For venture capital & private equity
Know whether a target's AI is real before you invest. Turn findings into a 100-day plan. Create value during the hold, integrate add-ons, and prepare for a sale that holds up to the buyer's diligence.
Led by an operator who builds AI and has led integrations and turnarounds.
“12 is the new 5.”
Bain & Company estimates that typical buyout deals now need 10–12% annual growth in earnings before interest, taxes, depreciation, and amortization (EBITDA) to reach a 2.5x return over five years, up from about 5%. More of the return has to come from operating improvement. Bain & Company press release, February 2026
“AI washing” is on regulators' radar.
In 2024 the US Securities and Exchange Commission (SEC) settled charges against two investment advisers over false claims about their use of AI. Overstated AI is a diligence question, not just a marketing one. SEC press release 2024-36
01 · Pre-acquisition
The risk: Many targets now lead with AI. Some of it is proprietary, some is a thin wrapper on someone else's model, and some doesn't work on the company's own data.
3–4 weeks · fixed fee
An independent technical read on a target's AI claims, from someone who builds these systems.
You get
5–10 days · fixed fee
A fast read on the biggest AI risks in a target, for early screening or a tight deal timeline.
You get
For growth-stage and lower-middle-market targets: architecture, technical debt, product roadmap, and whether the team can deliver it.
You get
Where AI and operations could move EBITDA after close, sized before you commit.
You get
02 · First 100 days
The risk: The value case is set in diligence and won or lost in the first months, sometimes while the company is short a key leader.
Diligence findings turned into an executable plan tied to the investment thesis, with owners and numbers.
You get
1–3 days a week · 6–12 months
If the company lacks a leader, the same senior operator can take a fractional chief AI, product, operating, or executive officer seat part time while you hire.
You get
The metrics, reviews, and accountability that let the board see whether the plan is working.
You get
03 · Hold period
The risk: With longer holds and a higher bar for returns, operating improvement carries more of the result.
Use cases chosen for EBITDA impact, taken into production, and tracked against a business case.
You get
4–8 weeks · fixed fee
The AI Value Diagnostic run across several holdings to show where AI can move value first.
You get
For portfolio companies whose delivery is slowing growth: backlog, quality gates, and release discipline.
You get
Customized sessions for executives and managers on using, governing, and funding AI well.
You get
04 · Mergers and add-ons
The risk: Buy-and-build theses depend on integration that actually happens: one operating model, one set of systems, and synergies someone owns.
A repeatable way to fold add-ons into the platform, and an operator to lead it.
You get
Bringing overlapping products, tools, and data onto one platform, with a migration plan built around service continuity.
You get
A baseline and a monthly record of which synergies are realized, so the story is ready when a buyer asks.
You get
Finding what is shared in practice, not just on paper, before transition service agreements are signed.
You get
05 · Pre-sale and exit readiness
The risk: Buyers scrutinize technology and AI claims. Problems found late can reduce the price or stall the deal.
Fixed fee
A buy-side-style review of technology, product, and AI, done early enough to fix what it finds.
You get
Make AI claims testable, measure what they deliver, and document the evaluation and governance behind them for the data room.
You get
Operating metrics that reconcile to the financials, so the numbers are ready for a buyer's diligence.
You get
How to engage
For your deal team, investment committee, or portfolio board. An in-depth look at the company first, then advice on AI strategy, risk, and approach.
Senior help inside the team, or in a fractional executive seat, toward agreed results, then a handoff with training and coaching.
AI due diligence, portfolio AI readiness, and exit-readiness reviews, each with a defined scope and deliverable.
Supporting evidence
Unified three merged healthcare IT service providers serving 250+ clients into one operating company in nine months. Revenue grew 12% and customer satisfaction rose from 6.5 to 9.2 (Sunset Technologies).
Eliminated 90% of technical debt and cut production defects 85% in five months on an AI identity-verification platform serving major US banks, retaining $15M in annual recurring revenue (AuthenticID, 2022–2023).
Designed and coded an autonomous agent platform with retrieval-augmented generation (RAG), a task-level evaluation harness, and human review (Paragon Energy AI).
Structured multi-entity capital stacks for qualified small business stock (QSBS) eligibility and energy tax-credit transferability.
Get a first view of what to examine, and whether the AI is the thesis or the risk. A non-disclosure agreement (NDA) can be signed before you share anything confidential.