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AI Compliance Checks
Adopt AI with confidence — and the documentation to defend it.
In shortTriton Foundry audits how your organization uses AI against the obligations that govern you — HIPAA, CMMC, state privacy law, insurance questionnaires, client contracts — and closes the gaps: written policy, data classification, vendor terms, logging, and the evidence file that proves control.
What is an AI compliance check?
A structured audit of how AI is actually used across your organization — sanctioned tools, shadow tools, vendor features that quietly became AI — measured against the obligations you already carry. It answers the questions that now appear in audits, insurance renewals, and enterprise procurement: what data reaches which models, under what terms, logged how, governed by whom. The output is evidence, not vibes: a findings register, a remediation plan, and a governance pack you can hand to whoever is asking.
What usually turns up?
The same classes of exposure, everywhere. Staff pasting regulated data into consumer chatbots because no sanctioned tool exists. AI features enabled by vendors inside products nobody re-reviewed. Assistants with tenant-wide reach inheriting years of permission sprawl. Zero logging of prompts or outputs anywhere. Vendor terms that permit training on your data. None of it is exotic; all of it is answerable — once it is written down and ranked.
How does this connect to HIPAA, CMMC, and state privacy law?
Directly — AI use is already regulated by the frameworks you answer to; the audit makes the mapping explicit. Health information reaching a non-BAA model is a HIPAA problem, not an AI curiosity. CUI touching a consumer assistant is a CMMC scoping failure. Consumer data flowing to a vendor without disclosure trips state privacy statutes. The parent company’s compliance practice has worked these frameworks for regulated clients for years; the AI layer extends that work rather than reinventing it.
What does engagement and follow-through look like?
Discovery interviews plus technical inspection produce the findings register within weeks, ranked by regulatory exposure. Remediation follows in priority order — policy and quick technical wins first, structural fixes scheduled. Then the part most governance efforts skip: an annual re-check cadence and a standing rule set for evaluating each new AI tool before it enters the building, so compliance is a system, not a one-time binder.
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AI Compliance Checks: common questions
Why do we need an AI compliance check at all?
Because your staff already use AI, sanctioned or not, and regulators, insurers, and enterprise clients have started asking pointed questions about it. An audit establishes what is actually happening, maps it to your obligations, and produces the written evidence that you govern it.
Which frameworks do you map against?
The ones that already bind you: HIPAA for health data, CMMC and DFARS for the defense supply chain, state privacy laws in the states where you operate, PCI where cards are touched, plus cyber-insurance questionnaires and client contract clauses. AI-specific guidance is folded into those rather than treated as a separate universe.
What does the deliverable look like?
A findings register mapped to specific obligations, a prioritized remediation plan, and the governance pack: AI use policy, data classification with tool rules, approved-tool register, vendor review file, and logging requirements. Auditors and insurers get answers instead of shrugs.
Do you also fix what you find?
Yes. The same organization can implement the technical controls — tenant settings, logging, retention, access boundaries — and Foundry builds compliant alternatives when staff are using risky tools because nothing sanctioned exists. Governance that only says no gets ignored; ours ships replacements.
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Have a system in mind?
Describe what you are trying to build or fix. A senior engineer reviews every inquiry and responds directly, with a technical read on the problem.