CognitionHive helps regulated enterprises — banking, insurance, healthcare, life sciences — build the Codified Reasoning Infrastructure (CRI) that puts AI-generated code under the same control regime as human-authored code.
Agentic coding operates at sub-minute timescales, outside the pull request, and leaves no cryptographic trail of the reasoning behind changes. Existing controls assume human authors.
OCC 2011-12, FDA 21 CFR Part 11, and SOC 2 CC7 controls were written for human-authored code. Examiners are beginning to ask how agentic decisions are governed.
When an AI agent modifies a payment calculation or an auth path, who made the decision? What was the reasoning? Standard git history does not capture that context.
Human commits are signed. Agentic commits typically are not. There is no way to verify that a commit came from the agent it claims, or that it has not been altered.
Sensitivity rules — auth paths, payments, PII, regulated data — are enforced at merge time for humans. Agents bypass those gates entirely.
All services are built on the Codified Reasoning Infrastructure (CRI) methodology and the Prufs framework. No platform deployment required to begin.
An 8-dimension maturity scorecard, regulatory gap analysis, and prioritized remediation roadmap for regulated enterprises evaluating agentic coding readiness.
Instrument a pilot team or workload with Prufs SDK, custom OPA policy rules, and CI/CD integration. Includes team training and two-week go-live support.
A control-by-control mapping from your AI-generated code practices to specific regulatory control objectives — examiner-ready, with evidence.
Ongoing access to CRI expertise for platform evolution, regulatory updates, and team coaching — for organizations that have completed an Implementation engagement.
CRI engagements are scoped to the specific regulatory framework your organization operates under. Multi-framework cross-reference available.
CognitionHive serves enterprises where AI-generated code decisions carry regulatory, financial, or patient-safety consequences.
OCC, Federal Reserve, FDIC model risk management requirements
State regulatory filings, actuarial model governance
HIPAA Security Rule, clinical decision support oversight
FDA 21 CFR Part 11, GMLP, electronic records compliance
NERC CIP, operational technology AI governance
B. Wade Lovell is the principal of CognitionHive. He brings 30+ years of enterprise technology leadership, spanning CTO, Technical Architect, and AI Architect roles across banking, insurance, and enterprise software. He holds a Columbia MBA, a CPA license, a PMP certification, an MS in AI, and 42+ professional certifications.
His doctoral dissertation at Walsh College focuses on LLM agent reliability in banking — the same domain CRI consulting addresses. He is a published author on Ethical AI in Education, the Workforce, and the C-Suite, and has held technical architect roles at Salesforce and Simpatic.
The Codified Reasoning Infrastructure (CRI) methodology grew out of the observation that regulated enterprises adopting agentic coding have no existing control framework that treats agent identity, causal reasoning, and policy enforcement as structural properties of a commit. CognitionHive exists to close that gap.
Tell us about your organization. We will respond within one business day to schedule a discovery call.