Gateco: The Critical Security Middleware for Vector Databases & RAG

Are your AI agents bypassing your IAM and SSO? In this video, we dive into Gateco, the purpose-built security middleware designed to bridge the RAG Authorization Gap. While your vector database is great at finding "meaning," it often fails at checking "authorization"—leading to critical data leaks and security vulnerabilities. With the EU AI Act enforcement deadline of August 2, 2026 fast approaching, enterprises must move beyond "Wild West" AI deployments and toward audit-ready, secure architectures. What you’ll learn in this video: What the RAG Authorization Gap is and why it's a massive vulnerability. How Gateco’s "deny-by-default" architecture secures your AI retrieval. Why generic policy engines and DIY row-level security fail at scale. The high cost of non-compliance: penalties up to €15M or 3% of turnover. How to deploy Gateco in just 5 lines of Python with less than 25ms latency. Timestamps: 0:00 - Introduction to Gateco 0:38 - Why AI agents bypass IAM & SSO 1:00 - The RAG Authorization Gap Explained 1:48 - Gateco’s Infrastructure & Key Features 2:12 - The Catalyst: EU AI Act Deadline (August 2026) 2:53 - Gateco vs. Generic Policy Engines 3:43 - Pricing & Business Model Connect with Gateco: https://www.gateco.ai #EnterpriseAI #AISecurity #RAG #VectorDatabase #EUAIAct #Cybersecurity #Gateco #Middleware