Security, built for AI agents.

AI scaled on a simple assumption: deploy the agent, trust the output. It worked well enough when agents were tools, but it breaks when agents are actors.

Not everyone will feel this problem yet. The most advanced enterprises are now running hundreds of agents across dozens of platforms, each with different access, different instructions, different behaviors. No two are the same, and none of them are fully legible.

The question is no longer whether your AI can do the job. It’s whether you can trust it with the autonomy it needs to do it at scale.

Today, no single system knows what every agent is, what it can touch, and what it has already done, so real autonomy stays out of reach. That leaves two bad options: lock agents down and lose the value, or let them run blind and carry the risk.

This is the problem Isochronic exists to solve. We are building the identity infrastructure for the enterprise AI estate, the infrastructure layer that makes heterogeneous agent deployments observable, auditable, and actionable. Not by slowing AI down, but by giving enterprises the confidence to let it run.

Isochronic is built by people who have lived this from both sides, building the infrastructure enterprises depend on and owning the security decisions that govern what runs on top of it. Yannis spent four years as CTO of a McKinsey spinout behavioral science and decision provenance fintech covering $265B in assets, where the call on whether to trust a new system was his to make. Anna built authentication infrastructure at Bloomberg, then scaled its first production AI agent to all 10,000 of the firm’s engineers. We’re backed by Entrepreneur First, and working with design partners on context-driven Attribute-Based Access Control, behavioral fingerprinting of agents, and Just-in-Time provisioning.