Deck reader

A deck lands. You flip through it on your phone, between two other things. A team that looks solid, a market that sounds big, a nice curve. You remember the founder's energy and two figures. What you do not remember is what was not there.

And that is what matters: how many users were interviewed, who is full-time, what was tested and then dropped, where the figure on page 5 comes from. You would ask every one of those questions if you had an hour per deck. You have ten minutes.

The reader asks them for you. It hands you a report, next to the deck: what is missing, what does not hold, and the questions to ask the founder before the call.

Why the gaps are invisible

A deck is built to show what is going well. The founder spent weeks on it, and every page was reworked to convince. The gaps sit between the pages, and to the naked eye you do not see them.

Once the company has customers, at seed, the problem changes shape. There are figures, and a figure on a page is reassuring: a monthly revenue, a retention rate, four named customers. What the page does not say is where it comes from, and whether it still holds once you open the billing export.

At series A there are one or two years of figures, and the question changes again. No longer "does anyone pay", but "does the machine repeat": does the next customer cost the same as the last one, bring the same, sign without the founder in the room? That does not show on a page. It shows in a monthly P&L and in cohorts.

Then, from series B to series D, the question shifts again: does the machine hold without the founders, does it hold without new money, is it ready to change hands? What answers is the past of the deck: what the boards promised each quarter, against what the P&L delivered.

What the reader does

A PDF goes in, a report comes out. In between, eleven steps, each one isolated from the others so the AI cannot make up what is missing. On the right, the report of a fictional deck fills in as the steps go by.

You givedeck.pdfand, from seed on, the documents behind its figures

You getdeck.reading.pdfand the same reading as markdown, next to the deck on your disk

First, for every deck
1. The PDF is transcribed page by page, and every sentence keeps its page number. That is what makes quoting possible.
  Headerpreseed-deck.pdf · 12 pages · read on 2026-09-08Quotes verified against the PDF text layer
2. Sector, business model, announced stage, each with its quote. The stage picks the list of questions: 24 before the first customers, at pre-seed, 26 once there are some, at seed, 32 to 48 from series A to series D. Before customers, we look for what the founder learned in the field. After, who pays and who comes back. Then whether the machine repeats, whether it holds without the founders, without new money, and whether it is ready to change hands. The business model adjusts the list: a marketplace, a hardware company or a biotech do not get the questions of a SaaS. A later round, series E, growth or pre-IPO, is read with the series D grid.
if pre-seed
series A to DFrom series A to series D, it demands the documents before reading
1. Always the same list for a stage: six documents at series A, twelve at series D, over 24 to 60 months of figures. The monthly P&L, the cohorts, the CRM export, the cap table, the three-year financial model, the contracts of the top customers, then, round after round, the audited accounts, the board packs, the org chart, the billing export, the auditor's letters. Every annex received is sorted into its slot, with a quote the code checks. One document missing, or too short, and it stops there: no reading, but the email that asks for it, document by document. There is no coverage threshold, the list is the gate.
seed to series DIf the company has customers, it checks its figures
1. Every verifiable statement, one per line: figures, named customers, competitors, founders, past funding. Page and quote each time.
2. Revenue export, cohorts, financial model, cap table: every deck figure is looked up in them. Under 25% off, noted with no penalty. Up to double, a question for the call. Beyond that, blatant. With no documents, it stops and drafts the email that asks the founder for them. At series C and D, the plan promised to the boards is looked up next to the actual in the P&L, quarter by quarter.
3. Only for what a document cannot settle: a named customer, a competitor, a founder's track record. It searches for and against, and only concludes with two independent sources. Otherwise it writes "unverifiable" and makes nothing up. From series A to series D the list grows at every round: public reviews, job posts, the LinkedIn profile of every executive, the accounts filed at the registry, the pricing page history, the price of past rounds, the last IPOs of the category.
4. Before calling anything false, a second AI, which has seen none of the rest, looks for an honest explanation: a date, a unit, a scope. With one, it becomes a question for the call. Without one, it stops and shows you the sources on both sides. Everything read so far stays in the report, and you decide.
Then, for every deck
1. The questions are grouped by theme: team, market, evidence, money. Each theme is read by an AI that sees only its own questions. No way to excuse a gap on the team side with a nice sentence on the market side. Every answer is found, partial or absent, with the page and the exact quote. A quote that is not word for word in the deck is rejected. A figure that is not on a page does not exist.
  Read the pre-seed questions ↗Read the seed questions ↗Read the questions, series A to D ↗
2. On borderline questions, two readings of the same deck do not always agree. When the result lands in the grey zone, between 65 and 80%, it reads twice more and keeps the majority answer. Disagreements stay marked in the report.
series A to DFrom series A to series D, it puts the benchmarks and the tables next to the figures
1. For the model and the stage, public orders of magnitude, each with its source and date: what a net retention, a CAC payback or a burn multiple is worth at that round. They show next to the deck figure and never enter the score. When no dated source exists, the cell stays empty. At series C and D, tables filled by code are added: the plan of the last eight to twelve quarters against the actual, the liquidation preference stack, the last IPOs of the category. Laid out, never summed, never valued.
Finally, for every deck
1. The score is the share of questions the deck answers, each theme weighing according to the stage: before customers, team and field count the most; after, traction and economics; from series A to series D, unit economics and net retention, then efficient growth, then profitable growth, and predictability. The report is written by an AI that sees only the answers, never the deck. It cannot be charmed by a good page 3.

