AI Technical Diligence
An honest technical read before you wire the money.
Independent diligence on AI companies and investments. Architecture, model, data, team, moat, and cost, translated into language an investment committee can act on.
Who I work with
Built for the people writing the check.
Venture and growth funds
Pre-term-sheet and confirmatory diligence on AI bets. A senior operator read that does not depend on the founder's deck.
Family offices and LPs
Honest technical translation for capital that wants AI exposure without taking on hype risk.
Strategic acquirers
Pre-close diligence on AI platforms, teams, and IP. What is real, what is glued together, and what it costs to operate after close.
What I look at
Four lenses on every engagement.
Depth varies with scope and time. Every engagement covers all four, focused on the single decision in front of the committee.
Architecture, model, and data
Model choices, training and fine-tuning posture, data provenance, RAG and agent design, latency, throughput, and the unit economics of inference.
Security, governance, compliance
AI policy, data handling, model risk, audit posture, and where the company sits relative to regulated buyers.
Team and execution
Engineering bench, leadership maturity, hiring plan, and the gap between roadmap ambition and the team that has to ship it.
Moat, cost curve, competition
Defensibility under model commoditization. Where unit costs go as scale grows. Honest competitive read.
Deliverables
What you get.
A full engagement produces a written report your investment committee can read and act on, plus a working session to defend the findings.
- Kickoff call with the investment team to scope the questions that matter
- Document and data room review
- Founder, CTO, and key engineer interviews
- Live walkthroughs of architecture, model evaluation, and key code paths
- Vendor and infrastructure cost analysis
- Reference calls with customers or design partners where available
- Written report with executive summary, risk register, and recommended diligence follow-ups
- Partner-level debrief call
Engagements
Three ways to engage.
Indicative pricing. Final fees are confirmed in writing after a short scoping call and reflect company stage, data room volume, and turnaround.
Diligence Briefing
A fast, focused read for the partner meeting.
Fixed fee.
5 to 7 business days.
- Up to 2 founder or technical interviews
- Architecture and model review at depth-one
- Top risks and questions for deeper diligence
- Short written memo and 60-minute debrief
Full Diligence Report
Most requestedThe full technical and operational read on an AI investment.
Fixed fee, scoped per engagement.
2 to 3 weeks.
- Full document and data room review
- Founder, CTO, and engineering interviews
- Architecture, model, security, and cost analysis
- Team and execution assessment
- Written report with risk register
- Partner-level debrief call
Portfolio Advisory
An ongoing relationship across multiple deals and existing portfolio companies.
Priced on volume and scope.
Quarterly or annual retainer.
- Priority diligence engagements at preferred rates
- On-call for partner technical questions
- Portfolio company technical office hours
- Annual AI landscape briefing for the partnership
Rush engagements (under 5 business days) carry a premium. Engagements requiring travel, on-site sessions, or coordination with multiple co-investors are quoted separately.
How I work
The posture behind the report.
Independent.
No platform fees, no referral kickbacks, no incentive to soften the read.
Operator-grade.
Diligence written by someone who has shipped the systems being evaluated, not just modeled them in a spreadsheet.
Investor-ready.
Findings framed for an investment committee. Plain language, ranked risks, clear recommendations.
Confidential.
Standard NDAs. Conflict checks before scoping. Discreet handling of founder and company information.
Get an honest read before the wire.
Tell me the company, the round, and the timeline. I will respond with a scoping call inside one business day.