Beyond M&A

    For investors and buyers

    You're buying into a sector nobody in the room can judge.

    Most investors call us at one of two moments. Either there's a target in a space where nobody on the deal team can judge the technology, or they've already been burnt: a portco where the technology bill arrived after close and nobody saw it coming.

    We usually start with technology due diligence and stay on as advisers once the opinion is in. Beyond the technology we cover the people side too: HR and P&C, organisational design and management training, which is where most deals actually come unstuck.

    Book an introduction Watch the five films

    Two situations

    The deal you can't judge, or the tech you already own.

    Before the deal

    Nobody on the deal team reads this sector.

    The management team sounds credible, the demo works, and no one can tell you what it costs to run at three times the volume. Right now that has an extra edge, because nobody can confidently price AI in a deal. You get an opinion your IC can price, not a risk list with no view in it.

    After the deal

    You've been burnt before, and you'd rather not repeat it.

    Tech-enabled services businesses bought without formal diligence. Workarounds holding the platform together. A roadmap nobody has costed. We sweep the portfolio the same way we'd run a diligence: what's being spent, whether it's sensible, and what has to be true for a clean exit in a few years.

    Read how that played out

    We take ten diligences a month. Quality over quantity. In a decade of them we have issued two fully green reports, and the average unbudgeted technology spend we uncover is around £250k, with a range from £20k to several million.

    The difference in practice

    What usually happens, and what we do.

    We do not name other firms. This is the pattern investors describe to us, set against how we run an engagement.

    Who runs the work

    A partner sells it, an analyst delivers it, and you meet neither again.

    The people who write the report are the people who ran technology functions, and they stay on the deal.

    What the report contains

    A risk list, a maturity score and a set of recommendations with no price on them.

    An opinion the investment committee can price. Every finding carries a number, an owner and a timing.

    Scope

    A blanket review sized to the provider's template, not the deal.

    Twelve scope areas, sized to the deal. We will tell you when a smaller piece of work is the right answer.

    AI

    A pitch about what AI could do, or a section that describes the AI and stops short of judging it.

    Judgement on whether the position holds, priced, applied to an estate we then have to integrate and run.

    Integration

    Integration is somebody else's workstream, staffed by people who never read the report.

    A full Post-Merger Integration practice: Day 1 readiness, transitional service exit, consolidation, the savings you priced delivered, and the people work underneath it.

    After the report lands

    The advisers leave at stage two and the plan becomes someone else's problem.

    The plan in the report, delivered by the people who wrote it, through integration to exit.

    Capacity

    Volume. More assessments, more associates, thinner attention on yours.

    Ten diligences a month. Quality over quantity, and a named person accountable for the verdict.

    What we heard when we asked

    Investors told us what goes wrong.

    We called around 200 investors and asked what they want from IT due diligence and what they actually get. These are their words, anonymised. They are interview notes, not client testimonials, and the complaints have not aged.

    The key issue we've found with DD providers has been a blanket approach rather than a focussed and pragmatic approach. The cost outweigh the benefits of this. We'd much prefer focus and costs that are commensurate with our size of investment.

    Our answerScope proportionate to the deal. We size it with you before we start, and we will tell you when a smaller piece of work is the right answer.

    IT DD has not considered the foundations of the businesses in the past, we've tended to jump to 'high-value' or very expensive solutions that the company can't implement or get maximum value from because the foundations aren't good enough.

    Our answerWe check the foundations first, so what we recommend is something the company can actually implement.

    What is always helpful to us in a report is to get a COST of how much changing the IT infrastructure and the recommendations that are being in the report are going to cost.

    Our answerEvery recommendation carries a cost and a timing, drawn from models we have built across 200+ deals. That is what makes it a costed roadmap rather than a wish list.

    Missed items causing large costs down the line for us or restricting the business' growth potential.

    Our answerThe average unbudgeted spend we uncover is around £250k, with a range of £20k to several million. Found before close it is priceable. Found after, it is a write-off.

    Clear report which can be understood by non-tech people and including very clear recommendations.

    Our answerPlain English, written for the investment committee rather than the engineers, and structured so the recommendations drop straight into a 100-day plan.

    Investor interviews, 2019 to 2020. Anonymised and quoted verbatim.

    How we help investors

    Before the LOI, and long after it.

    01

    Pre-deal opinion

    Technology due diligence in plain English: what's real, what's marketing, what it will cost to fix, and what to negotiate on.

    02

    The people risk

    The team, the leadership and the org design behind the technology. Most of the value walks out on legs, not servers.

    03

    Integration, then the hold

    Post-Merger Integration is the practice we are built around: Day 1 readiness, transitional service exit, consolidation, and the savings and gains you priced the deal on, delivered and tracked, then spend taken out and exit preparation across the hold.

