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Canadian buyers are using AI engines to research vendors, compare services, and form opinions about brands before they ever visit a website. The AI Visibility Audit is a 47-point diagnostic across 12 AI engines, completed in 5 working days, that tells you precisely where your brand appears, where it is absent, and what is driving the gap — with explicit bilingual coverage of both English and French-language AI behaviour. You receive a prioritised action roadmap, not a summary document, so your team can move immediately from findings to implementation.
National brands operating across both English and French Canada whose marketing teams manage bilingual content and SEO but have never formally measured whether their AI brand representation is consistent across both languages. The audit tests both language contexts and scores them separately, surfacing gaps that bilingual teams may not have thought to look for.
Technology and SaaS companies headquartered in Canada — particularly those in the Toronto, Vancouver, Montreal, and Ottawa corridors — whose target buyers are conducting AI-assisted vendor research. If your sales team is finding that prospects already have a formed opinion about your brand before the first call, AI engine representation is a plausible driver worth measuring.
Regulated-sector businesses in financial services, healthcare, and legal that need to understand whether AI engines are describing their services accurately. In regulated industries, an inaccurate AI-generated description of your firm's capabilities or compliance status is not a minor SEO problem — it is a reputational and potentially regulatory concern.
Marketing and brand teams at mid-market and enterprise organisations that have invested in traditional SEO and content marketing but have not yet adapted their strategy to AI engine citation logic. If your organic traffic growth has plateaued while your competitors continue to appear in AI-generated answers, the audit will tell you why.
AI engines draw citation authority from structured data, trusted sources, and entity signals. Most Canadian brands have built these assets primarily in English. French-language schema, French-language entity data, and French-language authoritative sources are typically much thinner — and AI engines reflect this gap faithfully.
Without correct hreflang implementation, consistent French-language structured data, and a coherent bilingual entity presence across knowledge graph sources, AI engines may be representing your English and French brand presences as separate, inconsistently described entities — which weakens citation confidence in both languages.
A competitor whose French-language content is more thoroughly structured — even if their overall web presence is smaller — will consistently outperform you in French-language AI citations. The audit measures this gap precisely.
Without a scored baseline covering both English and French AI visibility dimensions, you cannot demonstrate whether changes to your bilingual content and technical strategy are improving your AI citation rate or leaving it unchanged.
how frequently your brand is cited in AI-generated answers across English and French query sets
your share of brand mentions in AI-generated responses relative to identified competitors, measured in both languages
whether AI engines describe your services, products, and positioning accurately in English and in French
how consistently your brand entity is represented across English and French knowledge graph sources
structured data implementation quality, with specific assessment of French-language schema and hreflang coverage
citation rate and brand representation compared against three competitors across English and French queries on 12 AI engines
The audit covers 47 distinct checks across six dimensions — AEO citation rate, GEO brand mention share, LLMO accuracy, entity completeness, schema quality, and competitive AI citation gap — tested across 12 AI engines in both English and French. You receive scored results for both languages, a competitive gap report, and a 90-day action roadmap with bilingual work streams.
Five working days is the minimum required to conduct bilingual testing across 12 AI engines with genuine depth. Running 50-plus queries in both English and French, capturing and analysing responses, building the bilingual competitive comparison, and producing a ranked action roadmap takes the full five days. Cutting the timeline would require reducing either the engine count or the query volume, which would compromise the accuracy of the citation scores.
Pricing is quoted in CAD and is based on the scope of your audit and the complexity of your competitive set. Contact Ignited Nepal for a fixed-price quote. Pricing is confirmed before any work begins.
The audit is a complete deliverable. Your internal team can act on the 90-day roadmap directly, or you may engage Ignited Nepal for implementation. The audit report is structured to be handed off to any content, technical, or SEO team without requiring additional scoping or briefing from our side.
The standard audit covers 12 engines, including ChatGPT, Perplexity, Google AI Overviews, Microsoft Copilot, Google Gemini, Claude, Meta AI, and additional engines relevant to Canadian market buyer behaviour. Both English and French-language modes and interfaces are tested where they exist. The engine list is confirmed during onboarding.
The audit includes a scored diagnosis and a prioritised action plan. The 90-day roadmap ranks every finding by impact and effort and separates English and French work streams so your team knows exactly what to do and where to start. It is a strategic brief, not an observation report.
AI engines are answering your buyers' questions in both languages right now. The AI Visibility Audit tells you exactly how your brand is represented across 12 engines in English and French, what is suppressing your citation rate in each language, and which changes will improve it fastest. You receive the full 47-point report and 90-day bilingual action roadmap within 5 working days of your brief.
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