No black box. Every number traces to confirmed deal facts — amounts, stages, stage win rates that become yours as deals close — and every headline number has an ⓘ that shows exactly how it was computed.
The revenue forecast is built from your pipeline and nothing else: real deal amounts, weighted by each stage's win rate — standard to start, yours stage by stage as your deals close. Expected revenue is closed revenue plus every open deal at its stage's rate, and the ⓘ beside it shows that sum deal by deal, with where each rate came from. When someone asks “where does that come from?”, you point at the math.
Beside the headline forecast sits its own record: how Expected revenue and what your calls say — closed revenue plus every deal the calls put in commit, never blended into the model — moved day by day against what closed and the target, and for every completed month, the day-one forecast next to the real number. Under it, coverage against the target, run rate, and whether each stage's win rate is your own history or still estimated. A likely range simulated 3,000 times sits under the headline.
One engine, three vantage points. A rep forecasts their own book; a founder sees the whole business with each team one toggle away — same math underneath. No more three spreadsheets telling three stories.
The forecast turns on at 15 closed deals — importing your deal history counts — and starts with standard stage weights. Then it gets personal: as more deals close, the win rates recalibrate to your business, your market, your motion. No data scientist, no model to babysit. And it keeps score on itself: every month, what the calls said, what was expected, what actually closed, and whether the range held.
On the first morning of every quarter, a written forecast for the quarter ahead is already waiting — for the business, for each team and each rep with open deals. Nobody asks for it and there is no button to press. It reads the same pipeline the numbers come from and says what the quarter looks like, which deals decide it, and what is at risk.
From the second one on it also grades the last: what was forecast on day one against what actually closed. That is how you learn whether to trust the number.
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