Your customers ask Google for a recommendation, but they also ask ChatGPT and Perplexity. This system bundles Schema.org markup, a Markdown twin of every page, NAP consistency and citation tracking to build your visibility in AI answer engines, so Google and AI both find you, understand you and cite you.
For Greater Montreal SMBs that want to show up when a customer asks for a recommendation, whether in Google or through an AI answer engine like ChatGPT or Perplexity.
Ask ChatGPT or Perplexity for a service in your sector in Montreal. Without structured data or citable content, the assistant names the competitor who has it, not you, and that recommendation repeats every time a new customer asks.
An AI assistant favours a plain page over one loaded with scripts. Without a Markdown twin and an llms.txt file, it has to guess at your content instead of citing it with confidence, and it may end up favouring a source that's easier to parse instead.
Name, address and phone number differ between your site, your Google Business Profile and directory listings. Google and AI both hesitate to cite a business whose facts don't line up, even when that business offers exactly what the customer is looking for.
Every page carries Schema.org markup (LocalBusiness, Service, FAQPage, BreadcrumbList) that names your business, your services and your area without ambiguity, for Google and for AI. That markup also states your hours, address and linked reviews, when that data exists.
An llms.txt file and a Markdown version of every page give assistants like ChatGPT and Claude clean content to cite, without having to interpret your layout or your scripts. This page itself has a Markdown version, reachable with the HU|IA toggle at the top of the screen.
Your service, your city and the platforms you use are named plainly, not hidden behind vague phrasing. The same contact details appear on your site, your Google Business Profile and directory listings, so every source an AI checks shows the same facts.
| Traditional SEO approach | RecommendedFound on Google, cited by AI | |
|---|---|---|
| Schema.org markup | Missing or partial | LocalBusiness, Service, FAQPage and BreadcrumbList on every page |
| AI-readable version | None, AI reads the rendered HTML | A Markdown twin of every page, plus an llms.txt file |
| Information consistency | Name, address and phone number vary by source | Same details on your site, your Google Business Profile and directory listings |
| Content | Generic, built around keywords | Entity-first, names the service, the city and the platform |
| Tracking | Google rankings only | Google rankings and citations in AI answers |
| Goal | Getting the click | Getting cited, click or not |
Discuss Found on Google, cited by AI
Book a callWe go through your pages, your Google Business Profile and your directory listings to find NAP inconsistencies, pages missing markup and content an AI still can't cite accurately.
We install Schema.org markup, publish the Markdown twin and the llms.txt file, then fix the inconsistencies found across your site, your Google Business Profile and the directories that matter most.
We track your citations across AI answer engines and your Google rankings, and adjust content that isn't cited yet or is cited with inaccurate information.
Aesthetics & Beauty · Promenade Fleury, Ahuntsic, Montreal, Quebec
Financial services / Payment terminals · Laval, Quebec
It's the combination of structured data, a Markdown twin of every page, an llms.txt file and entity-first content that lets Google and AI answer engines like ChatGPT or Perplexity understand your business clearly and cite it with confidence, instead of guessing or naming a competitor instead.
Traditional SEO aims for a click in Google's results. This system adds a layer: making your content readable and citable by AI answer engines like ChatGPT and Perplexity, which often answer the question themselves, without a click to your site happening at all.
It's a plain-text version of every page on your site, published at the same address followed by '.md'. AI assistants read it more easily than a script-heavy HTML page with layout and navigation, which can help reduce factual errors in a citation.
It's a file at the root of your site that tells AI assistants where to find your important pages and their Markdown twins. It works like a sitemap built for AI rather than for a traditional search engine, and it makes your whole content library easier to read.
When your name, address and phone number differ between your site, your Google Business Profile and directory listings, Google and AI can't tell which version is accurate. They may cite a competitor whose information matches everywhere instead, leaving your business out of the answer.
The audit sets the order of the steps: structured data, Markdown twin, llms.txt. How soon you show up in an AI answer then depends on your sector and which competitors are already cited; the timeline for the base structure is confirmed at the audit.
No. It builds on the same foundations, structured data, clear content, consistent information, and extends them to AI answer engines like ChatGPT and Perplexity. A site that already ranks well on Google starts ahead when it comes to being cited by AI, rather than starting from zero.
Ask ChatGPT or Perplexity the question a customer would ask for your service in your city. If your business doesn't come up, or the information cited is wrong or outdated, that's a sign you're missing structured data or a consistent source AI can verify easily.
The case studies linked on this page show the structured-data work and Search Console tracking achieved for these clients. None has a measured AI citation yet; we'll add that proof here once a sourced, measured result exists for a client.
Structured data, a Markdown twin, llms.txt and consistent information: we get your business ready to be found and cited, in Greater Montreal and across Quebec.
20 minutes, no jargon: we show you where your information contradicts itself.
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