The Gap We Fill

PE portfolio monitoring is a well-established software category. Maestro, Chronograph, Allvue, Planr—they track KPIs, flag variances, and automate board reporting. They are the dashboard.

We are the engineer who inspects the engine. A VCP tracker can show a green status on an AI initiative. We determine whether that green status reflects an AI system that can scale to produce the EBITDA impact the value creation plan projects—or whether it is tracking a pilot that will never reach production.

Every deal deck now has an AI story. Most IT diligence firms can assess whether a company uses Python or has a data warehouse. Almost none can evaluate whether a company's AI forecasting model that "drives 15% of revenue" is actually production-grade, or whether the chatbot that "reduced support costs 40%" is hallucinating answers that create liability.

How We Compare

Alternative	What You Get Instead
Big 4 firms	Senior practitioner who does the work personally. Mid-market pricing. No junior analyst team that leaves after six weeks.
VCP tracking platforms	We evaluate whether the AI initiatives your tracker reports on can actually scale. You need the dashboard and someone who can tell you whether the engine works.
Generalist fractional CAIOs	Quantitative methodology: Monte Carlo financial modeling, seven-dimension evaluation, technical reliability testing. Not a strategy slide deck.
AI platform vendors	Vendor-neutral evaluation. 42% of companies scrapped most AI initiatives last year. The tool is not the hard part.
"The CTO can handle it"	Asking the CTO to evaluate their own AI system is like asking the chef to rate their own restaurant. Independent evaluation is standard in every other domain of due diligence.

Where We Fit in the PE Lifecycle

Pre-investment diligence: Evaluate AI maturity, data readiness, and technical debt of the target. Quantify realistic AI upside and flag hidden costs. Feed findings into deal models.

First 100 days: Evaluate which proposed AI initiatives can scale to produce projected EBITDA impact. Build financial models. Design governance guardrails. Define measurable milestones for the VCP.

Ongoing execution: Test whether AI systems are producing reliable output. Identify hallucination, drift, and integration failures. Evaluate vendor claims. Score organizational readiness to scale.

Pre-exit: Validate that AI capabilities attributed to value creation are actually working. Prepare technical diligence documentation for prospective buyers.