Compliance
Meeting regulatory requirements and industry standards for AI systems
Hero Post
By Adesh Gairola
Agent identity isn't solved. Here's the model I use anyway.
Agent identity makes more sense as four stacked layers: a tamper-proof token format, cryptographic proof of which workload is running, a delegation chain that keeps the human as the subject, and a way to onboard to a service an agent has never met. Climb all four and you've proven who the agent is. You still haven't proven that what it did was okay.
Featured Posts
By Adesh Gairola
Three Regulatory Philosophies, One Global AI Market
The EU (9/10 risk), US (5/10), and Australia (6/10) take vastly different approaches to AI regulation. Build for EU standards globally—the Brussels Effect means you'll need them anyway.
By Adesh Gairola
Identity Crisis in AI Agents: Why Traditional IAM Is Breaking Down
AI agents are breaking traditional identity and access management systems. From impersonation risks to cross-domain delegation chains, enterprises need new frameworks that balance autonomous operation with accountability and security.
By Adesh Gairola
How to use safety benchmarks to assess technical and business risk
We translate academic benchmarks into actionable risk signals through our proprietary AI governance pipeline, helping organizations implement regulatory-ready controls.