    What changed

    Two reads, two outcomes.

    These are our clients' outcomes, not ours. Beyond M&A is bootstrapped and independent, so the opinion you get is ours, not an investor's.

    Invested with eyes open

    A VC backing a Web3 immersive events platform. The technology claim held, the team didn't yet, and the remediation list was defined before the cheque.

    Read the case

    Client closed a £9m round

    A profitable HR SaaS firm had never been diligenced. Three months of structured remediation and an investor-ready evidence pack got their round away.

    Read the case

    Best fit

    We work best with

    • Buyers who bring us in before an LOI rather than after the problem.
    • Investors backing a sector they don't yet read technically.
    • Deal teams who want an opinion, not a risk list with no view in it.
    • If you need a tick-box report at the lowest price, we're probably not the right firm, and we'll say so on the first call.

    Leadership

    8 in 10 leadership teams need support to reach the next stage. Here is what that support actually changed.

    The money is one thing. Whether the team can carry the growth plan is the other. Four situations, anonymised, with the consequence attached.

    The investors were ready to let the CTO go.

    An incoming CTO wanted out. He had no appetite for institutional investor pressure, and the investors could not see his value in diligence. Neither side knew the other's plan. We worked with him on how to operate at that level and how to be read by a board.

    He stayed, raised his game, and is still in the seat more than five years later.

    A new hire had to face a PE board, having never done it.

    Strong technologist, first institutional board. We helped him cut the pack to what the board actually decides on and rehearse the argument until he could defend it.

    He presented it himself and the board backed the plan.

    The CTO and the CEO could not stop clashing.

    Projects were landing late and the business felt it. His Kolbe profile showed a natural entrepreneur, not an operator, sitting in an operator's seat and underpaid for either.

    He left to build, with our support and no bad blood, and a governed operator took the seat. Delivery dates started holding.

    An investor could not work out why technology cost so much.

    Psychometrics and a short piece of work with the leader showed a commercial mind in a CTO title. We gave the strategy advice the seat needed rather than pretending the fit was there.

    Product stack reduced, the team refocused, and the spend became explainable.

    Five films

    Pricing AI in a deal, out loud.

    The spoken version of our paper, Who The Hell Knows. Pain, aspiration, traps, and what you can actually test for before you sign.

    Five films · about 13 minutes in total

    01 · The pain

    Who the hell knows: nobody can price AI in a deal right now

    3 min watch

    Public SaaS multiples fell from a median 6.2x EV/revenue at the end of 2024 to 3.3x by Q1 2026, while AI-native software still commands double digits. The same ARR, growing at the same rate, is worth a completely different number depending on a label. That is not a knowledge gap in your team. It is the market.

    What to test for

    • · Which side of the valuation split is this deck implicitly asking you to price it on?
    • · Is the AI claim doing valuation work that the revenue quality cannot support?
    • · What would have to be true in three years for today's multiple to still make sense?

    02 · The trap

    Technology is transforming industries, but there is no tech moat

    3 min watch

    This is not a cynical view, it is the industry's own working assumption, argued inside Google itself in the memo "We have no moat, and neither does OpenAI." If the labs building the frontier models do not believe in a technology moat, a Series C company's version of the same claim deserves real scrutiny.

    What to test for

    • · Strip the model out of the story. What is left that a competitor could not buy off the shelf?
    • · Is the advantage in the technology, or in the data, workflow and judgment wrapped around it?
    • · Could a well-funded competitor replicate the core capability in twelve months?

    03 · The aspiration

    AI-native or AI-washed: knowing which is in front of you

    2 min watch

    Two things make AI defensible, and neither of them is the model. It is proprietary data that compounds with use, and an operating model genuinely rebuilt around the technology rather than bolted onto it. Everything else is a label. The goal is to walk out of the room knowing which one you just saw.

    What to test for

    • · Is the data proprietary and compounding, or licensed and available to anyone?
    • · Has the operating model actually changed, or has AI been added to the existing one?
    • · Has anyone assessed the technical team's structure and psychology, not just the product demo?

    04 · How to address it

    Turn the diagnostic into a number

    3 min watch

    Score each dimension one to five and add them up. This is not precision. It is a forcing function against gut feel and against whatever the management deck has already told you to conclude. Above 32 is credibly AI-native. Below 20, the multiple has not been earned by the technology yet.

    What to test for

    • · Score before the management presentation frames your thinking, not after.
    • · Twenty to thirty-one is transitional: real signal and real risk in the same target.
    • · Is there a documented 90-day AI roadmap with measurable milestones, or a vision slide?

