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Canaster is a canvas based visual workspace

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Canaster is a canvas based visual workspace

Canaster is a canvas based visual workspace (think high performance hierarchical miro board). I had a particular vision for workspace I wanted where I can put my documents including pdfs/markdowns/tables/checklists in a visual hierarichal workspace. I started with a DOM based approach but that quickly hit its limits of responsiveness in terms on interaction, so i built this one with webgl and my main priority was a consistent 120+ fps rendering (you can see the fps number by clicking the (i) icon in the bottom right, the other buttons there are for refit/rearrange panels). You can drop pdfs/markdown files as it is organize them. Each 'panel' can the canvas can be maximised to interact with it and can inline edit with double clicking. You can also embed other websites (the ones which allow it) Workbooks can be private or public. Here are a bunch of documents I have created as a demo https://canaster.in/d/naruto-casefiles/how-come-these-three-... https://canaster.in/d/admin/thirty-six-views-one-mountain--0... (ps, documents have original images which can be large and depending on your location might be slow to load since its running on a single server in 1 location) there are more things I am adding like email to a workbook (each account gets their own email account @canaster.in) and can connect panes to each other (have not created a good demo for it yet) you can switch dark/light theme, and can set image for the panel/canvas background as well (cmd/ctrl + k to bring up the command menu). canaster is optimized for usage on mobile as well. https://x.com/phparth/status/2077397341674627470 (a screen recording from past when it was in dev)

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, visual, single · Missing: mac, agents, macos
90%90% 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, started, including · Missing: supports, reddit linkedin, podcasting
69%69% 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, including · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
53%53% 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
50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
18%18% 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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