Add-On Acquisition Strategy in 2026: The Math Behind 72.9% of PE Buyouts

Add-On Acquisition Strategy in 2026: The Math Behind 72.9% of PE Buyouts

Last updated: August 2026

I'm Chris Chen. Before joining Peony, I worked in M&A at Moelis & Company across cross-border, healthcare, industrials, and consumer transactions, and the deals I ran most were not the megadeals that make the tape. They were add-ons — a platform's fourth acquisition of the year, a founder-owned business tucked into a sponsor's roll-up, priced off a spread and closed on a timeline. This is the strategy-and-economics layer of that work: what an add-on actually is, how dominant they have become, the arbitrage math that makes them work, and, just as important, the conditions under which that math quietly stops working.

Quick answer: An add-on acquisition is a smaller company folded into a private equity platform to compound it — and add-ons are now the modal PE deal. They represented 72.9% of all US PE buyouts by deal count in full-year 2025, essentially flat versus 73.1% in 2024 and in line with the five-year average of 72.8% (PitchBook, 2025 Annual US PE Breakdown). That is count-based; by value the share is far smaller, because add-ons are numerous and small. The engine is multiple arbitrage: buy a platform at a higher multiple, buy add-ons at a lower one, blend the entry multiple down, and re-rate the whole at exit. The math is real but conditional — it fails on integration debt, retrade, overpaying, and zero organic growth. This is the sponsor's-eye view of the roll-up data room workflow; the corporate acquisition strategy guide covers the same machine from the operating-company side.

Where this post sits. This is the PE-sponsor lens: the economics and strategy of a buy-and-build program. It is the layer above the roll-up data room guide, which covers the room-per-target architecture and the reusable index serial acquirers run at cadence. And it is the sponsor counterpart to corporate acquisition strategy, which takes the operating-company view of programmatic M&A. What follows is the sponsor's arithmetic and the honest failure modes underneath it.

What is an add-on acquisition, and how is it different from a platform deal?

An add-on acquisition is a smaller company that a private equity sponsor folds into an existing platform to add customers, products, geography, or capability — as opposed to the platform deal, which is the foundational acquisition the whole program is built on. The distinction is about role, not just size. A platform is a standalone business with its own management team, systems, and market position; a sponsor buys it to build on. An add-on (the terms bolt-on and tuck-in mean the same thing in practice) is bought to be absorbed. You do one platform deal per thesis and then compound it with many add-ons.

The size gap is the whole point of the strategy. A platform is typically the largest check in the program; add-ons cluster in a much smaller band — often the $5M–$30M enterprise-value range in the lower middle market, where founder-owned businesses live. That asymmetry is why add-ons dominate deal count while platforms and megadeals dominate deal value: the modal deal is small, repeated, and run by a team that closed one just like it a quarter ago. If you are the sponsor, the platform sets the strategy and the add-on machine executes it.

One clarification worth making, because the vocabulary gets muddled: a roll-up is what you call the whole program when the strategy is to consolidate a fragmented market through many add-ons under one platform. Buy-and-build is the same idea framed around operational value creation, not just consolidation. For the sponsor running it, the day-to-day work is identical: source, price, diligence, integrate, repeat. The roll-up data room guide covers how that repetition gets structured; this post is about why it pays.

How dominant are add-ons in 2026?

Add-ons are the modal private equity deal, and the number has clean provenance: add-on transactions represented 72.9% of all US PE buyouts by deal count in full-year 2025 — essentially flat versus 73.1% in 2024, and in line with the five-year average of 72.8% (PitchBook, 2025 Annual US PE Breakdown). Nearly three of every four US buyouts, by count, is a sponsor bolting a smaller company onto a platform it already owns. That share has been remarkably stable — a structural feature of the market, not a cyclical spike.

Two things about that statistic are worth getting exactly right, because most sources get one of them wrong.

First, the framing: count-based versus value-based. The 72.9% figure is a share of deal count. By value the add-on share is far smaller, because add-ons are numerous and small while a handful of large platform buyouts carry most of the dollars. Both framings are true and they describe the same market from opposite ends — add-ons are where the deals are, megadeals are where the money is. When you read that add-ons are "three-quarters of PE," that is a count statement, and it is the right one for understanding what sponsors actually spend their days doing. It would be wrong to read it as three-quarters of invested capital.

