The Problem

Organizations implementing AI in regulated environments face a hidden risk: epistemic drift—when AI-enabled systems gradually erode decision-making integrity without triggering obvious red flags. By the time leadership notices, the damage is operational, reputational, and regulatory.

Traditional AI governance frameworks focus on initial deployment: bias testing, ethics review, documentation. But the real failures happen 6-12 months later, when AI systems drift from their approved parameters without triggering alerts. Decisions can't be traced. Outcomes can't be defended. You're in crisis mode.

The Solution

An EpistemIQ Readiness Assessment identifies where AI integration creates systemic risk in your organization before it becomes a compliance failure or operational crisis.

Over two weeks, a comprehensive analysis of your AI implementation detects epistemic drift and the gaps it creates, the invisible points where AI-enabled decisions stop aligning with reality. This uses information-theoretic methods to analyze compression dynamics and information flow in your governance architecture.

What You Get

Comprehensive Risk Analysis

• Identification of epistemic gaps in your current AI implementation
• Assessment of where decision-making integrity is most vulnerable through information-theoretic analysis
• Analysis of governance blind spots that traditional frameworks miss, including compression efficiency failures

Prioritized Recommendations

• Risk prioritization framework specific to your regulatory environment
• Actionable governance structures that preserve integrity while enabling innovation
• Practical procedures aligned with NIST AI RMF, ISO 31000, and ISO/IEC 42001
• Architectural guidance for maintaining information flow and compression efficiency

Executive Presentation

• Presentation of findings to leadership
• Clear documentation you can use for compliance, audit, or strategic planning
• Q&A to address your specific implementation concerns

Engagement Options

EpistemIQ Readiness Assessment

Timeline: 2 weeks
Ideal for: Initial risk identification and governance gap analysis

• Week 1: Discovery, analysis, and risk identification using information-theoretic methods
• Week 2: Framework development and executive presentation

Extended Implementation Support

Timeline: Custom scope (typically 3-6 months)
Ideal for: Organizations requiring ongoing architectural guidance during AI deployment

For complex implementations requiring continuous epistemic drift monitoring, architecture review, and governance refinement, extended engagements and retainer arrangements are available.

Schedule a discovery call to discuss scope and timeline for your specific needs.

Is This Right For You?

This engagement is designed for:

• Organizations implementing AI in healthcare, finance, life sciences, or regulated industries
• Leadership responsible for risk management, compliance, or operational integrity
• Teams that need to understand systemic risks before they become crises
• Organizations with established compliance frameworks integrating AI (FDA/EMA, SEC/FINRA, AML/KYC)

Next Steps

Book a 30-minute discovery call to discuss your specific challenges and whether an EpistemIQ Assessment is right for your organization.

Schedule Call

Questions? Email me at jenniferfkinne@proton.me

About EpistemIQ

EpistemIQ is a patent-pending information-theoretic method for detecting epistemic drift in AI systems, developed over 20+ years in high-stakes research environments at Harvard University.

The approach analyzes compression dynamics and information flow to identify epistemic gaps that emerge when AI integration meets operational complexity in regulated settings—gaps that traditional risk assessments miss until it's too late.

This method has been validated in environments where decisions must remain traceable, explainable, and resilient under regulatory scrutiny, including biosafety oversight, clinical research compliance, and FDA/EMA pathways.

The underlying theoretical framework is detailed in The Information-Theoretic Imperative: Compression and the Epistemic Foundations of Intelligence (arXiv:2510.25883), currently under review at a scientific journal. Learn more about EpistemIQ →