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Investor due-diligence answer register
A category-balanced register of answers to standard investor due-diligence questions, structured as data-room-ready JSON, with category coverage, answered-count consistency, and per-answer length floors machine-checked.
You receive: A JSON object { company, round_stage, items: [ { id, category, question, answer, evidence_refs: [..], status } ], category_coverage: [ { category, answered_count } ] }. category must be exactly one of: financing, technology, product, market, business_model, team, financials_returns. status must be exactly one of: answered, na, pending. Each category_coverage answered_count must equal the count of answered items in that category.
Part of Launch Product, Pitch Investors
Example
A sample of what this play produces. Your result is generated for your inputs.
- Company
- STUD.com
- Round stage
- pre-seed
Items
- Id
- fin-1
- Category
- financing
- Question
- What is the company raising, and on what basis was the amount set?
- Answer
- STUD is targeting an illustrative $1,000,000 pre-seed raise (a target, not a committed round). The amount is sized to fund the path from soft launch to the illustrative revenue objective of $250,000 in annual revenue, on a concierge fulfillment model whose capacity is one founder-operator at roughly 30 plays per week.
- Evidence refs
- fact:finance.raise_amount_usd (illustrative)
- fact:metrics.revenue_objective_usd (illustrative)
- Status
- answered
- Id
- fin-2
- Category
- financing
- Question
- What prior financing has the company taken?
- Answer
- None. STUD is pre-revenue and has taken no outside capital to date. There are no convertible notes, SAFEs, or venture debt outstanding, so the pre-seed round would be the first priced or convertible instrument on the cap table.
- Evidence refs
- fact:company.stage
- Status
- answered
- Id
- fin-3
- Category
- financing
- Question
- Is the company incorporated, and is the cap table clean?
- Answer
- Yes. STUD is a registered trade name of TELEVORT INC, a Delaware corporation. Dan Schmitz is the sole founder, and the company has taken no outside capital, so the cap table enters the round with no legacy investor claims to unwind.
- Evidence refs
- fact:company.incorporated
- fact:company.founder
- Status
- answered
- Id
- tech-1
- Category
- technology
- Question
- What is the core technology and what is defensible about it?
- Answer
- STUD is a living system for a venture: a workspace that holds what the business knows, a catalog of ready-made plays that AI agents run from a short intake, and structured results that stay current and feed the next play. The defensible part is the compounding loop, a fact stated once flows into every run, and every deliverable passes its play's acceptance check before it lands, so the catalog and the acceptance harness improve with every run.
- Evidence refs
- fact:company.what_it_does
- fact:company.one_liner
- Status
- answered
- Id
- tech-2
- Category
- technology
- Question
- How is output quality controlled when AI agents do the work?
- Answer
- Every play carries a machine acceptance check that screens each deliverable before it counts. Calculators are graded against hand-written reference oracles with held-out cases, and document plays are graded by validators that enforce the published contract, so quality control is structural rather than a manual review step.
- Evidence refs
- fact:company.solution
- Status
- answered
- Id
- prod-1
- Category
- product
- Question
- What does the product ship today, and how mature is it?
- Answer
- The live catalog holds 265 plays across 14 playbooks (measured dev-seed count, 2026-08-09), covering marketing, finance, product, and engineering work. The platform is in a soft launch: the search-first marketplace and waitlist are live, and paid fulfillment opens behind gated auth and payments.
- Evidence refs
- fact:metrics.catalog_size
- fact:company.stage
- Status
- answered
- Id
- prod-2
- Category
- product
- Question
- What problem does the product solve for its user?
- Answer
- AI can produce real knowledge work, but extracting it is still manual craft: users must know what to ask, phrase it well, re-explain the business every session, and carry outputs somewhere by hand before they go stale. STUD replaces the blank prompt with a catalog of plays whose intakes fill themselves from workspace facts, so nothing starts from zero and results compound.
- Evidence refs
- fact:company.problem
- fact:company.solution
- Status
- answered
- Id
- mkt-1
- Category
- market
- Question
- How large is the market and how fast is it growing?
- Answer
- The AI agents market is about $8B in 2025, growing at a 42 to 50 percent CAGR (cited external estimates). STUD's beachhead within it is code-first verifiable knowledge work for early-stage ventures, a segment where the buyer already trusts agents but lacks a system that makes their output land structured and reusable.
- Evidence refs
- fact:metrics.market_size_note
- Status
- answered
- Id
- mkt-2
- Category
- market
- Question
- Who is the target customer and how are they reached?
- Answer
- Solo and early-stage founders and small product teams who need marketing, finance, product, and engineering work done while staying small, with ops and engineering leads adopting AI agents as a secondary segment. Acquisition is content-led through SEO, developer documentation, and launch communities, at an illustrative blended CAC of about $40.
- Evidence refs
- fact:company.target_customer
- fact:metrics.acquisition_channels (illustrative CAC)
- Status
- answered
- Id
- bm-1
- Category
- business_model
- Question
- How does the company make money?