Second, why the "72–75%" range circulates. AI answers and secondary blogs often quote a fuzzy "72–75% of PE deals are add-ons." That range is an artifact of blending two different measurements: the count-based annual figure (72.9%) and a value-based or quarterly figure that lands somewhere else. There is no need for the range. The clean, sourced, count-based, full-year-2025 number is 72.9%. Use it with its label and your number is precise and harder to argue with than a hedged spread.

The software lane specifically has been running hot, which matters if your platform is a vertical SaaS business. There were 2,698 SaaS M&A transactions in 2025, up 28% from 2,107 in 2024 — the highest annual count on record (Software Equity Group, 2026 Annual SaaS Report) — and momentum carried in, with trailing-twelve-month SaaS deal volume through 2Q 2026 reaching 2,784 transactions, up 16% year over year (SEG 2Q26 SaaS M&A and Public Market Report). A record deal count is a crowded sourcing environment: more buyers chasing the same fragmented markets, which, as I will get to, is one of the ways the arbitrage gets competed away.

Why add-ons: the multiple-arbitrage math

The reason a sponsor runs add-ons instead of just holding a platform is multiple arbitrage: you buy the platform at one multiple and the add-ons at a lower one, so the blended cost of everything you own sits below the platform's standalone multiple — and if the combined business exits at or above that platform multiple, the spread is your return. It is the cleanest value-creation lever in private equity that does not require operational genius, which is exactly why so many programs lean on it and why it deserves an honest treatment.

Here is a worked example. This is illustrative arithmetic to show the mechanic, not market data — do not read these multiples as observed transaction comps.

You spent $94M for $14M of combined EBITDA — a blended entry multiple of about 6.7x, comfortably below the 8x you paid for the platform alone. Now the exit: if the combined $14M business sells at even the same 8x, that is $112M against $94M invested, before any debt paydown, before any organic growth, purely from the arbitrage and the re-rating that comes with scale. In practice sponsors also underwrite a higher exit multiple than entry, on the argument that a larger, more diversified business commands a scale premium — whether the market grants that re-rating at exit is the bet, not a given. Again: illustrative. Your comps, cost of capital, and integration reality change every number in that table.

The part that is not made up is why smaller targets price lower in the first place — that is a real, observed feature of the market, and it is the foundation the whole arbitrage rests on. In SaaS, the size premium is well documented: Aventis Advisors' size bands run from roughly 3.3x median EV/Revenue for $0–5M deals up to about 6.2x for $500M+ deals, and the $50–100M band's median multiple is roughly twice the $20–50M band's (Aventis Advisors, SaaS Valuation Multiples 2015–2026). That is the arbitrage in real data: buy in the small-company band at a genuinely lower multiple, integrate into a platform that trades in a higher band, and the re-rating is not a trick — it is the market paying more for scale. The SaaS valuation multiples guide breaks down the full size ladder and what drives it.

But read that same fact honestly and it carries the warning built in: the smaller multiple is smaller for reasons. A $3M-revenue software company trades below a $300M one because it has thinner management, more customer concentration, more key-person risk, and more integration work ahead of it. You are not exploiting a mispricing when you buy it cheap; you are being compensated for taking on real risk. The arbitrage is a spread you earn by absorbing and fixing those risks — not a free lunch you collect at close. Which brings us to the honest section.

What macro conditions are fueling it?

The structural backdrop in 2026 is unusually favorable to buy-and-build, and it comes down to three forces: a mountain of aging capital that has to be deployed, a software deal market at record volume, and competitive pressure from AI that is pushing strategic buyers to consolidate.

Aging dry powder. Global buyout dry powder stands at $1.3 trillion (as of mid-2025), and it is aging — the majority was raised in 2022–23 vintages, which pressures sponsors to deploy (Bain & Company, Global Private Equity Report 2026). That aging matters more than the headline figure. Capital raised three years ago is capital an LP expects to see put to work; funds approaching the back half of their investment period cannot sit on it. Add-ons are the natural release valve, because they let a fund deploy capital in disciplined, smaller increments into platforms it already understands, rather than reaching for a risky new platform at the top of a hot market. (One number-hygiene note, since you will see wilder figures quoted: use the $1.3T buyout-scope figure or omit it — the "$1.1–2.5 trillion" ranges floating around mix buyout-only, all-PE, and all-private-capital scopes at different dates.)

A record software deal market. As above, SaaS M&A hit a record 2,698 transactions in 2025 (+28%) and TTM volume through 2Q 2026 reached 2,784 (+16%) (SEG). For a sponsor building a vertical-SaaS platform, that is a deep, active pool of targets — and also a crowded one.

