AI Visibility Audit
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Prepared by saigon.digital · July 2026
This report is confidential. Enter the access code provided by Saigon Digital to continue.
Your customers are no longer just searching on Google, they are asking AI which companies to shortlist. This audit shows exactly where you stand, who is winning, and what to do next.
Saigon Digital helped us completely rethink our digital visibility strategy. Within months of working together, our school started appearing in AI-generated recommendations, our organic traffic grew significantly, and the quality of admissions enquiries improved dramatically. They understand where digital discovery is heading and how to position brands to win.
See how we have helped brands grow. Read our case studies and learn more about what we do.
View Case StudiesA snapshot of where Canary Technologies stands in the AI search era, and the opportunity cost of the current gap.
Canary Technologies dominates traditional hotel tech review sites and award lists, yet when hotel operators ask AI assistants to recommend solutions, the brand appears inconsistently or not at all. Competitors with weaker domain authority but deeper long-form educational content are capturing the AI recommendation layer that will increasingly drive shortlisting decisions.
We tested how Canary Technologies appears when potential customers ask AI tools to recommend Hotel Technology / Hospitality SaaS providers globally. Here is what we found.
ChatGPT mentions Canary Technologies in some hotel tech queries but often leads with competitors like Duve or Mews for broader guest experience questions. Brand awareness exists, consistent citation does not.
Google AIO surfaces Canary in "contactless check-in" queries via Hotel Tech Report links, but for broader "hotel technology platform" queries, competitors with deeper editorial coverage dominate.
Perplexity cites Canary when pulling from Hotel Tech Report rankings, but for educational "how to" queries about hotel technology, competitors with stronger blog content get cited instead.
Gemini occasionally references Canary in hotel tech lists but tends to favor solutions with more third-party editorial coverage and detailed comparison content outside aggregator sites.
2 of 4 platforms currently surface Canary Technologies in relevant AI-generated recommendations consistently. The other two show only partial or inconsistent results.
Structured authority content, third-party mentions, FAQ pages, and consistent brand signals across the web, all of which competitors currently have more of in the educational and thought-leadership categories.
We ran the exact searches your buyers use when asking AI tools to recommend a solution. Here is who appeared, and whether Canary Technologies was in the answer.
Canary wins on narrow, product-specific queries (contactless check-in, digital tipping, upselling) where Hotel Tech Report awards drive citations. But on broader category queries like "hotel guest management platform," competitors with deeper educational content and wider editorial footprint capture the recommendation.
Hotel operators increasingly search broad, exploratory queries first before narrowing. Winning the "hotel guest management platform" and "hotel technology solution" layer would capture buyers earlier in the decision process, before they even know Canary exists as a category leader.
These are the companies currently winning AI recommendations in your market. Understanding why they are cited, and where Canary is not, reveals the exact gap to close.
| Company | DR | ChatGPT | Google AIO | Perplexity | Why They Win |
|---|---|---|---|---|---|
| Canary Technologies You | 70 | Partial | Partial | Partial | Audit target |
| Duve | 61 | Cited | Cited | Cited | Deep AI-focused content strategy, educational blog with how-to guides, strong third-party editorial coverage across hospitality publications |
| Akia | 69 | Cited | Partial | Cited | Niche-focused messaging authority, high DR near Canary, strong content on AI concierge use cases |
| HiJiffy | 59 | Cited | Cited | Partial | AI chatbot authority positioning, multilingual content, extensive hospitality publication mentions |
| Oaky | 52 | Partial | Cited | Cited | Category-defining upselling content, 6 consecutive Hotel Tech Report awards, Plusgrade acquisition boosted authority |
| Kipsu | 51 | Partial | Partial | Not Cited | Guest messaging niche authority, limited broader visibility, weaker editorial footprint |
Badge key: Cited Partial Not Cited
These are the highest-leverage changes Canary Technologies can make right now to start dominating AI-generated recommendations within 30 to 90 days.
Deploy an llms.txt file and build a structured "Hotel Technology Knowledge Base" section with FAQ-rich, definition-style content that AI models can easily parse and cite. Cover category terms like "what is contactless check-in," "hotel guest management platform explained," and "digital tipping for hotels." This directly addresses the gap where competitors with educational content are getting cited over Canary.
Canary already wins award rankings but loses on educational queries. Publish 8 to 10 long-form guides (2,500+ words) that own category terms: "The Complete Guide to Hotel Guest Management," "Contactless Check-In: Everything Hoteliers Need to Know," and similar. Include original data from your 20,000+ hotel install base, something no competitor can replicate. AI models heavily favor original research and data-backed content.
Canary is well-cited on Hotel Tech Report but underrepresented in broader hospitality publications, tech blogs, and industry analyst content. Secure guest posts, expert commentary, and bylined articles in publications like Hospitality Net, Hotel Dive, Skift, and PhocusWire. AI models weight third-party editorial mentions heavily when assembling recommendation lists.
While auditing how AI sees Canary Technologies, we also looked at the website itself (Webflow). These specific issues are holding back both your AI visibility and how the site converts, and they are all fixable.
Multiple images across the homepage lack descriptive alt text, including logo variations, partner logos, and award badges. This reduces accessibility compliance and means AI crawlers and search engines cannot understand what these images represent, weakening the contextual signals your site sends about partnerships and credibility.
The partner logo carousel loads the same set of images three times over, inflating page weight unnecessarily. Combined with multiple analytics scripts and heavy JavaScript bundles, this slows initial page load, particularly on mobile. Google Core Web Vitals penalties from this directly impact both SEO rankings and AI crawl efficiency.
While the robots.txt correctly allows AI crawlers (GPTBot, Google-Extended, PerplexityBot), there is no llms.txt file to guide AI models on which content to prioritize. Adding this file helps AI systems understand your product categories, use cases, and key differentiators, increasing the likelihood of accurate, favorable citations.
Web development and Webflow are core strengths at Saigon Digital. Fixing the issues above is part of the work, not a separate project. We handle the AI visibility, the SEO, and the website itself.
This audit shows the problem. Fixing it usually means more than AI alone: the website, the SEO and the AI visibility all work together. We handle all three, then keep it growing.
Canary Technologies has a clear path to winning AI and search visibility, and a website that supports it. The gap to competitors is real but closeable. We typically start with a fixed-price foundation sprint (AI and GEO, SEO, and the website fixes above), then a simple monthly retainer to keep growing and maintain the site. A 30-minute call is all it takes to map it out.
Nick Rowe · CEO & Co-Founder, Saigon Digital
A fixed-price 3-month sprint: get cited in AI answers, fix the SEO foundations, and reposition and repair the website (development and Webflow included). One scope, one price.
A simple monthly retainer once the foundation is set: continued SEO and AI visibility growth, content, and website maintenance and support. Rolling monthly, no long lock-in.
Every month your competitors build more authority signals, the gap widens. AI models are training on content published now, so delay compounds the problem.