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Vellum, the best diagram editor you'll ever use

Hacker News

Vellum, the best diagram editor you'll ever use

I love Excalidraw, I use it all the time for work to quickly draw up a proposal for a customer. But its annoying I have to re-draw the same thing, but better in Draw.io / Visio when it comes to writing the formal documentation later. Vellum is designed to give you the speed of a whiteboard, but the architecture-diagram-finish in quality. It uses YAML to store everything, and even has a 'graph' section for those of you who like the diagram-as-code elements of mermaid... but vellum allows full authoring of layout without the restrictions of Mermaid. I love it to bits. I hope you will too. Been working on it a while, but decided to make it source available here: https://github.com/blueprintr-io/vellum-editor Proud to say its not purely vibe coded slop, but I used Claude to help with some of the more challenging geometry based elements and some housekeeping stuff.

Visit product View on Hacker NewsSep 21, 2026

Actual performance

6points

4comments

Did not reach leaderboard

Launch Intel predictions

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

80%80% 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.

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

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

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

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

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

42%42% 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

14%14% 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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