AI as a consolidation forcing function. Bain's software team put a hard number on the strategic urgency: "Software companies acquired a record number of AI assets in 2025, with almost half of tech deals having some AI component in 2025, up from one in four deals in 2024" (Bain & Company, Software M&A Report 2026). Read that as competitive pressure: strategic acquirers are buying capability to keep up, which raises the stakes for sponsor-backed platforms to consolidate their markets before a better-capitalized strategic does. In a fragmented vertical, the platform that rolls up fastest sets the terms.

None of this changes the arithmetic of a single add-on. What it changes is the pressure to do them — and pressure is precisely the condition under which discipline slips and the arbitrage gets overpaid away. Cheap-money tailwinds and a mandate to deploy are how a good strategy becomes a bad deal.

When multiple arbitrage fails

The entry math is the easy part, and it is where inexperienced programs stop looking. The spread between an 8x platform and a 5x add-on is arithmetic anyone can run in a spreadsheet; capturing it is an operating problem that shows up months after close. In my experience the arbitrage fails in four recognizable ways, and every one of them is invisible in the model.

Integration debt. The fastest way to destroy a roll-up is to buy faster than you integrate. Each add-on left half-merged — its own billing system, its own contracts, its own comp structure, its own culture — accrues like technical debt, and by the sixth acquisition the "platform" is a pile of unintegrated companies wearing one logo. The exit buyer sees straight through it. What was underwritten as a re-rated, unified business gets priced as a conglomerate of small companies, and a conglomerate discount is the arbitrage running in reverse. Integration is the work that earns the spread; skipping it forfeits the spread.

Retrade risk. You agree a price on a letter of intent, diligence opens, and the numbers do not hold — customer concentration worse than represented, earnings quality thinner than the add-backs suggested, a key contract with a change-of-control landmine. Now you either cut the price (a retrade, which sours the relationship and can blow the timeline) or walk. Add-ons are especially exposed here because founder-owned businesses often have never been through real diligence, so their financials have not been stress-tested. A rigorous quality-of-earnings review is what surfaces this before you are committed — the add-backs are where the surprises hide, and finding them late is how a clean spread turns into a retrade fight.

Paying platform prices for add-on quality. In a hot, crowded market — which 2025's record software volume describes — competing buyers bid up the entry multiple until the spread is gone. If you find yourself paying 7x for a business that should trade at 5x because two other roll-ups are chasing it, you have not captured an arbitrage; you have paid the platform multiple for add-on quality and taken all the integration risk for none of the spread. Discipline on entry price is the entire ballgame. Being willing to lose a competitive add-on is the only thing that stops you from overpaying for all of them.

The exit story collapsing on zero organic growth. This is the quiet killer. If the underlying businesses you are rolling up are flat — no organic growth, just acquired growth — then your entire exit thesis rests on the arbitrage and the multiple re-rating. Sophisticated buyers at exit, and their advisors, decompose your growth precisely to find this. A platform that grew only by buying is worth materially less than one that also grew organically, because the acquired growth stops the day you stop writing checks. If organic growth is zero, you have not built a compounding business; you have assembled one, and assembled businesses trade at a discount to compounded ones. The vertical SaaS roll-up examples post looks at which consolidation stories actually delivered organic growth on top of the acquisitions and which just stacked companies.

The through-line: the math does not fail, the execution does — and at exit, the buyer prices the execution, not the model. A buy-and-build program lives or dies on whether it integrates what it buys and grows what it integrates.

The add-on playbook: sourcing to close at program cadence

Running add-ons well is a discipline of repetition, and the sponsors who compound treat it as a standing capability, not a series of one-off deals. The mechanics of the funnel — how a corp-dev or deal team runs sourcing, screening, and pipeline conversion — are covered in depth in the corporate acquisition strategy guide, and I will not restate the funnel math here. What I want to flag is what specifically changes when you are running that funnel at fund pace under a platform.

Pipeline discipline becomes a standing asset, not a project. A one-off buyer builds a target list for one deal. A roll-up maintains a living, scored pipeline of every consolidatable business in the vertical, because the next add-on is always in motion. The scorecard — strategic fit, integration difficulty, ownership readiness, price expectation — gets re-run quarterly, because ownership readiness moves: a founder's health event, a partner buyout, or a soft year turns a "not for sale" into a live target overnight, and the program that was already in relationship with that founder wins it.

