Investor Diligence & AI Derisking

Independent technical and AI diligence for investors evaluating healthcare technology and AI-enabled targets—separating durable product and data advantages from fragile pilots, vendor dependencies, and undisclosed model risk before capital moves.

Who it's for

PE and VC investment teams, deal leads, and portfolio operating partners evaluating healthcare AI or health-tech acquisitions, investments, or portfolio company risk exposure.

Top outcomes

  • Independent technical and AI risk assessment ready for the investment committee
  • Clear view of what's durable IP vs. vendor-dependent or pilot-stage AI
  • Regulatory and data-rights exposure mapped (HIPAA, CMS, model provenance)

Problems it solves

AI and product claims in the data room don't hold up under technical scrutinyNo independent view of model risk, data rights, or regulatory exposure pre-closeVendor and build-vs-buy dependencies hidden inside the target's AI stackTechnical debt and pilot-stage fragility mistaken for production-grade capability

Engagement formats

  • Fixed-fee diligence sprint (1–3 weeks, matched to deal timeline)
  • Rapid technical/AI risk memo for time-boxed deal processes
  • Add-on: post-close 100-day AI derisking and value-creation plan
  • Independent technical and AI risk assessment ready for the investment committee
  • Clear view of what's durable IP vs. vendor-dependent or pilot-stage AI
  • Regulatory and data-rights exposure mapped (HIPAA, CMS, model provenance)
  • Actionable 100-day post-close derisking roadmap for the operating team
  1. Data room and technical artifact review
  2. Management and technical team interviews
  3. AI/product architecture and model risk assessment
  4. Regulatory and data-rights exposure mapping
  5. Investment committee-ready findings memo
  • Time to investment-committee-ready findings
  • Material risks identified pre-close vs. post-close
  • Valuation-relevant findings surfaced
  • Post-close derisking roadmap adoption
  • Pre-LOI technical diligence on a healthcare AI platform acquisition
  • AI/model risk assessment for a health-tech growth equity investment
  • Post-close 100-day derisking plan for a newly acquired care-management AI vendor
  • AI and product claims in the data room don't hold up under technical scrutiny
  • No independent view of model risk, data rights, or regulatory exposure pre-close
  • Vendor and build-vs-buy dependencies hidden inside the target's AI stack
  • Technical debt and pilot-stage fragility mistaken for production-grade capability

Ready to architect your AI strategy with someone who has operated at every level of the stack?

Schedule a 15-minute strategy briefing or send a direct note — let's determine fit.