Transforming the way private businesses are bought and sold

I have spent my career on both sides of how private businesses are valued, financed, and sold.

I grew up around owner-operated businesses. I saw how much of an owner's identity, family security, and life's work could be concentrated in a single company.

Later, working around corporate development and large-scale transactions, I saw the other side of the market. Large institutions had teams of analysts, sophisticated models, market data, scenario analysis, and experienced advisors helping them determine what a business was worth. Most private-business owners had none of that.

When the time came to consider a sale, succession, acquisition, or capital raise, many were expected to make one of the most important financial decisions of their lives using fragmented spreadsheets, broad industry multiples, and opinions from people sitting on the other side of the negotiation.

I built Value Alpha to close that gap, for both sides of the table.

Value Alpha combines institutional valuation methods, private-market intelligence, and company-specific analysis to help owners and buyers understand three things:

1. 1. What is the business worth today?
2. 2. What is increasing or reducing that value?
3. 3. What should happen next?

This is not about replacing judgment with an algorithm. It is about giving better information to the people making the judgment, on either side of a deal. Here is exactly where the AI works, and where it never does.

Because no one pricing a private business should have to rely on a generic calculator or the other side's opinion. They deserve a defensible view of value, a practical path to improve it, and greater control over what happens next.

You can see the price of a publicly traded company every second. A private company's price is, well, private: it is set by whoever holds it.

The owner prices their company. The buyer prices the target. Funds mark their own portfolios. Even inside one company, the tax return, the bookkeeping and the owner's forecast can tell three different stories.

At the top of the market, a deal gets a room of analysts and weeks of diligence. In the middle market it gets an asking price, a multiple and a rule of thumb. Everyone prices their own book: the same math, and a completely different standard of proof.

Price is not value. Value is in the numbers, in the risk, in the growth, and sometimes in something the next owner can see that everyone else missed. That is where the alpha is. The number that matters is the one you can defend: the one you offer, the one you accept, or the one that tells you to walk away.

AI is changing this work. But ask a general-purpose AI what a private business is worth and you get a number with nothing behind it: no method named, no source traced, no scenarios. In private company valuation, a number you cannot defend is not an answer.

I built Value Alpha to hold every private deal to one valuation standard.

AI reads the documents, organises the financials and finds what is missing. Our financial models, built for 43 industries, do the math. Every figure traces back to your documents, every method is named, and every change recalculates the range and its scenarios.

Then the whole deal lives in one place. The Deal Book tracks every company from first look to close. The data room holds the documents. The portfolio keeps what you own. And your team works on the same numbers.

When an owner is ready to sell, the Value Alpha Marketplace keeps them in control. They list anonymously, only approved buyers get in, under NDA, and the owner decides who learns about the business before we make the introduction.

The top of the market has always held its numbers to a standard. Now every private deal can.

Know the value. Find the alpha.