Customer Stories — How a German Private Equity Investor Uses Beauhurst with Claude to Surface Off-market Deals

The firm buys majority stakes in established, engineering-led businesses across Germany, often pursuing a buy-and-build strategy alongside its existing portfolio. It invests partner capital rather than a managed fund, and works hands-on with management after completion. Its targets sit between EUR 1m and EUR 50m of revenue, and are rarely on the market.

Sourcing succession-driven acquisitions

Mature, owner-run companies in defined industrial niches, filtered by size and financial health, where an ageing owner might be ready to step back.

Add-on targets for buy-and-build

Working outwards from an existing portfolio company to find businesses that fit alongside it.

Understanding ownership before an approach

Who owns a target, how much each shareholder holds, when they became involved and what else they are involved in.

For this German private equity investor, the problem is not evaluating companies; it’s finding them. Roughly two-thirds of the opportunities it sees arrive through M&A advisers, already in a process. The deals it actually wants are the other kind, and those do not arrive at all:

Without data, sourcing them is a manual process. The company’s incumbent tool for German company data couldn’t close that gap: it answered questions about companies you can already name and worked by name lookup rather than by criteria.

One of the firm’s Executive Directors said: “What I couldn’t find a way to do was to say: show me every business in the machinery industry in Germany below EUR 5m EBIT. As far as I could see, you mainly search by name. And if you aren’t completely sure how a company’s name is written, it can be very difficult to find the right one, because in Germany we have a lot of GmbHs with the same or very similar names.”

Beauhurst profiles every private company in Germany, classified and searchable by industry, size, financials and growth signals, with records built from official filings and checked by a research team. The feedback on this platform was clear:

What the investment lead valued most was being able to work outwards from a company he already owned. He explained, “The possibility to do a guided or focused search around a specific area of interest, particularly if you think in buy-and-build strategies. We have acquired X, and we would like to acquire Y, which fits with X. Starting to separate the good from the bad and narrowing down to a small portfolio of potential companies we could acquire is certainly valuable. The search function itself is great.”

He was clear about which firms gain most from that: “The classical private equity companies do have those buy-and-build strategies, for which it is super important to get all of the information on companies in the same ballpark of where you want to play. And because of that, they may value your platform much higher than others, because they wouldn’t get what they were looking for.”

He described one large European PE house running a self-funded buy-and-build programme across ten target sectors, with an external M&A adviser hired to find candidates: “Those guys would love this [Beauhurst] kind of search engine, where they can say: give me all automation companies between EUR 1m and 5m EBIT, always profitable, maximum two shareholders, and the majority holder older than 50. And I don’t think that example is a one-off. You see this with increasingly more PE firms building buy-and-build strategies around specific areas.”

Preparing for a first management workshop with a live target, the investment lead built the company fact pack himself using a general-purpose AI assistant on its most capable model.

“The first AI version was a perfectly laid-out document, but with 50% mistakes. It stopped at the first answer it found and never looked at what else was available. If it had gone one step further, it would have seen that the management and the shareholder structure had both changed.

“I took the most advanced model, which ate all of my credits for the month, because I wanted to go deep. And still it took me four hours, which I find incredibly stupid. I ask a very simple question: give me a detailed fact pack on that company, and this is the outline. And then I need four hours to check it.”

The errors were correctable. What they cost him was confidence in every line he had not checked personally: “I felt insecure with every line I read. It may be true, but maybe not. If I go to Beauhurst, whatever comes out is right. It’s not made up, and it’s not old data.”

Asked what Beauhurst’s strength was, he pointed to the research operation rather than any feature:

His conclusion is that while verified data beats manual research and general AI assistants; serious investors need to utilise both to succeed, concluding, “Verified data with AI enables ease of handling and ease of questioning, while keeping the outcome as trustworthy as possible. That is the combination that we were looking for.”