Due Diligence Prep Workflow
A DD-ready data room that lives in sync with your ops, not a 2-week scramble after a term sheet.
You got the term sheet. Closing in 4 weeks. The VC's checklist has 147 items: audited financials, cap table with scenarios, every contract >$10K, IP assignments from every contractor back to 2022, customer list with revenue concentration, SOC 2 evidence, every founder's employment agreement. Your lawyer quotes $40K for DD support. You cancel your week and start digging through Google Drive.
AI CFO + AI COO maintain a DD-ready data room year-round. Every vendor contract auto-archived at signing. Every IP assignment tracked from day one. Cap table stays current in Carta/Pulley. Customer data aggregated monthly. Security posture documented continuously. When a term sheet lands, you have 95% of the checklist already assembled — the raise closes in 4 weeks, not 12.
How it runs
- 1Year-round data room maintenance
Tycoon's DD data room in DocSend/Vaulto updates continuously: new contracts archived at signature, new hires' IP assignments tracked at onboarding, new customer logos added to the customer list, monthly financials dropped in the financials folder. Not a scramble — a living system.
- 2Checklist mapping to VC/acquirer standard
When the term sheet arrives, AI CFO maps the VC's DD checklist (pulled from their intake or a shared template) against your existing data room. Green = already in the room. Yellow = partial, needs assembly. Red = missing, needs new work. Typical starting point: 75-85% green, 10-15% yellow, 5-10% red.
- 3Cap table scenarios
AI CFO runs cap table scenarios in Carta/Pulley: pre/post money at the proposed terms, founder + employee dilution across current round + next 2 rounds, option pool sizing for the expected hire plan, liquidation waterfall under 3 exit scenarios. All exportable as a DD-ready doc with math shown.
- 4Customer concentration analysis
Stripe + HubSpot data aggregated by customer: ARR, contract length, churn risk, concentration (top 10 %, top customer %). DD teams always ask — your answer is ready with source data, not a hand-wavy estimate. Anonymized version for early-stage VCs, named for term-sheet-stage.
- 5Legal and IP clean-up
AI COO runs the legal checklist: every contractor has a signed PIIA, every employee has an IP assignment, every major vendor has an MSA with IP and data terms, trademark/copyright filings are current, founder IP was properly assigned to the company. Gaps identified early, so your lawyer fixes 5 things instead of 25.
- 6Security and compliance posture
For SaaS companies: SOC 2 evidence (if you have it), security policies, incident history, privacy posture (GDPR, CCPA), data residency. For consumer: privacy policy versioning, DMCA compliance. AI CTO maintains the security artifacts in Vanta or Drata year-round.
- 7DD Q&A response
During active DD, questions come in waves. AI CFO + AI COO draft responses pulling from the data room with source links. Founder reviews and ships in hours instead of days. Nothing gets stuck waiting for 'I'll pull that and get back to you'.
Who runs it
What you get
- ✓DD starts 85% complete on day 1 of term sheet
- ✓Raise closes in 3-5 weeks instead of 8-14
- ✓Legal bill drops 50-70% (lawyer reviews, not reconstructs)
- ✓Zero last-minute 'I can't find that contract' crises
- ✓Cap table scenarios at any moment, not a 2-day modeling exercise
- ✓Compounding advantage: same system serves Series A, B, acquisition
- ✓Founder answers DD questions in minutes, not wait-till-Monday
Frequently asked questions
I'm pre-seed — isn't this massive overkill for my stage?
At pre-seed the data room is tiny (incorporation docs, founder IP, maybe 2-3 contracts) but the habit is what compounds. Founders who run this workflow from day one spend 4 hours total on DD at their seed round. Founders who don't spend 40-80 hours. The marginal effort at pre-seed is near zero because there's almost nothing to maintain; you're just putting things in the right folder as they happen. The payoff shows up 12-18 months later when it saves you a month on your seed raise.
What about DD for acquisition, not fundraising? The checklists are different.
80% overlap with fundraising DD — same financials, same legal/IP, same customer data. The extra 20% for acquisition: employment retention packages, customer assignment clauses in contracts, tech integration feasibility, PII handling for migration, employee option acceleration scenarios. AI COO has a separate checklist template for acquisition DD that extends the fundraising one. Most founders who sell report that the data room they built during their Series A saved them 60% of time at exit.
Can it handle international DD — FIRPTA, foreign entity structure, VAT registration, GDPR?
Yes, with the same caveat as tax prep: international adds real complexity. Tycoon handles the collection (foreign entity docs in the data room, GDPR DPA with all vendors, VAT registrations tracked per country, treaty elections documented). The strategy questions — is your UK subsidiary properly structured for the acquirer? does your Irish entity create PE issues? — need a cross-border lawyer. Tycoon makes their job easier by having the underlying data clean and findable.
Our customers have NDAs — we can't share their names. How does that work?
Customer DD has three tiers: anonymized (logos replaced with 'Fortune 500 fintech', revenue bands), pseudonymized (customer ID only, with a separate key held by founder), and named (post-term-sheet, under mutual NDA). AI CFO prepares all three versions. Early VCs get anonymized. Term-sheet-stage gets pseudonymized + references. Closing gets named under NDA. The named version is the same data with a different rendering — you decide who sees what based on where the conversation is.
What about ongoing DD updates during a 4-week closing window — things change fast.
This is where 'living data room' beats 'scramble'. During closing, AI CFO runs a weekly 'data room freshness' check: new customers added, financials rolled forward, any new contracts or hires included. VCs get notified when anything material changes, so there's no 'we forgot to tell you about the big new customer you signed Tuesday' surprise. Closes feel coordinated instead of chaotic.
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