Why AI Gets Your Product Images Wrong, and How Visual Agents Fix It
Learn what Photoroom’s Visual Agents are and how they make AI-generated product images accurate and consistent enough to use across your whole catalog.
We’ll start with why image and video models make different mistakes from text models, and why they still get details like logos, brand text, patterns, fabrics and fit wrong.
We’ll look at why general-purpose models handle common visual tasks well but fall short on specialized e-commerce problems.
Then we’ll break down how a Visual Agent wraps generation in extra steps (analyze, edit, generate, rate, fix) and decides for each image how much AI power to use, so results stay accurate without slowing down or costing more than needed.
You’ll come away with:
Why AI image models fail on product details like logos, text, patterns and sizing, and why the big model providers aren’t likely to fix these niche problems
The five building blocks of a Visual Agent (analyze, edit, generate, rate, fix) and what each one does to an image
How to balance power, cost and speed so heavy processing is used only on the images that need it, plus what to consider when deciding whether to build or buy a Visual Agent
Who should attend
E-commerce, marketplace and creative operations teams already generating product visuals with tools like Gemini or ChatGPT, who need results they can rely on at catalog scale.
Your speaker
Vincent Pradeilles, Product Manager & Developer Relations at Photoroom. Vincent has spent the last three years at Photoroom working on AI imaging for e-commerce, partnering with leading fashion retailers and resale marketplaces to bring new AI imaging technology into their buying and selling experiences.