The use of AI in finding a search fund target

Search funds offer exciting opportunities for aspiring entrepreneurs to acquire and manage established businesses. Also known as entrepreneurship through acquisition, the term ‘search fund’ refers to the initial stage where an entrepreneur (or “searcher”) raises capital to identify and purchase a company to lead. This strategy reduces many of the risks associated with starting a business from scratch.

There are three main models for entrepreneurship through acquisition:

• Traditional: originating at Stanford Graduate School of Business in 1984, the traditional model involves raising search capital from a group of investors to provide financial support during the phase of identifying acquisition targets. Beyond funding, investors provide advice, offering guidance and access to networks.
• Self-funded: the entrepreneur finances the search independently, investing their own time and resources. This approach offers more flexibility in structuring ownership and shaping the eventual acquisition.
• Single-sponsor: backed by a single investor, often a private equity fund or family office, the searcher’s costs are typically covered during the process. Once a target is identified, the searcher co-invests alongside the sponsor.

Historically, the results have been impressive, with search funds typically generating a 35% IRR and a 4.5x return on investment. Deals have been completed across sectors ranging from software to healthcare.

Identifying a Target

Traditionally, the challenge has been in identifying the right acquisition target. Searchers generally focus on steady, profitable companies valued anywhere between £2 million and £20 million, often with recurring revenues and strong margins. Searchers may also focus on owners approaching retirement. Finding these opportunities has meant spending months combing through industry databases, visiting trade shows and making countless cold calls.

How AI is Changing the Process

AI tools are becoming increasingly capable of analysing extensive company databases and can now assess not only basic industry information, but detailed financial records, market performance, and digital footprints of both companies and individuals. This can significantly accelerate the deal origination process by enabling customised searches based on criteria such as sector, location, revenue and profit margins to identify high-potential opportunities.

Once potential acquisition targets are identified, AI tools can further support in the outreach process, by assisting in drafting personalised emails to business owners, scheduling follow-ups and even identifying mutual contacts who could facilitate introductions. This enables a searcher to maintain engagement with hundreds of deal opportunities simultaneously, something that would otherwise require significant time and resources.

In summary, AI tools can help searchers with the following:

• Scanning large company databases;
• Building and applying custom search criteria frameworks;
• Identifying signals of companies likely to sell; and
• Outreach to companies.

Existing Tools

Many well-established company databases are now integrating AI tools within their platforms. The most common tools incorporate AI and machine learning to help users identify and evaluate potential acquisition targets more efficiently. Natural language processing (“NLP”) is increasingly being applied to extract and analyse company information that might otherwise be difficult to capture. In addition, some sales platforms have combined sales intelligence with AI-powered filters to flag indicators of company growth or sale readiness.

One illustration of this trend is Dealsuite, which in 2024 introduced an AI-powered search function designed to help users identify more relevant matches with greater speed and accuracy. Dealsuite has also established a strategic partnership with Cyndx, an AI-driven platform that enhances M&A sourcing capabilities. Using NLP and machine learning, Cyndx enables off-market company discovery by analysing a large volume of datasets to identify high-potential opportunities. Together, these developments have positioned Dealsuite as a powerful tool for deal origination.

PitchBook, a leading provider of private market data, has likewise integrated AI and machine learning to improve the efficiency of analysing its datasets. Among its recent developments are AI-generated company profile summaries, which highlight key details such as executive teams, investors, and financing history, helping users to assess opportunities more quickly. Grata, meanwhile, applies NLP to analyse company websites and identify niche, founder-led businesses that align with specific investment criteria.

Looking for support on your search fund journey? Speak to one of our advisers below or contact hello@geraldedelman.com.