Why I Built ImgSolve: Making Everyday Image Tasks Simpler

ImgSolve — Fri, 21 Aug 2026 07:38:07 +0000

Images are everywhere, but working with them is often more complicated than it should be.

People need smaller or correctly formatted images for:

Online applications
Email attachments
Government forms
Website uploads
Profile pictures
Social media posts

Many existing tools make users guess the correct quality, dimensions, or compression settings. I wanted to create something simpler.

The idea behind ImgSolve

I started building ImgSolve around one guiding principle:

Simple tools should feel simple.

The basic experience should be straightforward:

Choose what you need.
Upload an image.
Process it.
Download the result.

Users should not need to understand compression algorithms or image encoding settings to complete an everyday task.

What ImgSolve currently offers

ImgSolve provides browser-based tools for:

Compressing images to specific target sizes
Converting HEIC images to JPG
Converting between JPG, PNG, WebP and other formats
Resizing images for websites, forms and social platforms

One feature I have focused on is target-size compression. Instead of asking users to select an unclear quality percentage, the tool lets them choose a practical result, such as 20KB, 50KB or 100KB.

Why target-size compression is interesting

Compressing an image to a target size is more involved than simply setting JPEG quality once.

A basic approach is:

while (result.size > targetSize) {
  reduceQuality();
  encodeImageAgain();
}

A better implementation can search between quality values, keep the best result under the target, and reduce the image dimensions only when quality adjustment is not enough.

This creates a better balance between:

File size
Image dimensions
Visual quality
Processing time

Privacy matters

Images can contain personal documents, family photos and other sensitive information. That is why ImgSolve is designed as a privacy-first toolkit, with supported image processing performed locally in the browser.

Browser-based processing can also make the experience faster because users do not need to wait for an image to be uploaded to and downloaded from a remote server.

What I’m learning

Building ImgSolve is helping me learn more about:

Browser image-processing APIs
File formats and encoding
Performance optimization
Product design
Technical SEO
npm package publishing
Building tools around real user outcomes

I’m also working on small open-source npm utilities based on practical image tasks, including target-size compression and HEIC-to-JPG conversion.

What comes next

I plan to continue adding useful image tools while keeping the interface focused and easy to understand.

If you work with browser-based image processing or regularly use image utilities, I would appreciate your feedback.

You can try the tools at ImgSolve.com.