Vorlon

Vorlon is a security platform built for a world where AI agents and automated systems handle sensitive data. It focuses on the 'engine room' of modern software: the constant, high-speed data flows between SaaS applications, AI agents, and machine-to-machine integrations. Traditional security tools look at who has access to what, but Vorlon watches what happens after access is granted. It tracks the actual movement of data, API calls, and agent behaviors across your entire digital ecosystem, aiming to spot risks that emerge from how these automated systems interact.

It works by using read-only APIs to create a live model of your connected tools, which Vorlon calls the DataMatrix™. This model continuously observes activity, enriches it with behavioral context and risk scoring, and simulates potential threats. The platform is designed to detect anomalies in how agents use credentials and move data, map the potential 'blast radius' of a compromised integration, and provide the context needed for a response. Its architecture is built for scale, prioritizing broad observability over intrusive control.

This tool is for security teams in organizations that rely heavily on SaaS applications and are deploying AI agents for automation. It's particularly relevant for companies worried about data exfiltration through automated integrations or the cascading effects of a single compromised agent. Use cases include monitoring sanctioned and 'shadow' AI agent deployments, securing complex SaaS supply chains, and getting visibility into data flows that legacy tools like CASB or DLP often miss.