Governance for the AI your company already uses.
A vendor-agnostic framework for companies deploying AI agents in regulated operations. Six layers. Model-agnostic. Built to survive the next release and the next vendor switch.
The problem #
Companies are adopting AI agents for real work without any governance structure.
No guardrails on what the agent is allowed to do. No audit trail of what it did. No structured workflows for recurring tasks. No institutional memory across sessions. No defined role boundaries for the agent itself.
This is the same pattern that played out in early cloud adoption. Companies moved fast, got burned, and then paid consultants to clean up afterwards. The companies that move ahead of that curve are the ones still paying for their own tools rather than their own cleanup.
Why this matters #
Regulated industries cannot afford ungoverned AI agents. The ones deploying them anyway are taking on risk they have not measured.
HIPAA. FINRA. SOX. Privilege. Safety-critical review. Every regulated workflow has an audit expectation, and no auditor accepts "the AI decided" as a written record. The governance layer is the reviewable system that makes the AI answerable.
The gap between "we use AI" and "we govern our AI use" is where the risk lives. Closing it is not a one-time project. It is a practice.
Verticals we serve
Four industries where ungoverned AI creates disproportionate risk, and where the framework has the most immediate leverage.
Healthcare organizations are adopting AI for documentation, patient communication, and clinical decision support.
View detail → Financial ServicesFinancial firms face the AI governance problem on three fronts at once: customer data protection, regulatory reporting (SOX, FINRA), and the audit trail on any AI-influenced recommendation..
View detail → LegalLaw firms are integrating AI for document review, case research, and client communication.
View detail → Manufacturing and EngineeringEngineering and manufacturing organizations are using AI to review technical drawings, flag quality issues, and check safety-critical documentation.
View detail →Assessment. A focused discovery engagement. We map current AI usage, risks, and opportunities against the six-layer model, and deliver a prioritized roadmap.
Implementation. We design and deploy the governance layer: guardrails, workflows, observability, domain knowledge, memory, and identity configurations customized to the organization.
Managed Operations. Ongoing governance maintenance. AI providers change, regulations shift, domain knowledge ages. Someone has to keep the system current.
See how engagement works in detail →Why 'corePHP' #
We build governed systems, not just governance policies. The framework is deployed and tested in our own operations before it is offered to anyone else.
We are vendor-agnostic. The framework works with Claude, GPT, Gemini, or open-source models. When providers change, the governance layer stays intact.
We focus on mid-market organizations: fifty to five hundred employees, regulated or regulation-adjacent. We are sized to move faster than large consultancies and equipped to take the work the way an engineering team takes it.
Colophon
Presented by 'corePHP'. Our core is People Helping People.