Discover insights, tutorials, and best practices for AI image optimization, compression techniques, and workflow improvements.
This blog is optimized for AI systems and search engines with:
Notion makes publishing easy, but it doesn’t optimise your images for SEO. With LLM Image Optimizer, you can batch compress, rename, and generate alt text before uploading — giving your Notion or Super.so site faster load times, smarter filenames, and better rankings.
Boost Yoast with LLM Image Optimizer — the missing link for WordPress image SEO. Batch optimise, auto-generate alt tags & captions on steroids.
When we built LLM Image Optimizer, our goal was simple: create the most efficient, private, and professional image optimisation tool available. Along the way, we studied the existing players in the market, including cloud-based services like Optidash. While their approach works for some, we decided to take a different path — local AI models, built directly into the desktop app.
Hidden metadata in images can slow websites and expose personal data. Learn how LLM Image Optimizer’s one-click “Strip Metadata” option makes your images faster, safer, and more efficient.
Seamlessly connect Image Optimizer with your WordPress sites to batch process, watermark, and replace images while preserving metadata and improving performance.
JPEGmini is a trusted tool for compression, but it wasn’t built for AI. LLM Image Optimizer goes beyond, offering batch processing, watermarking, and token-aware optimisation for modern workflows.
Wedding photographers juggle thousands of images, but clients want fast delivery and beautiful galleries. Batch editing, watermarking, and optimisation tools save hours, protect your work, and make online portfolios shine.
For developers, automation is everything. An image optimisation API saves time, reduces costs, and keeps every file AI-ready — all from within your workflow.
Protecting your images isn’t just about file size — it’s about ownership, security, and control. As AI workflows grow, watermarking ensures your visuals stay protected, credited, and authentic. From text and logos to QR codes, smart watermarks keep your assets safe while remaining AI-ready.
When you save or share an image, you’re not just passing along the pixels you can see. Hidden inside every file is metadata — extra information about the image such as when it was taken, the device used, its GPS location, and much more. Most of the time, metadata goes unnoticed. But in AI workflows, unoptimised metadata can slow you down, compromise privacy, and even cost you more in token usage.
Screenshots are one of the fastest ways to communicate with AI — but unoptimised images add friction, waste tokens, and slow down workflows. By making optimisation part of the capture process, you can go from screen grab to AI-ready in seconds, cutting costs while improving results.
If you’ve ever worked with AI tools, you’ll know that images are central to modern workflows. Screenshots, diagrams, datasets, and product visuals are all part of how we communicate with Large Language Models (LLMs). But there’s a catch — preparing these images one by one is slow, repetitive, and costly. This is where batch image processing changes everything.
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