A Notion-like platform for building interactive models

Hacker News

Hey HN. I wanted to share an update to our previous thread, “Notion with problem solving capabilities”. The Decipad public beta is now live. You can try it for free here. https://www.decipad.com/ We started building Decipad to make numbers more expressive and playful. It’s a notebook environment where you can combine text, numbers, data and calculations into a story. Our goal is to help people communicate with numbers more effectively and collaborate across diverse backgrounds. It’s feels a bit like Notion, but it’s for building interactive models and reports. A few things we’ve been addressing building Decipad… - A friendly modelling experience: You can express variables and calculations with quasi-natural language and connect them with tables, charts, pivot tables and other widgets. - Unit expression: we built Decipad on a powerful unit system. You can assign labels and units to your data, like, `Cost = $5 per month per seat.` - Dimensional Categories: Expressing relationships between variables and categories, making a model easy to adapt. We wrote about it here: https://www.decipad.com/blog/breaking-the-grid-overcoming-di... - Connecting Data: Ability to connect data sources directly to your notebook. Right now, it’s intended for technical users. You can use JS and SQL to run a query. We’re still exploring several areas like support for large data sets and building more UX interactions on top of our language to make modeling even more approachable and collaborative. We would love to get feedback or any thoughts on our approach.

Visit product View on Hacker NewsJul 31, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, models · Missing: mac, agents, macos

93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

68%68% 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, friendly, users · Missing: plus, intuitive, reviews

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, users, widgets · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · 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 · Strong signals: collaborate · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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