How We Reduced AI Background Removal Time from 18 Seconds to Nearly Instant: Lessons from Building MakeMyVisuals

The team behind MakeMyVisuals reduced AI background removal time from 18 seconds to near-instant by optimizing image preprocessing, caching, and UI responsiveness. Key improvements included adaptive resizing, offloading work from the main thread, and caching intermediate AI results. The project demonstrates that significant performance gains often come from outside the AI model itself.

When we started building MakeMyVisuals, our goal wasn't just to remove image backgrounds—it was to create a tool that felt fast enough for everyday users. No one enjoys waiting 15–20 seconds just to edit a single image. Whether you're an e-commerce seller removing backgrounds from product photos or a designer creating transparent PNGs, speed matters just as much as accuracy. Here's what we learned while optimizing our AI image processing pipeline. The Initial Problem Our first implementation worked well. The AI accurately segmented subjects, handled complex edges like hair, and produced clean transparent backgrounds. The downside? Large upload times Heavy image preprocessing Slow AI inference Unoptimized output generation For high-resolution images, the complete workflow could take far longer than users expected. That wasn't acceptable for a modern web application. Bottleneck 1 — Uploading Massive Images Most smartphone photos today are between 5 MB and 20 MB. Many users uploaded images directly from modern phones with resolutions exceeding 4000×3000 pixels. The AI didn't actually need every single pixel. Solution Instead of processing the original file immediately, we: Read image dimensions first Generated an optimized working copy Preserved the original for export Sent only the required resolution to the AI model This significantly reduced unnecessary computation. Bottleneck 2 — Blocking the User Interface Initially, preprocessing happened synchronously. That meant users watched a loading spinner while the browser resized large images. Not a great experience. Solution We moved expensive operations off the main thread. This kept the UI responsive while background processing continued. The result felt dramatically faster—even before total processing time changed. Sometimes perceived performance matters as much as raw performance. Bottleneck 3 — Processing Images Larger Than Necessary Many uploaded photos contained far more detail than required for segmentation. Running the AI against extremely large images wasted GPU resources. Solution We introduced adaptive resizing. Instead of using a fixed resolution, we calculated an optimal size based on: Original dimensions Subject size Required output quality The AI processed fewer pixels without noticeably affecting quality. Bottleneck 4 — Repeated Processing Users often downloaded multiple versions of the same image. Originally, every export triggered another processing cycle. Solution We cached intermediate AI results. Only the final rendering changed. That eliminated redundant work and reduced repeat processing times. Bottleneck 5 — Sending Too Much Data Large PNG files are expensive to generate and transfer. Instead of producing oversized outputs every time, we optimized export generation by: Compressing transparent PNGs Optimizing metadata Generating only required image sizes Smaller outputs meant faster downloads. Performance Isn't Just About AI Most optimization came outside the AI model. We found improvements in: Image preprocessing Browser rendering Memory management Network transfer Export generation Caching The AI itself was only one piece of the puzzle. Real User Experience Matters When people upload an image, they don't care which neural network you're using. They care about three things: Does it work? Does it look good? Does it finish quickly? Optimizing those small steps made the biggest difference. Building MakeMyVisuals These optimizations are part of what powers MakeMyVisuals, an AI-powered platform for image editing, optimization, and document processing. Besides background removal, the platform includes tools for: AI Product Photo Enhancement Image Compression Image Resizing Format Conversion AI Portrait Editing Document & PDF Processing Explore the platform here: Background Removal Tool: 👉 https://makemyvisuals.com/background-tools https://makemyvisuals.com/background-tools Image Optimization Tools: 👉 https://makemyvisuals.com/optimization-tools https://makemyvisuals.com/optimization-tools Format Converter: 👉 https://makemyvisuals.com/format-converter https://makemyvisuals.com/format-converter Document Tools: 👉 https://makemyvisuals.com/document-tools https://makemyvisuals.com/document-tools Product Photo Studio: 👉 https://makemyvisuals.com/ecommerce-tools https://makemyvisuals.com/ecommerce-tools Final Thoughts Building AI products isn't only about choosing the best model. It's about removing every unnecessary millisecond from the user journey. Sometimes the biggest performance gains come from optimizing everything around the AI—not the AI itself. What performance optimization had the biggest impact on your projects? I'd love to hear your experience in the comments.