Score · Assess & Decide · Analysis & Finance
Pitch readiness score across the six due-diligence gates
An honest readiness scorecard over your own answers: each of the six investor due-diligence gates is marked covered or gapped against a disclosed character floor, every gap is surfaced by name, and a 0 to 6 readiness score is recomputed from the answers, never self-asserted.
You receive: A JSON scorecard: your company, one-liner, and stage, six gate sections (Technology, Team, Market, Manufacturability, IP, Competition) carrying your intake answers verbatim, per-gate coverage booleans, a named gap list, and an integer readiness_score. Coverage, gaps, and the score are recomputed by the validator; an answer left blank or under the floor is scored as a gap, not rejected.
Part of Pitch Investors
Example
A sample of what this play produces. Your result is generated for your inputs.
- Company
- STUD.com
- One liner
- STUD is a living system for your venture: it knows your business, does the work, and learns from every result.
- Stage
- pre-seed
- Readiness score
- 5
Sections
- Technology
- Tech what
- STUD.com gives a venture a living system: a workspace that holds what the business knows, a catalog of ready-made plays that AI agents run from a short intake, and results that land structured, stay current, and feed the next play. A fact stated once flows into every run, and every deliverable passes its play's acceptance check before it lands.
- Tech maturity
- in-production
- Tech proof
- The platform is live at stud.com in a pre-revenue soft launch: 265 plays across 14 playbooks settle against machine acceptance checks, every production deploy applies schema and catalog automatically, and STUD runs its own strategy work as settled runs on the system it sells.
- Tech risk
- The biggest remaining risk is deliverable quality beyond the machine floor: an acceptance check proves a deliverable is structurally complete, not that it is true or good. The plan to retire it: paired independent audits on every judgment-bearing play, and a tuning program that turns audit verdicts into a reward signal for the authoring models.
- Team
- Team founders
- Dan Schmitz, solo founder. He built the full stack (the play catalog, the acceptance-check judge, the deploy pipeline) and operates it daily. The company dogfoods the system it sells: every strategic artifact STUD ships, including this scorecard, is produced and settled on STUD itself.
- Team gaps
- The team is one founder-operator with concierge capacity of about 30 plays a week. Missing roles: a growth lead to run content-led acquisition and a founding engineer to scale the judge and catalog. Both hires are planned against the $1,000,000 target raise (illustrative target, not a committed raise).
- Market
- Market who
- Solo and early-stage founders and small product teams who need marketing, finance, product, and engineering work done while staying small, and secondarily ops and engineering leads adopting AI agents.
- Market size
- The AI agents market is about $8B in 2025, growing 42 to 50 percent CAGR (cited external estimates). Bottom-up (illustrative): at $300 average annual revenue per account, the $250,000 revenue objective needs roughly 830 paying accounts, a thin slice of the solo and early-stage ventures formed each year.
- Market pain
- AI can produce real knowledge work, but getting that work out of it is still manual craft: you have to know what to ask, phrase it well, re-explain your business in every session, and carry the output somewhere by hand before it goes stale. Every session starts from zero, so nothing compounds. Willingness-to-pay signal: buyers already pay $20 to $200 a month for AI subscriptions that leave all of that craft on the buyer.
- Manufacturability
- Mfg path
- The product is software with a concierge fulfillment layer: plays run from a short intake at 250 to 1,000 credits each ($10 to $40, most at 500 credits or $20), paid from prepaid credit packs (500 credits for $20 up to 5,000 credits for $200; purchased credits never expire), at a modeled gross margin of 85 to 90 percent (estimated 87). Scale-up replaces founder concierge capacity with autonomous agent runs settled by the acceptance checks.
- Mfg constraints
- The binding constraints are founder-operator concierge capacity (about 30 plays a week) and inference cost per run. Both are retired by the same lever: moving fulfillment from concierge to autonomous settled runs, which the acceptance-check harness that already gates every deliverable was built to make safe.
- IP
- Ip position
- No patents. The assets STUD owns and protects: the catalog of 265 plays with hand-built acceptance checks, the workspace fact graph that compounds per customer, and the growing audit corpus the tuning program treats as a proprietary reward signal. Each is slow, judgment-heavy work to replicate.
- Competition
- Comp who
- General-purpose AI chat assistants (the blank prompt box), freelance marketplaces, and static documentation tools. None of these compound: a chat session starts from zero, a freelancer's context leaves with the freelancer, and a document goes stale the day it is written.
- Comp moat
- The moat is the compounding living system: a fact stated once flows into every run, every result feeds the next play, and every settled run adds to a reward corpus that tunes the models. Switching cost grows with each run a buyer makes, and the acceptance-check catalog took a year of judgment-heavy authoring to build.
Coverage
- Technology
- true
- Team
- true
- Market
- true
- Manufacturability
- true
- IP
- false
- Competition
- true
Gaps
- ip_freedom
Opens soon
STUD opens runs for everyone soon, on every play at once.
Scope of the check
What's verified: STUD verifies the scorecard parses as a JSON object of at most 100,000 characters with exactly the six gate sections (Technology, Team, Market, Manufacturability, IP, Competition), coverage flags, a gap list, and a readiness score; that every gate answer on the scorecard equals the answer you gave at intake (only letter case and extra whitespace may differ, and an answer you left blank must stay blank); that stage and technology maturity carry one of their listed options; that a written answer counts toward coverage only when it reaches the covered-answer floor (default 120 characters, yours if you set it, accepted range 40 to 600), while the maturity selection counts once a valid option is chosen; that the coverage flags and the gap list exactly equal what STUD recomputes from the answers, so a hidden, padded, or mislabeled gap is rejected; that the readiness score is an integer equal to the recomputed count of fully covered gates, 0 to 6; and that the company name, one-liner, and stage you provided are echoed on the scorecard. STUD does NOT judge whether your answers are true, substantive beyond the character floor, or investor-ready: the floor is a length rule, not a quality read, and a covered gate means a long-enough answer is present, not a good one. Whether the venture is fundable stays your judgment and your investors'.
Get early access to STUD the day it goes live.