Why I Started Building an AI Image Toolkit Instead of Using Existing Ones

Tirkish — Mon, 13 Jul 2026 09:13:42 +0000

A few months ago, I kept running into the same problem.

Every time I needed to do something simple with an image—compress it, resize it, remove the background, or upscale it—I ended up opening a different website. Some had upload limits. Some added watermarks. Others were surprisingly slow or required an account before you could even try them.

None of that felt necessary.

So I started building my own collection of image tools.

The original goal wasn't to create another "AI platform." It was simply to make everyday image editing faster and less frustrating.

As I kept adding features, I realized every tool had its own set of challenges.

Background removal meant finding a model that was accurate without being huge. Image compression required balancing file size against visual quality. Upscaling had to improve detail without making photos look artificial. Batch processing introduced a completely different set of performance issues.

One thing I learned quickly is that image processing isn't only about AI. A lot of the work is performance optimization, browser compatibility, memory management, and designing an interface that doesn't get in the user's way.

Another lesson was that users don't care which model or framework you're using. They care whether the tool works, finishes quickly, and produces a result they're happy with.

I'm still improving the project almost every day. There are plenty of features I'd like to add, and just as many things I'd like to improve.

Building it has been a reminder that shipping something useful teaches you far more than endlessly planning the "perfect" product.

If you're building your own side project, I'd be interested to hear what technical problem surprised you the most once real users started using it.

DEV Community: Tirkish

Why I Started Building an AI Image Toolkit Instead of Using Existing Ones