About PreMetric

PreMetric was created to address a growing institutional gap: organisations are committing capital, governance authority, and operational reliance to AI initiatives before the underlying decision has been properly documented, tested, or made defensible.

PreMetric conducts pre-deployment AI audits to evaluate whether AI initiatives should proceed, be modified, paused, or stopped before irreversible commitments are made. Each audit examines the system, evidence, assumptions, controls, deployment context, exposure, and governance conditions behind the decision. The audit produces an AI Decision Record that serves as institutional infrastructure for defensible governance, procurement scrutiny, investor diligence, regulatory inquiry, and accountability.

Pre-Deployment Audit

AI ambition

Initiative identified or proposed

Decision uncertainty

Evidence gaps, assumptions, exposure

PreMetric audit

Structured examination of the decision

Defensible decision record

Board-ready · Investor-ready · Auditable

Pre-deployment only. Point-in-time. Not retainer-based.

Why PreMetric exists

AI initiatives increasingly affect capital allocation, operational exposure, customer outcomes, regulatory posture, and board accountability. Yet many organisations still approve AI initiatives without a complete pre-deployment audit — without structured examination of the system, evidence, assumptions, controls, and governance conditions required for defensible decisions.

PreMetric exists to create a structured audit layer before deployment. Its role is to produce a documented basis for determining whether an AI initiative is sufficiently evidenced, governed, and defensible to proceed.

01

Decision gap

AI initiatives are often approved without a complete evidence chain linking value assumptions, deployment conditions, and governance readiness.

02

Accountability gap

Responsibility for deployment, ongoing oversight, exception handling, and reassessment is often unclear or unassigned at the point of approval.

03

Capital gap

Resources are committed before value assumptions, downside exposure, and implementation conditions have been tested against a structured evidence standard.

What PreMetric does

PreMetric conducts bounded, point-in-time pre-deployment AI audits that produce structured AI Decision Records. Every engagement concludes with a documented recommendation and an evidence chain — which may include technical evidence, benchmark results, vendor materials, validation documentation, governance records, and deployment assumptions — that can withstand board review, procurement scrutiny, investor diligence, and regulatory inquiry.

PreMetric's audit framework applies across digital, operational, and physical deployment contexts, including enterprise AI systems, agentic workflows, robotics, autonomous systems, industrial automation, and AI-enabled operational infrastructure.

01

Evaluates whether AI initiatives should proceed, be modified, paused, or stopped before irreversible commitments are made.

ProceedModifyPauseStop
02

Produces documented recommendations supported by a structured evidence chain.

03

Creates board-ready decision records for governance, investor, and regulatory scrutiny.

04

Operates before deployment, where decision leverage is highest and commitments remain reversible.

05

Surfaces assumptions, capital exposure, accountability gaps, and reassessment triggers.

How PreMetric is structured

PreMetric separates delivery, oversight, and assurance functions to preserve independence, methodological discipline, and decision defensibility.

Core Team

Delivery

Decision methodology, evidence review, capital exposure analysis, documentation, and client engagement.

  • Decision methodology design
  • Risk assessment and analysis
  • Regulatory interpretation
  • Documentation and deliverables
  • Capital allocation analysis

Advisory Board

Oversight

Independent review of methodology, governance posture, regulatory alignment, and institutional credibility.

  • Methodology review
  • Governance posture assessment
  • Regulatory alignment checks
  • Independence from delivery
  • Periodic framework evaluation

Governance & QA

Assurance

Internal quality standards, documentation audit trail, conflict controls, and framework consistency.

  • Internal quality standards
  • Documentation audit trail
  • Conflict of interest controls
  • Decision framework consistency
  • Evidentiary rigour checks
Structural separation

Advisory oversight is independent of delivery. Governance and quality assurance operate across both functions to maintain decision defensibility.

The Team

PreMetric is operated by a multidisciplinary team spanning capital allocation, enterprise risk, governance, and regulatory interpretation. Team members are selected for their ability to evaluate high-stakes decisions under scrutiny — not for AI system development or deployment experience.

MD

Chief Executive Officer

Mushtaq Dost

Responsible for strategic direction, client relationships, and ensuring the evaluation infrastructure remains rigorous, independent, and aligned with institutional AI governance demands.

Background in capital allocation advisory, enterprise transformation, and regulatory engagement across financial services and the public sector.

CA

Director, Decision Methodology

Catherine Aldren

Responsible for decision framework design, evidence standards, assessment discipline, and consistency across PreMetric reviews.

Previously led enterprise risk methodology at a global reinsurer.

MH

Head of Regulatory Interpretation

Marcus Heldmann

Translates regulatory requirements into operational evaluation criteria. Maintains alignment between PreMetric frameworks and evolving EU, UK, and international AI governance regimes.

Former regulatory affairs lead at a European financial services authority.

PN

Senior Risk Analyst

Priya Nandakumar

Conducts quantitative and qualitative risk assessments across AI deployment scenarios. Identifies exposure concentrations that require board-level visibility.

Background in actuarial science and institutional portfolio risk.

JW

Governance & Documentation Lead

James Whitford

Manages documentation standards and quality assurance across all deliverables. Ensures decision records meet the evidentiary requirements of board scrutiny and regulatory inquiry.

Previously managed governance documentation for large-scale infrastructure transactions.

SE

Capital Allocation & Transaction Analyst

Sofia Eriksson

Evaluates AI initiatives through the lens of capital allocation discipline. Applies institutional investment standards to pre-deployment decision quality.

Former analyst at a Nordic institutional asset manager.

Advisory Board

PreMetric's Advisory Board provides independent oversight on methodology, governance posture, and regulatory alignment. Advisors do not participate in commercial delivery or operational decision-making.

Capital Markets & Transactions

Dr. Henrik Lund

Reviews decision frameworks for consistency with institutional capital allocation and transaction diligence expectations.

Former managing director at a European investment bank with oversight of structured transactions.

Regulatory & Compliance

Anne-Claire Dufresne

Reviews methodology for alignment with governance, regulatory scrutiny, and decision defensibility across jurisdictions.

Former senior counsel at an EU regulatory body focused on digital services and financial regulation.

Enterprise Risk Management

Richard Okafor

Assesses whether risk evaluation methodologies appropriately capture operational, reputational, and systemic exposure from AI initiatives.

Previously chief risk officer at a multinational insurance group.

AI Governance & Ethics

Dr. Mei-Lin Tan

Reviews governance posture and ethical alignment of decision frameworks, with particular attention to proportionality and accountability structures.

Academic researcher in AI governance at a leading European university.

Public Sector & Institutional Oversight

Thomas Brennan

Evaluates whether frameworks meet the evidentiary and procedural standards expected by public sector institutions and oversight bodies.

Former director of institutional audit at a national government accountability office.

Advisory independence: Advisors review methodology, governance posture, and regulatory alignment. They hold no operational authority, do not participate in client engagements, and have no commercial interest in individual review outcomes.

Governance Statement

PreMetric is structured to preserve independence, methodological discipline, and decision defensibility.

Delivery framework

Delivery teams operate within a defined decision framework subject to internal quality assurance and documentation standards.

Advisory oversight

Advisory oversight supports governance posture, regulatory alignment, and methodological integrity without participating in commercial delivery or operational decision-making.

Institutional objective

Each PreMetric output is structured to support board review, investor diligence, regulatory inquiry, and institutional accountability without creating conflicts of interest or ongoing operational responsibility.

Scope boundary: PreMetric audits are point-in-time assessments tied to specific decision moments. They are not subscriptions, not monitoring services, and not retainers. Reassessment is triggered by material change — not by calendar interval.