How to vet the company that wants to buy yours

A checklist written by acquirers tells you what they want you to ask. It does not tell you what they hope you never think to look for. We are a serial acquirer ourselves, and what follows is the playbook we would want a seller to use on us, because the founders who investigate us hardest tend to become the happiest post-acquisition. If another buyer hides the signals described below, that silence should worry you more than anything they put in a pitch deck.

Why this matters more in 2026 than ever before

The SaaS M&A market has entered a strange new era. The S&P North American software index recorded its sharpest monthly decline since 2008 in January. Private equity firms that loaded up on software acquisitions during the 2021–2022 boom are now sitting on roughly $47 billion in distressed tech debt, and some of the biggest take-private deals in SaaS history have seen up to 30% workforce reductions post-close. For founders of smaller, bootstrapped businesses, this creates a specific risk: the buyers approaching you may be under financial pressure themselves. The questions you ask a buyer today are not just about fit. They are about whether your deferred payments, your earnout, and your team survive the buyer’s own financial weather.

Demand the failures, not just the highlights

Every acquirer will tell you about the deal where revenue tripled. That is marketing, not evidence. What you need is the full portfolio picture: how many companies acquired, how many still operate under their original brand, how many founding teams are still involved, and what happened to the ones that did not work out.

A buyer who has sold off or shut down an acquisition is not automatically a bad partner. Every portfolio has misses. But a buyer who refuses to discuss them is either hiding bad outcomes or does not believe you deserve to know. saas.group has publicly discussed divesting Sniply after it underperformed and acknowledged that buying businesses out of insolvency turned out to be “a different beast.” As Schumacher put it: “We also had businesses that tanked. So far it was just one out of 25. So knock on wood, but that’s okay because we have a portfolio approach.” These are not comfortable admissions. They are exactly the kind of information that should give a prospective seller more confidence, not less. Ask your buyer the same question. If the answer is a polished non-answer, keep looking.

What happens to your people and your product

This is the question founders care about most and get the least honest answers on. When a buyer tells you “we value the team,” that is a sentence, not a commitment. Ask instead: how many people worked at your last three acquisitions at the time of purchase, and how many work there now? Do teams keep their own leadership and roadmap? Are there roles you typically eliminate? Some buyers centralise finance, HR, or DevOps. That is not sinister. What matters is whether they tell you before close or let you find out three months later.

Understand the economics behind the answer. 60–80% of a SaaS company’s cost base is labour, split across G&A, R&D, and sales and marketing, and that is where the math gets done. PE acquirers chasing 40%+ EBITDA margins will typically centralise finance, HR, and DevOps into shared services across the portfolio; strategics will look for overlap with their existing functions. AI accelerates the compression. Agentic tools are becoming the standard way of operating across the entire business, not just engineering but support, finance, and HR, and any serious buyer is underwriting that productivity uplift into their model whether they tell you or not. Total retention numbers can hide the pattern; the roles that get cut are the signal.

Schumacher has described his philosophy in terms of superpowers and blind spots: “Every company, every founder is great at something. Everybody has a superpower… but then also everybody has blind spots and weaknesses.” The premise of a good acquisition is that the buyer fills the gaps without bulldozing the strengths. If a buyer cannot name the specific gaps they address, they may not have a real operating model. They may just have capital and a term sheet. Apply the same scrutiny to product continuity: look at their portfolio page, check whether acquired products show recent investment, and talk to founders who sold two to three years ago. The first year often looks great. Year three is the test.

Their AI thesis is a proxy for how they think about everything

In 2026, every acquirer will say they care about AI. That is meaningless unless they can show you what it looks like inside their portfolio. Venture capital firms have started openly rejecting AI SaaS pitches that lack proprietary data moats or real workflow integration. The same logic applies in M&A: if a buyer is acquiring your product purely for its current revenue without a thesis on how AI changes the competitive landscape around it, they are buying a melting ice cube and hoping it melts slowly. Schumacher described the lens saas.group uses: “Does it have proprietary data sets? Is it API ready? Could it connect into new things like MCPs as part of the AI world?” He also noted that API-based businesses may be more resilient to disruption than UI-heavy tools, since “what is disrupted is not the actual underlying stuff, it’s the user interface.” Specificity is the antidote to pitch deck hand-waving.

