Autorender
Your images have three visitors. Your pipeline serves one.
The first is a customer. They need a fast, beautiful, format-optimised image — the experience that makes them buy. You've built for them. It works.
The second is a crawler. They need enough to index. They get exactly what the customer gets. You pay full price for traffic that never buys.
The third is new. It's an AI shopping agent — ChatGPT, Google, Perplexity — evaluating your products to decide what to recommend to someone ready to buy. It needs a clean, unambiguous image it can read accurately. A noisy background confuses it. A wrong crop changes what it thinks your product is. Right now it gets whatever your pipeline sends.
Three visitors. Three requirements. One pipe that treats them identically.
This is no longer theoretical.
AI crawlers alone generated nearly one billion requests in a single month across Vercel's network. For large product catalogs, this traffic — which will never convert — has become a material line item, not a rounding error.
But the crawlers aren't the real cost.
The real cost is the recommendation that never happens.
Anthropic's crawler dedicates 35% of its fetches specifically to images. These models are actively training on your product imagery — building an understanding of what you sell. That same understanding powers the AI shopping agents now fielding purchase decisions: ChatGPT shopping, Google AI overviews, Perplexity product discovery. If they couldn't process your images cleanly during training, your product doesn't surface when it matters. You can't measure a recommendation that never happened. But it's already not happening.
Cloudflare recently shipped an Agent Readiness Scan: a tool to check how prepared your website is for AI agents. It's infrastructure.
Autorender is the routing layer your image pipeline is missing. Every visitor gets what they actually need.
We're in early access, working with teams whose revenue doesn't move despite everything else being right.
engineering@autorender.io