Amazon Web Services published an end-to-end architecture for conversational supply chain intelligence, combining Amazon Quick (an enterprise AI assistant) with Amazon Bedrock AgentCore (a modular agentic platform) to bridge the gap between fragmented operational data and decision-makers (AWS Machine Learning Blog). The system uses the Model Context Protocol (MCP) to expose enterprise systems—ERP, procurement, monitoring, governance, quoting, invoice processing—as composable tools, allowing supply chain managers to ask questions like
Conversational AI drives supply chain and backend efficiency
ERPESB / iPaaSLLMAWSAmazonOracleSAPSalesforceAWS Agent RegistryAmazon Bedrock AgentCoreAmazon Quick
AWS combines Amazon Quick and Bedrock AgentCore for supply chain intelligence
Amazon Web Services unveiled a conversational supply chain platform pairing Amazon Quick (a no-code enterprise AI assistant) with Amazon Bedrock AgentCore (an agentic intelligence layer) to let supply chain managers query fragmented systems—ERP, procurement, monitoring, email—through plain-language chat and get live, cross-system answers in seconds instead of hours. For commerce practitioners, this pattern cuts decision latency by collapsing 45–60 minutes of manual system-hopping into a three-prompt conversation, while keeping every action gated for human approval and governed by deterministic policy rules.