Can AI find your restaurant?
In a scan of 105 business sites, only 2.9% opened with a passage an AI engine could quote verbatim. If your restaurant is in that 97%, a diner asking ChatGPT where to eat nearby gets an answer about the place down the street, not you. AuditLamp is a free scanner that checks the signals that determine whether search and AI engines can surface your restaurant. No email required.
Whole site up to 150 pages · 164 graded checks · no email on the diagnosis · $10 full report if you want the PDF
Why does my restaurant not appear when someone asks AI where to eat nearby?
AI assistants pull answers from what their crawlers can read on your site. If your hours, address, and phone are not in machine-readable structured data, or your menu lives in a PDF or image file, the crawler sees nothing quotable. The recommendation goes to the place whose site is machine-readable.
Most restaurant websites look correct to a human visitor but are invisible to a crawler. A photo of your menu, a phone number styled into a graphic, hours buried in image text: none of it reads. The AuditLamp scan runs 164 checks across your whole site and flags the specific failures, not a generic score. The stat above comes from our scan corpus: n=105 business sites, 2026-08-11, check for quotable homepage passage.
Does Google read my menu if I upload it as a PDF or photograph?
No. PDF content and text inside images is not indexed the way HTML text is. Google and AI crawlers need your menu as real HTML text on a web page. If the menu is in a scanned file or a photograph of a printed card, the crawler logs your menu pages as thin or empty and skips them.
This is one of the most common failures in restaurant sites. The fix is not a new design: it is putting menu items as readable text in the page HTML, ideally with a hasMenu link in your LocalBusiness schema. You do not need to remove the PDF; you need to add a text version the crawler can read. The scan will tell you whether your current menu pages pass or fail.
What local business structured data does a restaurant website actually need?
A restaurant site needs LocalBusiness or Restaurant schema with opening hours, street address, telephone, and coordinates in JSON-LD format in the HTML. Separately, menus should be linked via hasMenu pointing to HTML pages. The AuditLamp scan checks for these fields and reports the specific missing values, not just whether schema exists at all.
Many restaurant sites carry a schema block but leave the critical fields blank or incorrect. A LocalBusiness type with no openingHours property, or a telephone that disagrees with the one in the body copy, still fails the machine-readability check. The scan compares schema values against visible page content and flags contradictions, not just absences.
How do I check if my restaurant website is ready for AI search?
Paste your restaurant URL into AuditLamp. The free scan reads your site the way AI crawlers do: checking hours and address markup, phone number consistency across all pages, whether menus are in readable HTML, and whether AI crawlers like GPTBot can actually fetch your pages. Results in under a minute, no email required.
You get a ranked list of failures, not a pass/fail score. Each item includes what is broken, why it costs you visibility, and how to fix it in plain language. If you pay someone for local SEO, put their report next to a free scan: is your SEO agency actually working?
This is a readiness check, not a rankings guarantee.
The free scan tells you what machines can and cannot read on your site. It does not promise placement in a specific AI answer or a specific position on Google Maps. Rankings are a function of signals across many sites; readiness is a function of your site alone, and it is the half you control. Fixing the failures the scan surfaces removes blockers that are guaranteed to hurt you. Full Report is $10 once. Ongoing re-checks are on pricing.
Find out what machines see when they read your restaurant site.
local businesses · ecommerce · saas · pricing