Summary
Learn how buying a business is harder than starting one due to a structural infrastructure gap, why search funders face disproportionate due diligence and execution challenges in the “missing middle,” and how AI tools can partially close the gap between solo buyers and institutional-grade analysis.
In this article
- The Ecosystem Was Built for Founders, Not Buyers
- Starting vs Buying: What the System Actually Provides
- Where the Opportunity Actually Lives
- What This Means for Due Diligence Specifically
- What the Next Decade Looks Like for Search Funders
- How Kudra Fits Into This
The Ecosystem Was Built for Founders, Not Buyers
If you want to start a business in the United States, the support infrastructure is extraordinary. Incubators. Accelerators. University entrepreneurship programmes. Angel networks. Seed funds. Government grants. A decades-long cultural narrative that celebrates the founder and romanticises the startup.
If you want to buy one, you are largely on your own.
There is no acquisition equivalent of Y Combinator. No standardised curriculum that teaches deal sourcing, due diligence, and post-close operation the way business schools teach product development and go-to-market strategy. No centralised registry that connects motivated buyers with retiring sellers. No standardised financing product built for sub-$10 million transactions the way a 30-year mortgage is built for home purchases.
The result, as a recent McKinsey Institute for Economic Mobility report makes plain, is that buying a business is genuinely harder than starting one because the system surrounding the transaction is so much less developed.
Starting vs Buying: What the System Actually Provides
The gap between these two paths becomes stark when you map the infrastructure available to each side.
| Starting a Business | Buying a Business |
|---|---|
| University incubators and accelerators | A handful of MBA-level ETA programmes |
| Seed funding and angel networks | Fragmented broker networks, no standards |
| Standardised pitch processes | No central registry of opportunities |
| Government grants and startup loans | SBA 7(a) loans: slow and equity-heavy |
| Decades of cultural celebration | Almost no post-close advisory support |
| Mentorship networks built at scale | Due diligence largely self-taught |
| Post-launch accelerator aftercare | Opaque, informal deal sourcing |
This asymmetry has a direct consequence for search funders. The buyers who succeed in this market are not necessarily the ones with the best instincts or the deepest networks. They are the ones who compensate for the infrastructure gap with better tools, better preparation, and a more disciplined process than the market has come to expect from buyers at this deal size.
Where the Opportunity Actually Lives
The businesses most affected by this infrastructure gap are not the ones that attract private equity. Those deals (firms valued above $25 million with professional management structures and audited accounts) have a relatively functional market around them. Institutional buyers know how to find them. Professional advisers know how to run a process. Financing is structured and available.
The real opportunity sits in what the McKinsey research calls the “missing middle.” Firms valued between roughly $500,000 and $25 million. Too large for community succession models. Too small for institutional capital. And almost entirely dependent on independent buyers (search funders, self-funded searchers, and entrepreneurial operators) who face all of the systemic frictions without any of the institutional support.
These businesses span every sector of the local economy. Regional manufacturers. Construction firms. Professional service practices. Healthcare providers. B2B service businesses with stable customer bases and ten or fifteen years of operating history. They are exactly the kind of business that makes a compelling acquisition and exactly the kind that the market consistently fails to transfer successfully.
What This Means for Due Diligence Specifically
The infrastructure gap shows up most acutely in due diligence. And this is where the implications for search funders are most direct.
When an institutional buyer evaluates a business, they bring a team. Investment professionals, operating partners, financial analysts, legal advisers, commercial due diligence consultants. The cost of that team on a single deal can run to seven figures. The process is thorough by design because the buyer has the resources to make it so.
When a search funder evaluates a business in the missing middle, they are often doing it largely alone. The deal is too small to justify institutional-level advisory spend. The timeline is compressed. The seller controls the information flow. And the buyer is simultaneously managing investor relationships, negotiating terms, and trying to understand a business they’ve never operated all at the same time.
In this context, the quality of due diligence is not just an analytical question. It is a resource question. How do you get to the depth of analysis the deal requires, in the time available, without the team that institutional buyers take for granted?
| Due diligence dimension | Institutional buyer | Search funder without AI | Search funder with Kudra |
|---|---|---|---|
| Financial analysis | Dedicated analyst team, weeks of modelling | Solo, nights and weekends, high error risk | AI-assisted, patterns surfaced automatically |
| Document review | Legal and commercial teams review in parallel | Sequential, easy to miss cross-document issues | Simultaneous cross-referencing across all documents |
| Red flag identification | Pattern recognition built from hundreds of deals | Limited to personal experience and checklists | AI applies pattern recognition at institutional depth |
| Market context | Commercial due diligence consultants | Self-researched, often superficial under time pressure | Synthesised market context in hours not days |
| Investor reporting | Dedicated team produces structured output | Manual, time-consuming, often under-resourced | Draft output generated from analysis automatically |
The gap between what institutional buyers can do and what solo search funders can do has always existed. What’s changed is that AI makes it closeable not by replacing the judgement of an experienced buyer, but by giving a solo operator access to analytical depth that previously required a team.
What the Next Decade Looks Like for Search Funders
The McKinsey research is clear on one point that should matter enormously to anyone in the search fund world: supply is about to massively outpace demand at the deal sizes that search funders target.
Six million businesses coming to market. Institutional buyers constrained to the upper end. Community and employee ownership models too limited in scale to absorb the volume. That leaves independent buyers ( search funders, self-funded searchers, entrepreneurial operators ) as the critical category for the missing middle. And that category is currently structurally undersupported, undertrained, and underequipped relative to the volume of opportunity heading their way.
The buyers who invest now in building a more disciplined, more thorough, better-equipped acquisition process are not just better positioned for the next deal. They are building the capability to participate in what the research describes as one of the largest near-term economic mobility opportunities in the US economy.
That is not a small thing. And it does not require institutional resources to access. It requires the right tools, applied with rigour, to a process that the market has consistently failed to support, until now.
How Kudra Fits Into This
Kudra exists because the infrastructure gap in private acquisition due diligence is real, consequential, and ( with the right AI copilot ) closeable.
It does not give search funders a team of analysts. It does something more precise: it applies analytical depth to the specific dimensions of private acquisition due diligence where solo buyers are most exposed — financial pattern recognition, cross-document inconsistency detection, operational dependency mapping, market context synthesis — and delivers that analysis in a form that a single buyer can act on, in the time they actually have.
The $5 trillion wave of ownership transfers is coming regardless of whether the infrastructure is ready for it. The search funders who close more of those deals will be the ones who arrived better prepared. Kudra is how you get there.
References
- https://hbr.org/2021/05/value-creation-in-private-equity
- https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/the-value-creation-principle
- https://www.bain.com/insights/value-creation/
- https://www.pwc.com/gx/en/services/deals/value-creation.html
- https://www2.deloitte.com/us/en/pages/mergers-and-acquisitions/articles/value-creation-in-ma.html
- https://www.aicpa-cima.com/resources/article/what-is-due-diligence
- https://www.investopedia.com/terms/d/due-diligence.asp
- https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/the-ownership-transition-opportunity
