Artificial Intelligence
Author: Nidhi Gupta
Nidhi is a Senior Partner Solutions Architect at AWS, specializing in data, AI, and analytics. She leads the Snowflake partnership, helping customers and partners architect and optimize Snowflake workloads on AWS. Nidhi brings extensive experience in production-scale data platforms, machine learning, generative AI, and advanced analytics. She is a frequent speaker at industry events, delivering technical sessions on topics ranging from agentic AI and open lakehouse architecture to enterprise compliance automation.
Automate AML alert triage with Amazon Quick and Snowflake Cortex AI
This post demonstrates that integration in action by automating one of the most labor-intensive workflows in financial services: anti-money laundering (AML) alert triage. You will build a triage workflow using Amazon Quick Flows and Snowflake Cortex, connected through the Amazon Quick Model Context Protocol (MCP) integration. In our testing environment, automated workflows built using Amazon Quick reduced alert investigation time from 30-90 minutes to under 5 minutes. Actual results may vary based on alert complexity and data volume.