Pi

Pixweave – 2×/4× upscaler with CMYK print sizes (Postcards/A4/A3)

Hacker News

Pixweave – 2×/4× upscaler with CMYK print sizes (Postcards/A4/A3)

I built Pixweave to make “print-ready” upscaling simple for artists, illustrators, and POD sellers. What it does: clean 2×/4× upscales and one-click CMYK exports in common print sizes (Postcards, A4, A3) — all in the browser. Why: going from a nice web image to something you can actually print (right size, right color space) is still too fiddly for many non-technical creators. What’s different: the tool is focused on print workflow, not just pixels — choose size, get CMYK, download. The free tier works without sign-in; paid plans unlock larger limits. Would love feedback from the HN crowd on: missing sizes you rely on, CMYK expectations, edge cases (thin line art, gradients), and overall UX.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
45%45% 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
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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 · Strong signals: paid · 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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