About

Why aiListing exists

I'm Chris. I've been building AI models for over ten years — since before GPT-2, back when "language model" wasn't a phrase you'd use outside a research paper. In parallel I've spent fifteen years in digital marketing and web development, building hundreds of websites and a few dozen online stores for real businesses that had to actually sell things, not just look good in a portfolio.

Somewhere in the last couple of years those two backgrounds collided. I started noticing — first anecdotally, then in the traffic logs of stores I manage — that people had quietly started asking ChatGPT and Perplexity what to buy instead of typing it into Google. Not in a hypothetical, someday way. Already. And almost none of the stores I looked at, including some I'd built myself, were set up to be read by those systems at all: blocked crawlers, no product data a model could parse, pages that render empty until JavaScript runs. The store could be excellent and still be structurally invisible to the channel that was starting to send the highest-intent traffic on the web.

aiListing is the tool I wished existed when I noticed that: something that tells you, in plain terms and in under a minute, whether AI assistants can actually see your catalog — and if they can't, exactly why not.

How the audit works

Every audit crawls the target site live and checks five things AI assistants actually rely on: whether their crawlers (GPTBot, ClaudeBot, PerplexityBot and others) can read the site at all, whether products expose machine-readable Schema.org data, whether llms.txt and sitemaps make the catalog discoverable, whether pages render content AI crawlers can see, and whether titles/descriptions/alt text are usable as citation text. Category weights and the underlying scoring model are proprietary — the report shows the grade and the finding, not the formula.

Who this is for

E-commerce teams who want a straight answer to "can ChatGPT even see our products," self-serve, without a sales call. If your catalog needs implementation at scale, our team also does that as a separate, scoped engagement — but nothing on this site requires talking to anyone first.

Contact

Questions, bug reports, or press: [email protected]. I read everything that comes in.