Search Funded: The ETA Podcast
From Fired Searcher to $50M in Deals in One Year | Kevin Hong, Caprae Capital
Why It Matters
The episode sheds light on the hidden risks and structural flaws in the fast‑growing search fund industry, offering valuable lessons for aspiring acquisition entrepreneurs and investors. By exposing transparency gaps and sharing practical strategies for deal sourcing and governance, Kevin’s story helps listeners navigate the complexities of building generational wealth through acquisitions in a rapidly changing market.
Key Takeaways
- •Fired after AI-driven sales drop and board conflict.
- •Fragmented 22‑investor cap table to avoid dismissal.
- •Grew data‑center services 40% YoY before market slowdown.
- •Closed $50M lower‑middle‑market deals via CapRate Capital.
- •Launched Sasquatch Leads to help searchers generate acquisition leads.
Pulse Analysis
Kevin Hong entered the search‑fund world after a series of founder exits, targeting a data‑center services company that he grew 40% year‑over‑year. His early success was driven by a hands‑on sales pitch that positioned him as the missing co‑founder for a retiring owner. However, the rapid rise of AI‑driven GPU demand created an energy shortage, slashing the firm’s sales by half and igniting board politics that ultimately led to his termination. Hong’s experience underscores how macro‑technology shifts can destabilize even high‑growth acquisitions and why alignment with sellers and boards is critical for long‑term stewardship.
After the fallout, Hong leveraged his network to launch CapRate Capital, closing more than $50 million in lower‑middle‑market private‑equity transactions since 2025. He also founded Sasquatch Leads, a platform that supplies acquisition entrepreneurs with vetted deal pipelines, addressing a chronic lead‑generation bottleneck in the search‑fund ecosystem. Throughout the conversation, Hong critiques the industry’s rapid expansion, noting that mentorship has become diluted as larger funds crowd the space, leaving many MBA‑trained searchers without seasoned guidance. His transparent survey of fired searchers adds a rare data point for investors seeking to refine selection criteria.
The broader lesson for acquisition entrepreneurs is twofold: protect your position with a diversified cap table—Hong fragmented ownership across 22 investors, limiting any single stakeholder’s power to fire him—and stay agile amid technological disruptions. His 500‑page industry playbook on data‑center hardware, energy consumption, and AI trends illustrates the depth of research needed to anticipate market pivots. By openly sharing his failures and successes, Hong provides a roadmap for future searchers to balance aggressive growth with governance safeguards, ultimately enhancing the credibility and resilience of the acquisition‑entrepreneur model.
Episode Description
Kevin Hong is a former searcher who was fired from the company he acquired and is now the founder of Caprae Capital, a tech-enabled lower middle market investment platform behind SaaSquatch Leads, Search as a Service, and a growing portfolio of businesses.
After years as an entrepreneur, Kevin turned to search as a more de-risked path to ownership. But his experience running a data center services business turned into a battle over governance, board control, seller alignment, and strategy. Instead of disappearing after being removed, he went public, interviewed other terminated searchers, and began publishing investor rankings and operator feedback in an effort to bring more transparency to the search ecosystem.
In this episode, Kevin discusses:
Why search appealed to him, how he approached his acquisition, and what ultimately led to his firing
What he thinks traditional search gets wrong about governance, boards, and operator-investor alignment
How Caprae works, what he means by “rewriting LMM PE from the source code,” and why he believes founder-led, tech-enabled models can outperform the traditional playbook
What he learned from surveying terminated searchers and why he believes the industry needs more transparency as it scales
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