video1.0<iframe src="https://www.loom.com/embed/ab966bb76ebd4c44bef1ec6b0c906fdc" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/ab966bb76ebd4c44bef1ec6b0c906fdc-a81216352557ed84.gif209.061In this video I walk you through an autonomous cloud security and compliance auditing system I architected from scratch — designed to replace hours of manual AWS infrastructure review with a fully automated, AI-powered pipeline. What it does: Extracts metadata from 10+ AWS services like S3, RDS, EC2, IAM, Lambda, CloudTrail, KMS, and more Routes every finding through a SWITCHBOARD that classifies results as Pass, Fail, or Manual Review Stores all audit results in Supabase as a persistent, queryable audit trail Runs the full infrastructure data through a Groq + Llama 3 AI agent in Langflow to generate a 200-point security assessment Delivers a downloadable compliance report ,ready to hand off to any team Tech used: n8n · Langflow · Groq · AWS CLI · Docker · Python/Flask · Supabase · LLM Prompt Engineering The problem it solves: What used to take an engineering team hours of manual work ,this system completes in under two minutes.