Diagramming app for power users (Finegram)

Hacker News

Hello all, this is still quite an early release, but it's starting to be a proper diagramming app. At this point I call it a beta release and would love to get feedback from potential users. Highlights: - Fully offline and standalone desktop app - SVG file format - Better usability and workflow than alternatives I've written about these points and more (incl. what Finegram is not) in the linked blog post. You can download the app at https://finegram.com/downloads There's also a User Guide with videos of all the features: https://finegram-releases.ams3.cdn.digitaloceanspaces.com/0.... I'd be super happy to hear your thoughts on this project.

Visit product View on Hacker NewsOct 25, 2023

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Hacker NewsStrong engagement from HN community · Strong signals: ide · 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.

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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

37%37% 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

15%15% 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.

Correct prediction on native model

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