InpaintKit – A plugin let you use latest AI models in Photoshop

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Recently, many people have been building new tools around the latest AI image editing models like Google Nano Banana and Seedream 4, mostly for use on the web. Personally, I still prefer working in my familiar environment, Photoshop. So I decided to write a plugin that lets me use these models directly inside Photoshop, following a workflow similar to "Generate Fill." I've been using it with my team, and it works well so far. Because of rapid development, it currently only supports Photoshop 24.2.0 and above. A few teammates still use CS6, so I plan to add support for CS6 in the future. With the latest Photoshop release, I noticed they added Nano Banana too. But I think my plugin still has an advantage when it comes to the speed of adopting new models, so I believe there's still a place for it. You can have a look at a quick demo here: https://www.youtube.com/watch?v=ryXX23Hjtxs

Visit product View on Hacker NewsSep 30, 2025

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89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released

34%34% 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

16%16% 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.

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