You can reduce pricing analysis from days to minutes while maintaining final control over all pricing decisions, enabling faster market response with greater confidence.

Benefits

    Deploy parallel AI agents that simultaneously analyze demand forecasts, competitive intelligence, and margin compliance. Reduce pricing analysis time while improving decision accuracy through coordinated machine learning insights.

    Leverage AWS Lambda and Step Functions to automatically handle fluctuating workloads without infrastructure management. Focus your team on strategic pricing while AWS manages the underlying compute resources.

    Implement real-time margin compliance checks using specialized AI agents that validate pricing recommendations against your business rules. Prevent pricing errors before they impact revenue or customer relationships.

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.

Download the architecture diagram

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. 

Go to sample code

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