Build an autonomous ecommerce assistant with AWS End User Messaging, Amazon …

In this post, we walk through Claw Boutique, an open-source reference architecture that connects a web storefront, WhatsApp, email, and Telegram into a single OpenClaw-driven ecommerce experience on AWS. Buyers interact through WhatsApp and a web store. The shop owner manages everything from Telegram, where an artificial intelligence (AI) agent processes restock, refund, and order commands. The project uses Amazon Bedrock AgentCore Runtime with the Strands Agents SDK, an open-source framework for building AI agents, for real-time buyer chat. Amazon Elastic Kubernetes Service (Amazon EKS) hosts the seller-side AI agent (OpenClaw, an open-source AI agent gateway). AWS End User Messaging Social provides managed WhatsApp Business integration. The entire stack deploys with a single AWS Cloud Development Kit (AWS CDK) command. Architecture overview The architecture separates concerns into three channels that share a common Store API and database. Figure 1 – Claw Boutique architecture on AWS Buyer channel (WhatsApp): Inbound WhatsApp messages arrive through AWS End User Messaging Social, which provides a managed WhatsApp Business API integration. Messages publish to an Amazon Simple Notification Service (Amazon SNS) topic, which triggers a Dispatcher AWS Lambda function. The dispatcher invokes a Strands Agent hosted on Amazon Bedrock AgentCore Runtime, running Amazon Nova Lite
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