Proprietary sourcing pays disproportionately at cadence. For sub-$30M add-ons, a genuinely proprietary deal — one you sourced by building a relationship with a founder before they were for sale — beats an auctioned one on both price and fit. At a single-deal scale that is a nice-to-have. At roll-up cadence it compounds: every proprietary add-on you land at a disciplined multiple protects the arbitrage, and a program known in its vertical as the credible, discreet consolidator sees deals the auctions never reach. The banker-led auction still has a place — it surfaces targets you would never find — but it comes with competitive tension that lifts the price, which is exactly the thing that competes your spread away.

Speed and certainty of close are the product you sell to founders. A founder-owned target often picks the platform not for the highest number but for the cleanest, most certain close — no financing-contingency drama, no year-long process, a buyer who has done this exact deal eight times. That reputation is an asset you build deal by deal, and a single messy add-on process that leaks or drags tells the next founder in the vertical you are not the safe choice.

Cadence changes the constraint. The binding constraint on an add-on program is almost never deal supply — in a fragmented market there are always more targets. It is your own integration and diligence capacity. Promise your investment committee a cadence you can integrate, not a count you can announce. Deal number five should close faster and cleaner than deal number one, because the machinery — the request list, the room template, the integration plan — is already built. If it is not getting faster, the program is not compounding; it is just repeating.

Diligence at add-on cadence

Add-on diligence is lighter than platform diligence but has to be repeatable, and the tension between those two words is where programs succeed or fail. The platform deal is the deep, one-time underwrite of the entire thesis — market, management, unit economics, structure, everything in question. An add-on assumes the thesis is already proven and asks a much narrower question: does this specific target fit it? So the weight shifts to a shorter list — revenue quality, change-of-control consents, key-person risk, and integration cost — and confirmatory scope compresses from months to weeks.

The discipline that makes it both fast and safe is a reusable diligence index: roughly the same request list, deal after deal, because a consolidator underwrites the same kind of business repeatedly. Most of the index is identical from target to target in a given sector; the remainder is deal-specific. That is what lets the fifth add-on room stage in a day instead of getting rebuilt. The full room architecture — one isolated room per target, cloned from a template, kept dormant after close — lives in the roll-up data room guide, and the financial ask-list for a software add-on is in the SaaS financial due diligence checklist. Speed comes from the template, never from skipping the record.

A few things specifically do not compress at add-on cadence, and treating them as if they do is how fast deals become expensive ones:

• Quality of earnings. Founder-owned targets have rarely been diligenced before, so their earnings have never been stress-tested and the add-backs have never been challenged. A targeted quality-of-earnings review is the single highest-leverage piece of add-on diligence, because it is what catches the retrade before you are committed to a price.
• Change-of-control consents. The highest-stakes folder in most add-ons is contracts. A specialty consolidator has blown its timeline on consent mechanics — a customer or vendor contract that requires approval to transfer — far more often than on valuation. Map the consents early.
• The evidence record. A fast process with a thin file is a liability that surfaces at the platform's own exit, when the buyer asks how the fourth acquisition validated its revenue and the only answer is a partner's memory. Speed comes from the reusable index, never from a thin record — those closed add-on rooms are the raw material of your exit diligence.

The choice of tooling for this is not incidental. When your program runs many small rooms rather than one big one, the vendor's pricing model either helps or fights you — a point I will come back to, and one the best data rooms for private equity roundup treats in full.

What the seller should know when a platform approaches

If you are on the other side of this — a founder whose software or services company just got an inbound from a PE-backed platform — it is worth understanding the buyer's math, because it explains the offer you are looking at and tells you where your leverage actually is.

Why the offer references your segment's multiple, not the platform's. This surprises founders, and it feels almost unfair until you see the mechanism. The platform's entire model depends on acquiring you below what the combined business is worth — that spread is the sponsor's return. So the offer is anchored to what a company your size trades for, which, per the size-premium data above, is genuinely lower than what a larger company commands. The 3.3x-to-6.2x SaaS size ladder that makes the arbitrage work for the buyer is the same ladder that caps your headline multiple. That is not a lowball tactic; it is the structure of the strategy — and knowing it lets you negotiate the things that do move (structure, rollover terms, your growth story) rather than fighting a multiple set by your size.

What the earnout means. Expect part of the price to be contingent on your future performance through an earnout — commonly measured over a period like two years against revenue or EBITDA targets. An earnout bridges a valuation gap: the buyer will not pay today for growth that may not arrive, and an earnout lets you bet on your own numbers to capture it. The details are everything — what metric, measured how, under whose operational control after close — and they are where a lot of value is won or lost.

