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Numbrz – Finally there's a platform for financial analysts

Hacker News

Numbrz – Finally there's a platform for financial analysts

We all know the problems with spreadsheets when using them to build complex models: sharing is difficult, sophisticated formulas are difficult to build and understand, etc. But we’re not here to speak ill of the spreadsheet. We think spreadsheets are great and we're making them even more powerful. NUMBRZ is a financial modeling platform that automates work traditionally done in spreadsheets. The simplicity of our no-code UI and fully visual macros allows subject matter experts to build sophisticated models that are fully automated. Check out our demo video of building with the Numbrz function canvas: https://www.loom.com/share/8cf53e99da63479b9eb79ec24feb1c98 We’ve built a community platform that: - Creates a paradigm shift from single individuals developing & operating models to teams. - Easily shares model IP within orgs, through the community catalog, and on the Numbrz Marketplace. - Helps team members easily review models with features like traceback. The Numbrz Marketplace - Facilitates the connection between customers and builders of models. - Because you build models as templates on the Numbrz platform, they’re easily shareable and reusable. - Model builders have the option to keep their model IP hidden when sharing. - This allows builders to easily distribute their models, without distributing their IP. These features don’t exist in spreadsheets because they weren't designed that way. That’s why we created the Numbrz platform. We think spreadsheets are great and we're making them even more powerful. We’re hoping you sign up for a free account at numbrz.com and let us know what you think. Thank you from the Numbrz team!

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, models · Missing: agents, macos, agent
93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: created, para · Missing: supports, reddit linkedin, podcasting
78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, ide, io · Missing: https docs, excited, just released
71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: platform, builder · Missing: plus, intuitive, reviews
54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, way, para · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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