AI technical due diligence
We help VC, PE, and family-office investment teams examine the technical claims behind an AI business. We connect product evidence, architecture, delivery effort, and operating economics to the questions you need answered.
We work with teams across the UK, Europe, and Australia.
When to bring us in
- You need to distinguish a working product from a demonstration before an investment decision.
- Model dependency, data access, deployment work, or operating costs could change the investment case.
- You need a focused technical review within a defined diligence window.
Who does the work
A partner leads the assessment with engineering and operational input. The deal team sets the questions; the target's technical owners provide the evidence and context.
Meet our partnersWhat the engagement delivers
01
A decision-led scope
We agree the investment questions, information request, access boundaries, and reporting deadline with your deal team.
02
An evidence review
We examine architecture, evaluations, representative outputs, integrations, delivery requirements, and technical ownership.
03
A risk and dependency record
We separate observed findings from management assertions and missing evidence. We identify provider, data, reliability, and scaling dependencies.
04
A decision briefing
We explain the findings, unanswered questions, and follow-up work in a written assessment and a discussion with your team.
Timing and budget
We work backwards from your investment deadline and agree what the available access can establish. Missing evidence is recorded explicitly rather than treated as a clean finding.
Daily rates start at €1,000 EUR per consultant for a full day.
Daily rates start at £850 GBP per consultant for a full day.
Daily rates start at A$1,600 AUD per consultant for a full day.
Rates depend on the engagement and current exchange rates. Necessary project expenses add up to 10% of the daily rate.
What to bring to the first call
Bring the investment thesis, decision deadline, available materials, and your principal technical concerns. Arrange target consent and authorised access before any review.
Technical findings support your investment decision. Legal opinions, financial audits, penetration testing, and regulatory certification need separately agreed specialist work. Any conflict of interest is addressed before the engagement.
Read how we approach the work
These guides explain the method and the evidence to look for.
10 Technical Questions to Ask Before Investing in an AI Startup
Ten technical due diligence questions for AI startup investors, with the evidence to request on product quality, data rights, security, model risk, costs, and adoption.
Is an AI Startup Defensible Without Owning a Model?
A venture investor's guide to testing an AI startup's workflow depth, proprietary context, distribution, switching costs, and exposure to fast followers.
Is the AI Startup Solving a Budgeted Problem or Selling a Demo?
A commercial diligence guide for AI startups: test current customer spend, workarounds, buying authority, paid pilots, integration cost, and renewal evidence.
Discuss the work with a partner.
The introductory call is free. We'll discuss the problem, the decision you need to make, and whether an engagement fits.