- Answer
- Prepaid credit packs, with 1 credit always 4 cents. One-time packs are 500 credits for $20, 1,000 for $40 (+50 bonus), 2,500 for $100 (+250 bonus), and 5,000 for $200 (+750 bonus); annual prepay packs are 6,000 credits for $240 (+1,500 bonus) and 18,000 for $720 (+5,000 bonus). Purchased credits never expire, bonus credits included. A play costs 250 to 1,000 credits ($10 to $40), most plays 500 credits ($20); credits are held when a run is commissioned and spent only on an accepted run. Paid runs open at launch. A marketplace take rate on third-party supply is a later phase.
- Evidence refs
- fact:pricing.plans_summary
- fact:pricing.credit_peg_usd
- fact:pricing.play_cost_range
- fact:pricing.business_model
- Status
- answered
- Id
- bm-2
- Category
- business_model
- Question
- What are the unit economics of a buyer account?
- Answer
- Gross margin is estimated at 87 percent (modeled 85 to 90 percent at launch prices), driven by inference cost per play sitting well under the credit price. Illustrative account economics: about $300 average annual revenue per account (about $25 a month in pack purchases, roughly 1.25 plays a month at the typical 500-credit price) against an illustrative $40 content-led CAC, with illustrative 6 percent monthly logo churn and 108 percent NRR.
- Evidence refs
- fact:finance.gross_margin_pct (estimated)
- fact:metrics.avg_annual_revenue_per_account_usd (illustrative)
- fact:metrics.cac_usd (illustrative)
- fact:metrics.monthly_logo_churn_pct (illustrative)
- fact:metrics.nrr_pct (illustrative)
- Status
- answered
- Id
- team-1
- Category
- team
- Question
- Who is on the team and what is the key-person risk?
- Answer
- STUD is founder-led by Dan Schmitz, currently a team of one operating the platform and the concierge fulfillment loop (capacity about 30 plays per week). Key-person risk is real and disclosed: the mitigation path is that fulfillment is agentic by design, so headcount is a throughput lever rather than the delivery mechanism.
- Evidence refs
- fact:company.founder
- illustrative launch scenario: concierge capacity
- Status
- answered
- Id
- team-2
- Category
- team
- Question
- What are the first hires the raise would fund?
- Answer
- No hires are committed. The working plan is that the raise funds growth engineering and supply curation ahead of any go-to-market headcount, because the concierge capacity ceiling (one operator, about 30 plays per week) is the first constraint the illustrative launch scenario hits.
- Evidence refs
- illustrative launch scenario
- Status
- answered
- Id
- finret-1
- Category
- financials_returns
- Question
- What are current revenue and the near-term revenue objective?
- Answer
- Current revenue is zero: STUD is at pre-seed, in a pre-revenue soft launch. The illustrative revenue objective is $250,000 in annual revenue from pack sales, built from the illustrative launch scenario of 200 launch signups, 40 activated buyers in month 1 (a first pack bought and a play run), 25 retained at month 3, a 60:25:10:5 first-pack mix across the $20 / $40 / $100 / $200 packs (average first pack $42), and about $25 a month in pack purchases per active buyer.
- Evidence refs
- fact:company.stage
- fact:metrics.revenue_objective_usd (illustrative)
- illustrative launch scenario
- Status
- answered
- Id
- finret-2
- Category
- financials_returns
- Question
- Are audited financial statements available?
- Answer
- Not applicable at this stage: TELEVORT INC is pre-revenue and there is no revenue history to audit. Management accounts will be the reporting basis through the pre-seed period.
- Evidence refs
- fact:company.incorporated
- fact:company.stage
- Status
- na
Category coverage
| Category | Answered count |
|---|---|
| financing | 3 |
| technology | 2 |
| product | 2 |
| market | 2 |
| business_model | 2 |
| team | 2 |
| financials_returns | 1 |
Opens soon
STUD opens runs for everyone soon, on every play at once.
Scope of the check
What's verified: STUD verifies structure and internal consistency of the register, not the truth of its contents. Specifically, STUD verifies: the submission is a JSON object of at most 200000 characters with at most 200 items; company and round_stage are non-empty strings; items is a non-empty array where every item has a non-empty id, category, question, and status plus a string answer; ids are unique; every status is exactly one of: answered, na, pending; every category is exactly one of: financing, technology, product, market, business_model, team, financials_returns; every answered item has an answer of at least min_answer_chars characters after trimming whitespace (default 40, clamped to 1-2000); each required category has at least min_per_category answered items (default 1, clamped to 1-20); at least min_items_total items are answered overall (default 7, clamped to 1-200); no item in a required category is left pending; evidence_refs, when present on an item, is a list of non-empty strings; and category_coverage is present as a list where each answered_count equals the answered count recomputed from the items. That recount is the ONLY arithmetic checked: no valuations, totals, or financial figures inside the answers are computed or verified. Names in required_categories outside the seven-name list are dropped, and an empty selection falls back to all seven. STUD does NOT verify that any answer is true, accurate, or complete, that evidence_refs point to real documents, that the questions match what a specific investor will ask, or that meeting the length floor makes an answer substantive. company, round_stage, company_context, and known_gaps are operator context only and never change the machine verdict.
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