deck.reading.pdfSTEP 01 / 11

Headerpreseed-deck.pdf · 12 pages · read on 2026-09-08Quotes verified against the PDF text layer

Deck profileAnnounced stage: pre-seed · p. 1 · "Pre-seed round - September 2026"B2B · monthly subscription per site · p. 7 · "the plant director signs the subscription"

Required documentsCohorts 13 months · CRM export · model 36 months · contracts of the top 10 customers: presentMonthly P&L: 18 months, 24 required · cap table: absentStop before reading · email draft, document by document

What the deck states"42 paying customers as of August 2026" · p. 5"Customer acquisition cost: 900 EUR" · p. 7

What backs itCustomers: deck 42, revenue export 38 · 10% gap, minor, no penaltyCAC 900 EUR: no annex · document to requestDocuments still to request · marketing spend and CRM export behind the CAC, with the email draft

Named customersFerrolux SAS, Metalpro Ouest, Bricard Fonderie, Atelier Vion · p. 5Searched for and against · two distinct domains to conclude, otherwise unverifiable

Gaps to probe in the callAbove double, or a fact that cannot be found: second independent reviewerNo honest explanation: stop, sources on both sides, everything read is kept

Question A4How many users did the founder interview, and what do they say? partial · p. 4"We interviewed 14 purchasing managers between March and June 2026"Gap: no word-for-word quote from a purchasing managerB4 · What was tested and dropped? absent

Verification passesCompleteness 68.9%, inside the 65-80% band: 3 passes, median per questionA2 unstable · partial, found, found

Benchmarks, SaaS at series ANet revenue retention · 100% baseline, 110 to 120% competitive, 120% or above premium · CRV, 2026-03-31Burn multiple · below 2.0x by series A, the strongest closer to 1.0x · CRV, 2026-03-31Sales cycle by segment · no dated source

Deck completeness

A Problem and field87.5 %

B Evidence70 %

C Economics75 %

D Market and timing33.3 %

E Team50 %

F Money and next step100 %

Weighted global 68.9% · red block: D. Market and timingFor the call · [E3] Are Lena and Marc full-time on Gantrix, and since when?

The weights and the computation, stage by stage

The computation fits in three lines, and code does it. Per question: found is worth 2 points, partial 1, absent 0, multiplied by the weight of the theme. Per theme: points obtained over the maximum possible, as a percentage. Global: the average of the themes, weighted by their weight. A theme under 50% turns red and produces a question for the call, not a judgement.

