The seller assembled the data room. Read all of it before you set the price.
All 8 disciplines, one fixed scope
Each one is a scoped pass with its own question and its own output.
- 01
Financial
The EBITDA in the information memorandum has already been normalised by the seller, and working capital leaks in places the summary never mentions.
Which adjustments hold, which don’t, and what cost base is left standing after closing.
- 02
Commercial
Customer concentration and churn rarely make the summary page.
Which customers carry the revenue, what the pricing will actually bear, and how much retention sits underneath the growth.
- 03
Legal
The clauses that reach the margin sit in the schedules nobody reads to the end.
Every clause that triggers on the transaction or on the margin, with clause number and page, and what of it can be renegotiated.
- 04
Tax
A deferred position announces itself years after closing.
Where the structure carries risk, and what belongs in the purchase agreement because of it.
- 05
HR
Key people leave after closing, and the earn-out was resting on them.
Who is contractually tied in, who isn’t, and what pension and collective labour agreements really cost.
- 06
AI
“AI-driven” is usually a licence on someone else’s model, and who owns the data goes unanswered.
Whose model and whose data, what falls under the AI Act, and which processes genuinely automate.
- 07
Operational
Lead times and single points of failure appear on no overview.
Where the margin goes, which link carries the work on its own, and what automating those processes returns.
- 08
Valuation & deal economics
The bid comes out of a model that hadn’t seen the findings yet.
What the findings do to the price, and what room that leaves at the negotiating table.
One price for the whole scope. What each discipline looks at is set against your data room on the call. Legal and tax are tuned to Dutch law; for a target elsewhere, have local counsel check them.
What makes it one deliverable
What turns 8 separate reads into one deliverable, instead of 8 separate reports.
Value-creation read
Margin leakage, indexation gaps, cross-sell levers. The report carries the upside case too.
Cross-discipline reconciliation
Every discipline’s findings resolved into one coherent narrative, for your reviewer to sign off.
What never arrived
The running list of what was asked for and not delivered. A gap you can name is a question for the seller; a gap you cannot is a surprise after closing.
How it arrives
The dashboard and the report, plus the running list of what never arrived.
Live dashboard
Every discipline. A live, click-through dashboard. Follow any finding back to its source passage.
Synthesized report
The same findings, reconciled. One written report: every discipline’s findings resolved into a single narrative.
Alongside both
The list of what never arrived. Named, structured and delivered while there is still time to ask for it.
What it takes to start
Two things. No workshop, no kick-off week.
The data room
Uploaded by your team: financials, legal, tax, HR, contracts and IP.
Answers on what never arrived
Your answers close the gaps. Upload them and re-run the affected analysis from the platform.
Questions we get
Does this replace a quality-of-earnings report?
It is broader, and it is not an attest service. A quality-of-earnings read covers one dimension in four to ten weeks. This runs 8 disciplines and reconciles them. A signed accountant’s opinion stays a separate engagement.
How long does it take?
The pipeline pass runs in hours. Your team’s review comes after it, at your pace. We don’t commit to a date before seeing the data room.
What does it cost?
One price for the whole scope, set on the call against the size and state of your data room. No tiered menu.
What happens to our documents?
Confidential data is pseudonymised before analysis and reversed only in the final output. By default, analysis runs on Google Vertex AI in the EU, under a Data Processing Agreement. The model provider does not keep your documents or train on them.
Can I see an example report?
Not a real one. Factum is pre-launch: there is no public client or case study yet. The worked example on the homepage shows the format. The first real one you see is your own, days after the NDA.
Who signs off the findings?
Your own reviewer, in the review workspace. No client export leaves the platform without that sign-off. Factum provides the platform; the judgement and the signature are yours.