    05 · The partner

    The type of buyer changes the diligence you need

    2 min watch

    Diligence has to move earlier and get faster without getting shallower. Only around a quarter of GPs say AI is integrated into their diligence process, and diligence is the one place a meaningful share call it effective. Choosing a partner fit for this belongs before an LOI, not after.

    What to test for

    • · Can your advisor form a view on AI defensibility pre-LOI, in days rather than weeks?
    • · Is a human analyst directing the AI tools, or is the output unsupervised?
    • · Does the work cover the team and operating model, or stop at the architecture diagram?

    Thirty minutes

    Have a live deal where this question is unresolved?

    Bring the target and we will give you a strong, constructive opinion on how real the AI is, before an LOI rather than after.

    Book a conversation

    Score your target

    Turn the diagnostic into a number.

    This is not precision. It is a forcing function against gut feel, and against whatever the management deck has already told you to conclude.

    The diagnostic

    Score the target in front of you

    Eight dimensions, one to five each. Score it before the management presentation frames your thinking. Nothing you enter leaves your browser.

    01 · Proprietary data

    Is the data proprietary and compounding with use, or licensed and available to anyone?

    Public or licensed dataProprietary and compounding

    02 · Operating model

    Has the operating model been rebuilt around the technology, or has AI been bolted onto the old one?

    AI bolted onGenuinely rebuilt

    03 · Team and structure

    Is the technical team structured, incentivised and psychologically set up for continuous change?

    Traditional hierarchySmall, accountable pods

    04 · Architecture

    Can the architecture swap models and vendors, or is it wedded to one provider's roadmap?

    Single-vendor lock-inModel agnostic

    05 · AI roadmap

    Is there a documented 90-day roadmap with measurable milestones, or a vision slide?

    Vision slide onlyMeasured 90-day plan

    06 · Revenue quality

    Is AI revenue contracted and recurring, or pilot income being counted as ARR?

    Pilots counted as ARRContracted and recurring

    07 · Defensibility

    Strip the model out. What is left that a funded competitor could not replicate in twelve months?

    Replicable in monthsHard to replicate

    08 · Governance and risk

    Are data rights, model usage and customer consent documented and defensible?

    UndocumentedDocumented and defensible

    Your score

    0 / 40

    0 of 8 scored

    The paper · August 2026

    Who The Hell Knows

    Twenty pages on why the same growth number prices two completely different ways right now, how to tell an AI-native business from an AI-branded one, and how to choose a diligence partner fit for a market this unresolved.

    • · Part One. The market you're underwriting
    • · Part Two. The targets you evaluate, with a scored diagnostic
    • · Part Three. The partner you choose, before an LOI not after

    Your email sends the document and the occasional note worth reading. No sequence, no sales call unless you ask for one, and one click to stop.

    What clients say

    "Great due diligence leaves the management team with a sharper view of their business and enhanced motivation. Beyond M&A does great due diligence."

    John Reynolds, COO, Coadjute

    "Hutton and his team strike a good balance between technical and commercial skills. The output is an easy to read, concise report with no jargon."

    Thomas Nicholls, CFO, Renaissance Capital Partners

    "We engaged Beyond for technical due diligence, and their expertise was outstanding. Thorough, insightful, and actionable assessments that exceeded our expectations."

    Paul Freeman, CTO, DJH

    Questions we get asked

    What investors ask us first.

    All the questions in one place

    What is technology due diligence?

    Technology due diligence is an assessment of whether a target's technology, team and spend can carry the investment case. Beyond M&A covers twelve scope areas and returns a costed roadmap a non-technical reader can act on.

    How is the scope sized?

    In proportion to the deal. We check the foundations first, then scope only what the decision needs. Where a smaller piece of work is the right answer, we say so before the proposal.

    Do the recommendations come with costs attached?

    Yes. Every finding carries a number, an owner and a timing, so the investment committee can price it rather than read it. Integration is costed at diligence, not discovered after completion.

    How does Beyond M&A treat AI in a target?

    As something to judge rather than describe. We test whether the AI position holds, price it, and apply that judgement to an estate we may then have to integrate and run.

    Selected engagements

    • IRIS Software Group (Hg)
    • Civica (Blackstone)
    • Citation Group (Hg)
    • Equiniti
    • Acacium Group
    • Puma Growth Partners
    • Blixt
    • Mobeus Equity Partners
    • DJH

    Closing thought

    The moat, in the end, is the people directing it.

    The honest posture is neither panic nor denial. It is "who the hell knows, so let's go find out what we can actually test for." If you have a live deal where that question is unresolved, we will give you a strong, constructive opinion on it.

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