Work

Three ways to work together.

Every engagement starts with a discovery call. No pitch, no obligation — just an honest conversation about whether there is a fit and what the right structure looks like.

AI due diligence and technical due diligence for venture capital and private equity investors — delivered in 10 business days

Due Diligence

AI Due Diligence

You are 30 days from closing. The AI story is compelling. The team is strong. But you do not have the technical depth to stress-test the infrastructure, the pricing model, or the product-market fit claims. That is what this engagement is for.

Timeline10 business days

Venture capital firms · Private equity firms · Family offices

Book a discovery call →
01
AI infrastructure assessment
Model architecture, orchestration, vendor dependencies, deployment readiness, and hidden operational risk.
02
Pricing architecture review
Usage economics, gross margin logic, cost-to-serve, and whether pricing supports a durable business.
03
Product-market fit analysis
Retention signals, expansion revenue patterns, ICP clarity, and whether PMF is measured or narrative.
04
Competitive moat assessment
Data advantages, switching costs, and whether the AI layer is genuinely defensible or easily replicated.
05
Executive report + IC briefing
Written report structured for investment committee presentation, with a live briefing session.

Portfolio company AI strategy and ongoing advisory for VC and PE portfolio companies

Portfolio Advisory

AI Strategy & Portfolio Advisory

Your portfolio company is navigating an AI transition — rebuilding the product, repricing the offering, or pitching AI infrastructure to the board. They need an operator who has done this before. Not a consultant. An advisor with skin in the game.

TimelineMonthly retainer

Portfolio companies · Founders · Leadership teams

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01
AI roadmap prioritisation
What to build, what to buy, and what to deprioritise given the current stage and resources.
02
Pricing model design
Packaging, usage tiers, gross margin targets, and monetisation architecture.
03
Technical positioning
How to communicate AI infrastructure quality to investors and boards without overstating or understating.
04
Build-vs-buy analysis
Independent assessment of whether to build proprietary AI infrastructure or leverage existing models.
05
Ongoing advisory access
Monthly cadence with async support between sessions.

AI due diligence frameworks and investor education for venture capital and private equity investment teams

Investor Education

Investor Briefings & Frameworks

Your investment team evaluates AI companies every week but lacks a consistent framework for assessing technical quality, infrastructure risk, and commercial durability. This engagement builds that capability internally.

TimelineCustom format

Investment teams · GPs · Analysts

Book a discovery call →
01
AI due diligence framework
A repeatable evaluation framework your team can apply to every AI deal, customised to your fund's sector focus.
02
Technical literacy briefing
Practical education on AI infrastructure, model architecture, and the language AI founders use — without the hype.
03
Pricing and unit economics toolkit
How to read AI business models, assess gross margin quality, and identify pricing risk before it compounds.
04
Red flag pattern library
The 10 most common AI investment red flags — disguised as strengths — and how to find them in due diligence.
05
Live Q&A session
A working session with the investment team applying the frameworks to a live or hypothetical deal.

Ready to talk?

Discovery call takes 30 minutes. No obligation.