AI governance for regulated industries. Healthcare first.
Your organization is already using AI.
The question is whether anyone owns it.
Control Layer gives compliance, legal, and privacy leaders one record of every AI system: who owns it, who approved it, and the evidence behind the decision.
No pitch deck. No demo environment. A direct conversation about your governance gaps.
AI adoption inside regulated organizations is outpacing every governance framework built to contain it.
Employees are using AI tools. Vendors are embedding AI into products you've already contracted. Agents are making decisions that touch patient data, financial records, and legal exposure, often without a policy, an audit trail, or a clear owner.
Boards are asking who is accountable. Regulators are writing the rules. The organizations that have already established governance infrastructure will answer both questions with confidence. The ones that haven't will scramble.
Control Layer is built for the compliance and legal leaders who understand that "we'll govern it later" is no longer a defensible position.
Good faith is not a governance program. Regulators in the US and EU now expect organizations to show who approved their AI and why, on timelines that differ by jurisdiction. Organizations that build the record early answer those questions with evidence.
A governance operating layer built for the people accountable for AI risk.
Starting takes no engineering team. Designed for compliance, legal, and privacy leaders accountable for AI risk.
Know
Know which AI tools are in use, what data they touch, and who approved them. One inventory your legal team can stand behind and your auditors can verify.
Decide
Name an owner for every AI system. Route each new use through intake, review, and approval, with policy written in plain language.
Prove
Keep a tamper-evident record of AI decisions, approvals, and owner attestations in the Decision Ledger. Produce board, auditor, and regulator views from the same record.
Risk-aware operations
See which systems carry the highest risk tier and where approvals are overdue. Enforcement at the gateway follows in a later phase and covers traffic routed through it.
Every AI approval, on the record.
A tamper-evident record of who approved which AI system, under what authority, and on what evidence.
Record
Each approval, rejection, exception, and risk acceptance becomes a record tied to a named person and the policy that gave them authority to decide.
- System, use-case, and model-change approvals
- Conditions and review dates
- Authority basis and delegation by risk tier
- Corrections added as new records, never edits
Verify
Records are append-only and chained, with daily checkpoints written to write-once storage. Any alteration breaks the chain and shows.
- Chain verification on demand
- Approvals flagged when a vendor changes the model
- Coverage: share of AI systems with a current decision
- Read-only auditor workspace
Share
Give an auditor, insurer, or health system customer the evidence for one AI system or one period, in a form they can check themselves.
- Evidence packs for audits and regulator inquiries
- Scoped records for third-party review
- Board and committee views from the same record
Metadata, not content. The ledger holds decisions, people, authority, and references to evidence. Prompts and patient data stay in your systems.
What it does not do. It shows what was recorded, not what was decided elsewhere. It supports defensibility; it does not guarantee a regulator's conclusion.
Start with an assessment.
An integrated HIPAA Security Risk Analysis and AI Risk Assessment shows where AI operates in your organization, what data it touches, and where the risk sits.
You receive an inventory of the AI systems found, a prioritized risk register, and a 90-day remediation plan. The results load into Control Layer when you are ready.
Built for regulated industries where governance isn't optional.
Healthcare first. The same accountability problem exists wherever trust is non-negotiable.
Healthcare AI governance
Establish defensible oversight of AI tools that touch patient data, clinical workflows, and covered entity obligations. Know what's deployed, who approved it, and whether it meets the standard of care your organization has committed to.
Compliance and audit readiness
Replace manual evidence gathering with a governance record kept as decisions are made. When an internal audit, a regulator, or a board committee asks what your AI governance program looks like, have a real answer.
Vendor and embedded AI
Vendors add AI to products you already use, often after you sign. Control Layer records each feature and asks its owner to confirm what it does and what data it touches. We track renewals and release notes to catch new ones.
Other regulated industries
The same registry, approval workflow, and evidence record apply to financial services and other regulated industries. We start with healthcare.
A mission-driven company focused on making AI governance operational, auditable, and real.
Control Layer AI exists because the gap between AI adoption and AI accountability is widening, and the organizations most exposed are the ones operating in regulated industries, where the consequences of ungoverned AI are real.
We are building the governance infrastructure that compliance, legal, and privacy leaders need to establish accountability, produce evidence, and stay ahead of the regulatory curve.
We work directly with enterprise leaders, regulated-industry operators, and the advisors and partners who support them.
Chris Bowen first founded DirectClarity (clinically integrated network, ~43,000 physicians), then ClearDATA (healthcare cloud security, $80M raised, backed by Norwest, Humana, Merck). CISSP, CCSP, CIPP/US, CIPT. Past member of the Forbes Technology Council.
Read the full bio →Ready to talk about AI governance at your organization?
We work with compliance leaders, legal teams, and privacy officers in regulated industries. If you're trying to get ahead of AI accountability, let's have a real conversation.
CCOs, legal teams, privacy officers, compliance leaders, and executives accountable for AI risk in regulated industries.
No pitch deck. No demo environment. A direct conversation about where you are and what governance needs to look like for your organization.