RegulateAI/ML builds AI security and governance programs for enterprises that are shipping AI faster than their compliance function can follow. EU AI Act readiness, AI security architecture, and fractional CISO leadership, delivered by practitioners who run this at enterprise scale.
Whereas enforcement timelines do not wait for architecture reviews, and whereas every AI system your teams deployed last quarter is already in scope of someone's regulation: the organizations that fare best are the ones that governed themselves first.
Every engagement is scoped in writing, staffed by the person you spoke to, and measured against criteria we set together before work starts.
A structured assessment of where your AI estate actually stands against the EU AI Act, NIST AI RMF, and ISO/IEC 42001, ending in a prioritized roadmap your board can fund and your engineers can execute.
Hands-on security architecture for the AI you're deploying now: LLM gateways, RAG pipelines, agentic identity, model access control, and the cloud infrastructure underneath all of it.
Senior AI security leadership without the executive headcount. We own your AI risk agenda on a fractional basis: policy, vendor reviews, incident readiness, and the standing answer to "who owns AI risk here?"
Not a maturity model in a slide deck. These are the places where AI programs fail audits, leak data, or grant an agent more access than any employee has ever held.
EU AI Act classification, conformity obligations, technical documentation, and the evidence trail a notified body or regulator will ask for first.
Machine-speed identity for AI agents: scoped credentials, short-lived tokens, human accountability chains, and kill switches that work.
What your models train on, retrieve from, and emit. DSPM for AI pipelines, cross-border transfer constraints, and retention that matches your promises.
The CNAPP-grade security posture underneath the models: identity, network boundaries, secrets, and the misconfigurations that turn a pilot into a headline.
Key enforcement milestones. If your organization touches the EU market, some of these already apply to you.
Unacceptable-risk AI systems banned outright, and AI literacy obligations began for providers and deployers.
Transparency, documentation, and copyright obligations for general-purpose AI model providers, with the governance structures behind them stood up.
The bulk of the Act applies, including the high-risk obligations most enterprise deployers have been deferring. This is the milestone most compliance programs planned backward from, and many missed.
Extended transition ends for AI systems embedded in products already covered by EU product safety law.
// Dates reflect the Act's published application schedule. Confirm current enforcement status and any amendments with counsel; this page is not legal advice.
Governance that lives in a binder fails. Every phase ends in something your teams run without us in the room.
Inventory the AI estate, classify risk, and map it against every regime you're exposed to. Two to four weeks, ending in a written findings report.
Design the controls: technical architecture, policy, and the operating model that assigns every AI risk a named owner.
Implement with your engineers, not around them. Controls land in code, pipelines, and runbooks, gated by your existing review process.
Build the evidence trail: documentation, metrics, and audit artifacts that hold up in front of a regulator, a customer, or your own board.
Sixty minutes. You describe what your organization is deploying; we tell you where you're exposed and what we'd fix first, whether or not you hire us.
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