But the scrutiny runs both ways. A sophisticated buyer will probe your AI defensibility before they underwrite your growth. They will want to know which of your moats hold up in an agentic world: whether you have proprietary data the frontier models have not trained on, whether you operate in a compliance- or accuracy-sensitive domain where generalist models cannot yet compete, and whether your customer relationships provide context no model can replicate. They will also ask whether you are rebuilding your product from first principles given today’s AI capabilities, or simply automating yesterday’s workflows. Bolting AI onto existing processes is a car engine on a horse carriage: a powerful technology forced into a structural framework built for a different era. The question worth asking yourself before the buyer asks it: if you were building this product today, knowing what modern AI can do autonomously, how would you solve the problem? That reframe protects terminal multiples. Automating yesterday’s workflows is where valuations quietly compress.

Then flip it. Ask the buyer for proof points of their own: where in your portfolio has an AI initiative moved a real business metric, whether retention, expansion, or margin, and what did it take to get there? How will you help us close the gaps you just identified? A buyer who can point to specific case studies and name the operators who ran them is bringing real leverage. One who can only talk about access to models or a shared subscription is offering commodity infrastructure dressed up as a thesis.

Follow the money behind the offer

A founder looking at two offers will naturally gravitate toward the higher number. But the structure around that number is where the real story lives. An earnout tied to aggressive growth targets in a market where AI is reshaping buyer behaviour is a very different proposition from an earnout tied to retention metrics the founder already controls. Ask what percentage of the purchase price is guaranteed at close, what happens if the buyer changes product direction in a way that makes targets unachievable, and whether previous founders hit their earnouts. If the buyer will not share that data, that tells you something.

Around 60% of SaaS deals now include earnouts, and the smarter acquirers are quietly shifting toward retention bonuses instead, acknowledging that founders cannot control integration delays, roadmap changes, or post-close go-to-market decisions that drive the metrics they are being measured on. Ask the buyer directly: what percentage of your past sellers hit their earnout targets, and are those targets tied to metrics the founder actually controls? If they cannot answer with specifics, assume the earnout is a discount mechanism, not a real payment.

Then go deeper: who funds the acquisitions? Cash flow, investors, or debt? With a record $25 billion of software-sector leveraged loans now trading below the distress threshold, a buyer’s balance sheet is not a rude question. It is a survival question. Schumacher has spoken about deal flexibility directly: “We have earnouts so we can have a participation for the founder to continue. We also love if founders want to stay around for a while, but it’s all optional.” The word “optional” is doing important work there. Some buyers structure deals so the founder effectively cannot leave for years. Others make the transition genuinely flexible. The difference shapes your entire post-sale life.

Most software buyers carry debt. Historically, SaaS companies have not been GAAP-profitable enough for traditional bank lending, so the private credit market stepped in to finance leveraged buyouts and bolt-on acquisitions against recurring revenue. With private credit now contracting, leveraged buyers will find refinancing harder in the coming years, and that risk lands squarely on you if you are holding a seller note or earnout. The practical question: is this buyer funding the deal from cash flow, or from leverage? Ask whether they have cash on the balance sheet or an undrawn committed credit facility, or whether the offer carries finance contingencies that could open the door to a retrade in the eleventh hour of diligence. A leveraged buyer with a back-loaded earnout is the structural pattern to watch: it concentrates risk on the side of the table that has the least control.

Ask whether your pricing model survives their thesis

Buyers are now stress-testing whether per-seat pricing survives a world where their own customers are using AI to reduce headcount. If your ARR grows because your customers’ teams grow, that assumption is under active pressure, and a sophisticated buyer will price that risk into the offer. Be ready to answer it before they ask: how does your pricing model hold up if customer headcount flattens or declines? What is the path to usage-based, outcome-based, or workflow-based monetisation? Then flip it: how are you thinking about pricing model durability across your portfolio, and where have you helped companies transition? A buyer who has navigated this with other targets is bringing genuine operational value. One who has not thought about it is underwriting a revenue line that may not exist in three years, and that gap will show up somewhere, usually in the earnout.

Buyer transparency scorecard

Use this during conversations with any prospective acquirer. A transparent buyer will answer every row without hesitation.

Your business deserves a real investigation

Every acquirer in 2026 calls themselves founder-friendly. The term has become table stakes, not a differentiator. So stop evaluating the label and start evaluating the evidence: published case studies with real outcomes, public acknowledgments of failures, and founders from previous acquisitions willing to talk to you, both the ones who stayed and the ones who left. You built something from nothing. Evaluating a buyer is not a box-ticking exercise. It is closer to evaluating a co-founder. You need to understand not just what they say, but how they behave when things go wrong.

If a buyer is doing this well, they should welcome your scrutiny. They should open their portfolio to your questions, share their failures alongside their wins, and give you the space to decide on your terms. And if they do not? That tells you everything you need to know.