PitchScan/AI pitch deck review
AI Pitch Deck Review
A VC gives your deck about three minutes and one read. An AI committee gives it every number on every slide, cross-checked against each other. Here is what that catches, and what it honestly cannot.
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01 · What AI sees
The hurried human reads slides. The AI reads the deck.
Four classes of findings that surface almost exclusively under machine-grade attention.
- CATCH 01 Cross-slide contradictions. Your gross margin on slide 6 disagrees with the model on slide 11. A skimming partner misses it; a diligence associate finds it three weeks later, at the worst possible moment.
- CATCH 02 Driverless projections. Revenue that grows 14x without a visible engine: no pipeline math, no pricing lever, no hiring plan that supports it. The committee recomputes what your numbers imply and flags what does not follow.
- CATCH 03 Market construction errors. Top-down TAMs, wedges wider than the product, segments that quietly change definition between slides. The math gets checked, not admired.
- CATCH 04 Strategic avoidance. The claims your deck carefully does not make: no churn number, no competitor named, no CAC. Silence is legible to a machine that knows what should be there.
02 · The honest part
What AI cannot review.
An AI review reads the document, not the founder. It cannot score your delivery in the room, the trust you have built with an investor, the quality of your intro, or market intelligence that lives in someone's head rather than your PDF. It will not tell you whether a specific partner at a specific fund will lean in, and it is not investment advice.
That boundary is exactly why it works as a rehearsal tool. Everything inside the PDF gets the most thorough cold read it will ever receive, from five adversarial archetypes instead of one polite chatbot. Everything outside the PDF stays yours to rehearse, with the objections already on the table instead of arriving mid-meeting.
03 · How it works
Machine attention, committee judgment.
Parse
Every slide read in full: text, numbers, charts, omissions.
Cross-check
Numbers and claims verified against each other across slides.
Debate
Five VC archetypes argue the weak points and vote.
Report
Score, grade, and top findings in under 2 minutes, free.
04 · FAQ
AI review questions.
Can AI actually review a pitch deck?
Yes, for the parts of review that are pattern work: checking whether numbers agree across slides, whether projections have drivers, whether the market is built bottom-up, whether the ask matches the plan. PitchScan runs that through five adversarial VC archetypes rather than one chatbot, so weak points get argued, not politely summarized.
What does an AI review catch that a human reviewer misses?
The cross-references. A partner skimming your deck between meetings will not recompute your slide 8 revenue against your slide 12 hiring plan. The AI committee reads every number on every slide and checks them against each other, which is where contradictions hide: margins that drift between slides, a TAM that shrinks in the appendix, growth that outruns the team.
What are the limits of an AI pitch deck review?
Real ones. It cannot judge your delivery in the room, your reputation with the investor, warm-intro dynamics, or private market knowledge that is not in the PDF. It reviews the document, not the founder, and it is not investment advice. Treat it as the most thorough cold read your deck will ever get, then rehearse the human parts separately.
Will my deck be used to train AI models?
No. Your deck is used only to generate your report. It is never used for model training, never shared with third parties, and you can request deletion at any time.
Humans skim.
The committee reads everything.
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