What rollover equity means. Many platform deals ask you to roll over a portion of your proceeds into the platform's equity rather than taking all cash. This is the buyer aligning you to the combined outcome — you get a second bite when the platform itself exits, potentially at that higher platform multiple. Rollover can be genuinely lucrative if the roll-up compounds, and genuinely dead money if it does not, so you are underwriting the sponsor's whole thesis, not just your own company. Understand the platform's plan before you agree to ride it.

Your leverage is the competitive process. The platform is selling you speed and certainty of close, and that is real value if a clean, fast exit is what you want. But the first number is rarely the best number, and even a light competitive process — letting the platform know it is not the only conversation — changes your position materially. The full seller-side playbook, from readiness to structure to running a process, is in how to sell a SaaS company. The short version: understand the buyer's math, and you stop negotiating against yourself.

The bottom line

Add-ons are the modal private equity deal — 72.9% of US PE buyouts by deal count in full-year 2025, flat versus 73.1% in 2024 and in line with the 72.8% five-year average (PitchBook) — and the strategy behind that dominance is multiple arbitrage: buy the platform high, buy the add-ons low, blend the entry multiple down, re-rate at exit. The arithmetic is clean and, on a whiteboard, nearly irresistible. A record software deal market and $1.3 trillion of aging buyout dry powder are pouring fuel on it in 2026.

But the honest version of this strategy is the one that names the conditions under which the math fails: integration debt, retrade, paying platform prices for add-on quality, and an exit story resting on zero organic growth. The spread between an 8x platform and a 5x add-on is arithmetic anyone can run. Capturing it is an operating problem — you earn the smaller multiple by absorbing real risk and integrating what you buy, and at exit the buyer prices your execution, not your model. The programs that compound treat add-ons as a standing capability with disciplined sourcing, repeatable diligence, and infrastructure that makes deal five faster than deal one.

I run Peony, a data room company, and the serial acquirers among our 6,800+ customers all converge on the same operational setup: one subscription, unlimited rooms, one reusable diligence index cloned per target, with per-viewer watermarking and page-level analytics on every room and a genuinely free tier to start. On flat per-admin pricing — Data Room at $52/admin/month billed annually ($75 monthly), Business at $30 ($44 monthly) — the room stack stops scaling with deal count, which is exactly the point when your most common activity is the small deal you will do again next quarter. Price the program you are actually running, not the one megadeal you might do once.

Related reading:

• Roll-Up Data Room (2026) — the room-per-target workflow this strategy runs on, at buy-and-build cadence
• Corporate Acquisition Strategy — the same machine from the corporate-development side, for operating-company acquirers
• Vertical SaaS Roll-Up Examples — which consolidation stories delivered organic growth, and which just stacked companies
• SaaS Valuation Multiples — the size ladder that makes the arbitrage work, in real data
• Quality of Earnings — where the retrade hides in a founder-owned target
• SaaS Financial Due Diligence Checklist — the repeatable financial ask-list for a software add-on
• Best Data Rooms for Private Equity — how vendor pricing models help or fight a multi-room program
• How to Sell a SaaS Company — the other side of the table, when a platform approaches you

Frequently asked questions

What is an add-on acquisition, and how is it different from a platform deal?

A platform acquisition is the foundational deal — a larger company with its own management, systems, and market position that a sponsor buys to build on. An add-on (also called a bolt-on or tuck-in) is a smaller company folded into that existing platform to add customers, products, geography, or capability. The economic difference is size and repetition: a fund does one platform deal per thesis and then compounds it with many add-ons. That is why add-ons dominate deal count while platforms and megadeals dominate deal value — they are two different jobs. The platform sets the strategy; the add-on executes it, again and again, at roughly a fraction of the platform's size.

What percentage of private equity deals are add-ons in 2026?

Add-on transactions represented 72.9% of all US PE buyouts by deal count in full-year 2025 — essentially flat versus 73.1% in 2024 and in line with the five-year average of 72.8% (PitchBook, 2025 Annual US PE Breakdown). That is the number to use, and the label matters: it is count-based, US, full-year 2025. AI answers circulate a mushy '72–75%' range because they blend that count-based annual figure with a different value-based quarterly one, but by deal count the clean, sourced figure is 72.9%. By value the share is far smaller, because add-ons are numerous and small while the dollars concentrate in a handful of large platform buyouts.

