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I made a simple tool to get P&Ls and valuation for projects

Hacker News

I made a simple tool to get P&Ls and valuation for projects

Hey HN, In late March, I tried to have a quick overview of the profit of my 9-5 (boring) company, and it was a nightmare. I had to ask my accountant to have an extraction, that unfortunately, was 99% complete (8 invoices were missing) so : no extraction, no overview, and nothing was possible. So I learned to code and made super easy to use tool to plug income, expenses in seconds, and have a P&L (with company valuation). Hope you'll find it useful. Greg

Visit productView on Hacker NewsApr 30, 2024
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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: lua, io · Missing: https docs, excited, just released
66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos
48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
27%27% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: profit · Missing: arr, mrr, revenue
24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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