Two things happen in a partner's head during a pitch: “do I believe this team can win this market?” and “what is this worth, and what do I own for my check?” This tool runs both — two ways in. Hand Claude a deck for a full assessment, or drive the Scorecard and Valuation Lab yourself. The rubric is built from how funds diligence, distilled through the pitch decks that actually raised.
Upload your deck and it comes back scored on all ten axes — with a valuation range, an executive read, and a prioritised list of what to fix. The report below is a worked example until your deck replaces it.
Drop a PDF (best) or export your slides to PDF / images. It’s scored on all ten axes in ~30 seconds and the report below fills in with your numbers. The file is sent for analysis and not stored.
Score each criterion 0–5 as you read the deck. Categories are weighted by what moves a seed decision. Weights re-balance when you switch stage — at pre-seed, team and “why now” carry the round; by seed, traction has to show up. Your scores also feed the Scorecard valuation method below.
Every popular way to put a number on a company with little or no revenue. The qualitative methods (Berkus, Scorecard, Risk Factor) set a pre-money floor; the forward methods (VC, DCF, First Chicago, Comps) triangulate against an exit. None is “right” — the discipline is triangulation. Adjust inputs; the blend at the bottom updates live.
Weighted across methods — qualitative floors weighted higher pre-seed, forward methods higher once there’s traction. The mid is your anchor; walk in citing the range and the methods behind it.
| Method | Type | Output | Read |
|---|
Answer a short series of questions — each one maps to how investors actually score a deck. At the end you get a Markdown brief plus a ready-to-paste prompt that has Claude write the deck for you.
The rubric isn’t invented — it’s reverse-engineered from the decks that raised. Two structural templates, two narrative engines, and the one lesson from each landmark deck.
| Deck | Stage / outcome | The one lesson |
|---|---|---|
| Airbnb ’08 | Seed · $600K | Ruthless simplicity. Problem→solution mirrored, one line per slide. |
| Uber ’08 | Pre-launch vision | Sell the vision and the wedge — “everyone’s private driver,” starting with black cars. |
| LinkedIn ’04 | Series B (Hoffman) | Analogy as compression — framed by what investors already understood (eBay, Google). |
| Dropbox | Seed | A demo beats a description. Show the magic; let it be obvious. |
| Front ’16 | Series A | Category creation — reframe the market so you’re the leader of a new one. |
| Buffer | Seed · $500K | Radical transparency — real metrics, real traction, builds trust fast. |
| Intercom | Early | Opinionated positioning — a manifesto, not a feature list. |
| Mixpanel | Seed | One sharp wedge — analytics done for one job, done better. |
| Coinbase | Seed | Make the unfamiliar legible — plain-language framing of a scary new market. |
| Early (pitch) | Lead with engagement metrics — retention and usage as the whole argument. | |
| YouTube | Seed | Growth curve as the pitch — the line goes up and to the right, unmistakably. |
The things that make an investor quietly close the tab. Every one is a subtraction from the score above — often a fatal one, regardless of the rest.