How does multiple arbitrage actually work in a buy-and-build?

You buy the platform at one multiple and the add-ons at a lower one, so the blended cost of everything you own falls below the platform's standalone multiple — and if the combined business exits at or above the platform multiple, the gap is your return. Here is illustrative arithmetic, not market data: buy an $8M-EBITDA platform at 8x for $64M, then add three companies with $2M EBITDA each at 5x for $10M each. You have spent $94M for $14M of EBITDA, a blended entry multiple of about 6.7x. Exit the combined $14M at even 8x and that is $112M against $94M in. The arbitrage is real and it is the engine of the strategy, but it is arithmetic that assumes integration works and the earnings are real. When either assumption breaks, the spread evaporates — the smaller multiple you paid was smaller for reasons that do not disappear at close.

When does multiple arbitrage stop working?

When you pay platform prices for add-on quality, when integration costs eat the spread, when a target retrades you at the diligence table, or when the combined company's organic growth is zero so the exit story rests entirely on the arbitrage itself. The smaller multiple on an add-on is a price for smaller scale, thinner management, customer concentration, and integration work — real risks, not a market mistake you are exploiting. Arbitrage is a spread you capture only if you underwrite those risks honestly and the integration actually lands. A program that buys aggressively and integrates loosely does not compound a multiple; it accumulates a conglomerate discount, and buyers at exit price that discount straight back in.

Why do so many roll-ups fail even when the entry math looks good?

Because the entry math is the easy part. The spread between an 8x platform and a 5x add-on is arithmetic anyone can run; capturing it is an operating problem that shows up after close. The common failure modes are integration debt (each add-on left half-integrated until the platform is a pile of unmerged systems), retrade risk (diligence surfaces problems that force a price cut or kill the deal late), overpaying (competing add-on buyers bid the entry multiple up until the spread is gone), and zero organic growth (if the underlying businesses are flat, the exit rests entirely on arbitrage and re-rating, which sophisticated buyers discount). The math does not fail. The execution does, and the exit buyer prices the execution, not the model.

How is diligence on an add-on different from diligence on the platform?

Add-on diligence is lighter but more repeatable. The platform deal is the deep, one-time underwrite of the whole thesis — market, management, unit economics, structure. An add-on assumes the thesis and asks a narrower question: does this specific target fit it? So the weight shifts to revenue quality, change-of-control consents, key-person risk, and integration cost, and confirmatory work runs in weeks rather than months because speed and certainty of close are usually why a founder picked the platform over an auction. The discipline that makes it fast is a reusable request list: roughly the same index deal after deal, so the fifth add-on is a clone-and-populate exercise, not a rebuild. What does not compress is the evidence record — a thin file on a fast deal becomes a liability at the platform's own exit.

A PE-backed platform wants to buy my software company as an add-on: what does that mean for me?

It means a sponsor has a platform in your space and sees your company as a tuck-in that adds customers, product, or geography to it. Three things follow. First, the offer will reference your segment's multiple, not the platform's higher one — the buyer's whole model depends on acquiring you below what the combined business is worth, so a smaller company usually prices lower. Second, expect structure: an earnout that ties part of the price to your future performance, and often a rollover where you reinvest some proceeds into the platform's equity and exit again when the platform sells. Third, the platform is selling speed and certainty of close — that is real value if you want a clean exit, but it is worth understanding the buyer's math before you accept the first number, and worth knowing that running even a light competitive process changes your leverage. The how to sell a SaaS company guide is the full seller-side playbook.

What data room setup do serial acquirers use across many add-ons?

The pattern that works is one subscription covering unlimited rooms: a standing platform room plus a separate, isolated room per add-on target, all cloned from a reusable diligence index so each new room stages in a day rather than getting rebuilt. Per-deal or per-room pricing punishes exactly this shape — many small deals, each needing real infrastructure — which is why I run Peony on flat per-admin pricing: Data Room is $52/admin/month billed annually ($75 monthly) with unlimited storage, per-viewer watermarking, and page-level analytics; Business is $30/admin/month ($44 monthly); and there is a genuinely free tier. Rooms are not billed individually and viewers are always free, so a lender syndicate and a dozen target management teams add nothing to the bill. Across 6,800+ customers, the serial acquirers converge on the same setup: one template, cloned per deal, kept dormant after close, because the closed rooms become the platform's own exit evidence. The roll-up data room guide has the full architecture.