Playground
Playground's sale to Procare, a Roper Technologies company, closed in September 2026. There was no banker and no finance team.
- The challenge
- A buyer with three consulting firms, and no banker or finance person on our side.
- What we did
- Built the operating model from scratch, then ran the diligence war room with the three founders.
- The result
- Every request went back with a file built for it, and the deal closed.
Playground was acquired by Procare in September 2026. Procare is part of Roper Technologies, a public Fortune 500 company. The buyer had three separate consulting firms working on diligence. There was no banker. The deal team was the three founders and Sophie Finke, now Vantidge's founder. Nobody else at the company knew until it was done.
Playground also did not have a finance person when Sophie started. She built the operating model and the pre-diligence materials from scratch. When the buyer sent their request list, every answer went back with a file she built during diligence. In the end that was 439 requests, 714 files and 27 calls.
The screenshots are redacted: numbers are blacked out and names are removed.
The deal tracker
The buyer sent over 400 requests in a spreadsheet and stood up the VDR. Sophie built an app to track them internally. Each request had an owner, a status and a due date, and the app synced with the data room every night.
She also connected Claude to the tracker. It could read a request, draft an answer and attach a file. Every draft was a starting point. Sophie checked each one by hand before anything was posted.
The app had a page for the merger agreement too. Comments on it went to counsel from that one page. The buyer's consultants' written questions had their own queue. Every answer was drafted, reviewed and signed off in one place.


The Pooh Report
Sophie sent the deal team an email every night at 9pm. It had the day's progress, what was overdue and a leaderboard. Claude wrote a short “gossip column” from what changed in the tracker that day, and Sophie read it before it went out.
Each day gave us a “happiness meter” from the perspective of the buyer's diligence lead (an estimate). It went down when items were overdue or reopened. Sophie gave his LinkedIn picture twelve facial expressions to match. We showed the buyer's team after the deal. They loved it and still bring it up.


Burn and runway
Alongside the deal, the founders asked a simple question. If this doesn't go through, how long is our runway and what should we cut?
The only way the team tracked burn was looking at the bank balance each month. Sophie pulled the raw data from each source and tied it to the books, then built a dashboard for burn and runway on top of it. It has a cash forecast tested against past months, and a cut board that shows when each cut would actually hit the bank.


The operating model
The buyer's first ask was a financial model and a forecast. Sophie built one in Excel from scratch, since nothing existed since the Series A docs. Revenue starts from the number of active schools and builds up to payments and SaaS. Headcount and opex come after that. Every line ties back to the general ledger, and a script checks every tie-out before a new version goes out.
The internal team did not speak Excel. They kept asking for fewer spreadsheet-style views, so she built them a dashboard on the same model. Anyone on the team could move a lever and see what happened to cash and runway without opening a workbook.


What went into the data room
Every request went back with something built during diligence. These were the bigger ones.
- A quality of earnings pack with revenue and ARR by customer, and a key that matches customers across every system.
- A payments databook by location and card type, tied to the fee ledger.
- A P&L on a Stripe basis and a deferred revenue bridge, with a write-up of where they differ from GAAP.
- Written answers to the consultants' full question list.
- A cost build by function.
- Sales tax exposure by state, and the request lists for our CPA and counsel.
Vantidge's diligence work is built on this setup. See how diligence works.
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