What changes from one stage to the next is what weighs. The weights are public and dated, and they will move at the first reviews.

24 questions

Pre-seed

What did the founder learn in the field?

Pre-seed	Weight	Share of score
AProblem and field	3	21%
BEvidence	3	21%
CEconomics	1	7%
DMarket and timing	2	14%
ETeam	3	21%
FMoney and next step	2	14%

See the full computation↗

26 questions

Seed

Who pays, and who comes back?

Seed	Weight	Share of score
AProblem and customer	2	13%
BTraction	3	20%
CEconomics	3	20%
DMarket and competition	2	13%
ETeam	2	13%
FMoney and next step	2	13%
GReferences	1	7%

See the full computation↗

32 questions

Series A

Does the machine repeat?

Series A	Weight	Share of score
AProblem and customer	2	12%
BTraction	2	12%
CUnit economics	3	18%
DNet retention	3	18%
EMarket and competition	2	12%
FTeam	2	12%
GMoney and next step	2	12%
HReferences	1	6%

The business-model block adjusts these weights: a biotech puts traction at 0, a hardware company doubles economics.

See the full computation↗

41 questions

Series B

Does it hold at scale, without the founders?

Series B	Weight	Share of score
AProblem and customer	1	6%
BTraction	2	11%
CEfficient growth	3	17%
DRepeatability	3	17%
ENet retention	2	11%
FMarket and competition	2	11%
GLeadership and organisation	2	11%
HMoney and next step	2	11%
IReferences	1	6%

See the full computation↗

45 questions

Series C

Does it hold without new money, and keep its place?

Series C	Weight	Share of score
AProblem and customer	1	6%
BTraction	2	11%
CEfficient growth	3	17%
DPosition and durability	3	17%
ENet retention	2	11%
FMarket and competition	2	11%
GLeadership and organisation	2	11%
HMoney and exit	2	11%
IReferences	1	6%

See the full computation↗

48 questions

Series D and later

Is it ready to change hands, and why this round?

Series D and later	Weight	Share of score
AProblem and customer	1	6%
BTraction	2	11%
CProfitable growth	3	17%
DPredictability and exit readiness	3	17%
ENet retention	2	11%
FMarket and competition	2	11%
GLeadership and organisation	2	11%
HThe round and the exit	2	11%
IReferences	1	6%

Series E, growth, pre-IPO: the same grid.

See the full computation↗

What you get

A report, as PDF and as markdown, next to the deck on your disk. Inside: one bar per theme. Question by question, the answer, the page, the quote. The three main gaps, ranked by weight. Then the questions for the call, worded as such: "Are Lena and Marc full-time on Gantrix, and since when?"

If the company has customers, add every deck figure with what confirms or contradicts it, the gaps to probe in the call, and the ready-to-send email asking for the missing documents. You send it, or you do not. From series A to series D, every figure has its benchmark next to it, source and date included. At series C and D, the plan against the actual, quarter by quarter.

What it does not do

It does not say whether to invest, and it never gives a valuation. The score measures whether the deck answers the questions, not whether the company is good. A complete deck can describe a bad company, and a founder who presents poorly is not a founder who did nothing. Only a conversation tells those apart.

It makes nothing up. The thresholds, the score computation and the quote checks are done by code, not by an AI. It only blocks a reading on a proven contradiction or a missing document, never on something vague. It never sends the email. Nothing leaves your disk except the web searches, which carry the text of the statement and never the deck.

It has limits, and they are written down. Text that only exists inside an image or a chart cannot be cited: it counts as absent. A customer with no public trace is unverifiable, not contradicted. The thresholds are a first setting. They are public, and they will move.

The questions are dated and public, and every reading is kept. At eighteen months, we look at what the companies became and publish the result, flattering or not.