Built a desktop valuation app (DCF / DDM / reverse DCF) so I'd stop rebuilding Excel models for every pitch — would value some ER feedback

Long-time lurker. Full disclosure up front: this is my own tool, so flag it if self-promo isn't allowed here — but I think it's genuinely relevant to the people in this forum building pitch and interview models, and what I actually want is methodology feedback.

I kept rebuilding the same DCF in Excel for every company I looked at, and the models got fragile fast — one bad cell reference and the valuation's quietly wrong without you noticing. So I built Aperite, a native desktop app with a C++ engine that puts three models in one place:

• standard DCF for mature businesses
• a Dividend Discount Model for banks/financials, where FCF models fall apart
• a probability-weighted DCF that blends bull/base/bear cases by likelihood instead of betting everything on one forecast

It also has a WACC builder (CAPM cost of equity, after-tax cost of debt, target D/E), a reverse DCF that backs out the growth rate the current price is implying, a historical CAGR/YoY analyzer for baselining projections, and one-click PDF export of the full model — which I'd guess is the most useful part for anyone here putting together a stock pitch for interviews or a pitch competition.

What it deliberately doesn't do: pull live data or auto-fill financials. You enter the assumptions yourself, by design — the point is to force you to reason about the inputs, not hand you a number. So it's a modeling tool, not a screener.

Caveats: Windows-only right now (Mac/Linux on the roadmap), €9.99/mo with a 7-day trial if anyone wants to poke at it.

What I'd genuinely value from this forum: tear apart the methodology. Does the probability-weighting match how you'd actually risk-adjust a forecast? Is the reverse-DCF implementation sound? Anything in the terminal-value or WACC handling you'd do differently? I'd much rather have the math criticized than be told it looks clean.