Service 06
AI Due Diligence
Most AI companies overstate their technical moat. As a former deep tech VC investor, I know how to separate real AI capability from well-packaged demos. I conduct technical due diligence for investors, acquirers, and boards evaluating AI-native companies.
The assessment covers four dimensions: technical architecture (is it real, scalable, and defensible?), team capability (can they actually build what they claim?), data assets (is the data moat real or easily replicable?), and operational maturity (can they deliver reliably at scale?).
The output is a structured diligence report with a clear risk matrix, technical debt inventory, and go/no-go recommendation. I've evaluated companies across semiconductors, computer vision, agent systems, and enterprise AI, from pre-seed to growth stage.
- Technical architecture assessment & risk matrix
- Team capability evaluation
- Data moat & defensibility analysis
- Structured diligence report with go/no-go recommendation
VC and PE investors evaluating AI deals, corporate M&A teams, boards assessing AI capability, and founders preparing for diligence.