There's a window between when agentic AI systems become standard enterprise infrastructure and when regulators fully catch up with how to govern them. Insygna is building inside that window.

The startup, founded by Michael Beygelman (who previously built and exited Claro Analytics and led AI product development at Wilson) is constructing what he describes as the identity and credentialing layer for AI agents: the mechanism by which enterprises can know which agent did what, under what authority, with what level of verified trust.

It's an infrastructure play, not a SaaS dashboard. The distinction matters because the problem Insygna is solving isn't a reporting problem. It's an architectural one. Current enterprise AI stacks have no native way to distinguish one agent from another, or to enforce accountability when orchestration chains span multiple models and systems.

Beygelman draws an explicit analogy to IAM (Identity and Access Management), which became non-negotiable infrastructure for human workforce security. His argument is that multi-agent AI deployments require the same foundational layer, and that organizations building without it are accumulating governance debt that will become costly to unwind.

The EU AI Act's August 2026 enforcement deadline provides near-term commercial urgency. But the longer arc of Insygna's thesis is that agent identity becomes a baseline enterprise requirement, regardless of regulatory pressure, as agentic AI matures.

Insygna is currently in development and expects to launch ahead of the EU enforcement window.