AI Due Diligence for Industrial Investments

Many AI claims around industrial businesses rely on assumptions that do not hold up under operational scrutiny. Good investment decisions require independent technical judgment on what is real, what is risky, and what is realistic within the holding period.

How I Help

Pre-Acquisition Due Diligence
Independent assessment of AI claims, data conditions, system architecture, technical debt, and team capability. Identifies downside exposure and tests AI-linked value assumptions against operational reality.

Value Creation Roadmap
Post-acquisition AI strategy: what can realistically be achieved within the holding period, sequenced into milestones with dependencies, risk flags, and resource requirements.

Ongoing AI Advisory
Fractional technical support through the hold. Helps portfolio companies execute on the AI roadmap, course-correct when conditions change, and avoid common failure modes.

How I Work

Every engagement starts with a scoping conversation to understand the deal context, timeline, and what questions need answering. I assess the technical landscape, then deliver clear, commercially relevant judgment.

The goal is to give diligence teams the technical clarity they need to make well-informed decisions.

Engagement Structure

Most engagements follow three phases:

1. Scoping and Context
Understand the deal thesis, the AI claims, and the questions that matter most.

2. Technical Assessment
Evaluate data conditions, system architecture, team readiness, and operational constraints.

3. Findings and Roadmap
Deliver clear, actionable conclusions on risk, upside, and the path forward.

I work with a limited number of clients at a time to ensure each engagement receives the depth and precision it needs.