AEO · GEO · LLMO | AI Search Visibility for Canadian Businesses

Canadian Buyers Are Asking AI First — Are You the Answer They Get?

Across Canada's bilingual search environment, AI assistants have become a primary research tool for both English-speaking and French-speaking buyers. Google's AI Overviews dominate results on every device, ChatGPT is used by millions of Canadians for purchasing research, and Perplexity has grown rapidly as a professional research platform. Ignited Nepal helps Canadian businesses build the AI visibility infrastructure needed to appear accurately, consistently, and frequently across all three AI search disciplines — AEO, GEO, and LLMO — in both official languages.

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This is for you if

Who This Is For

Canadian B2B technology and SaaS companies competing in markets where AI-generated vendor shortlists are increasingly shaping RFP processes, and where being absent from those lists means being absent from the conversation entirely.

Professional services firms — accounting, legal, consulting, and financial services practices across Toronto, Vancouver, Calgary, and Montreal that are watching referral traffic decline as clients begin research through AI assistants rather than Google Search.

Bilingual businesses and Quebec-based enterprises whose AI visibility in French is significantly weaker than in English — because most AI visibility strategies have been built for English-language search environments and do not account for the distinct AI search patterns in French-language markets.

Retail and e-commerce brands operating in Canada's competitive consumer market, where AI-powered product recommendation features on Google Shopping and major e-commerce platforms are increasingly mediating what products buyers consider.

What's broken

What's Broken

Most Canadian businesses focus on one piece of the puzzle

Most Canadian businesses entering the AI search conversation focus on one piece of the puzzle. Some add FAQ schema to existing pages and call it AEO. Others pitch journalists and editors for brand mentions and call it GEO. A small number begin optimising their structured data with language models in mind and call it LLMO. What none of these approaches does on its own is build durable, cross-platform AI visibility in a market as linguistically and geographically complex as Canada's.

The bilingual gap is a compounding problem

AI systems like ChatGPT and Claude handle English and French as distinct knowledge domains. A business that is well-represented in English-language AI answers may be almost invisible in French-language responses, because the citation sources, entity data, and training signals that inform French-language AI outputs are entirely different. For businesses operating in Quebec, or for any Canadian brand that serves French-speaking buyers, this asymmetry is an immediate competitive vulnerability.

Regional AI search patterns vary more than most teams expect

Canadian AI search users in Alberta, British Columbia, Ontario, and Quebec exhibit different query patterns, different levels of AI assistant adoption, and different expectations about the types of brands that ought to appear in AI-generated category recommendations. A nationally scoped AI visibility strategy that ignores regional variation will underperform in every market it targets.

The measurement problem applies just as acutely here

Traditional Google Search Console data, GA4 acquisition reports, and Ahrefs ranking positions do not tell Canadian marketing teams how often AI engines cite them, how accurately AI describes their brand in French versus English, or what share of the AI conversation they hold in their vertical. Without AI-specific measurement infrastructure, Canadian teams are optimising blind.

What we engineer

What We Do

Answer Engine Optimisation (AEO)

Answer Engine Optimisation (AEO) targets the specific questions Canadian buyers are asking AI engines about your category. In practice, this means mapping the full question landscape around your offering — in both English and French — identifying where competitors are currently being cited as answers, and building the content architecture and schema markup that positions your pages as the most credible, citable response. For bilingual businesses, AEO requires distinct content strategies for English and French queries, because the question phrasing, competitive content, and AI selection patterns differ between the two languages.

Generative Engine Optimisation (GEO)

Generative Engine Optimisation (GEO) builds the citation and authority signals that cause AI engines to name your brand when synthesising broad industry answers. When a buyer asks "which accounting software is recommended for Canadian small businesses?" or "what professional services firms operate in Vancouver?" — the AI engine synthesises that answer from indexed sources and training patterns. GEO is the work of ensuring your brand is among those sources: earning citations in Canadian industry publications, building co-occurrence signals in both official languages, and strengthening the entity data that defines your competitive position in your category.

Large Language Model Optimisation (LLMO)

Large Language Model Optimisation (LLMO) addresses the foundational layer that precedes both AEO and GEO in terms of strategic importance. If language models hold inaccurate, incomplete, or outdated information about your brand — your products, your geography, your service areas, your competitive positioning — they will reproduce that inaccuracy in every AI-generated response that touches your category. For Canadian businesses, LLMO requires particular attention to geographic entity data (ensuring AI systems correctly associate your brand with the right provinces, cities, and markets) and to bilingual brand consistency (ensuring the French and English representations of your brand are equally complete and accurate).

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What changes

What Changes

Before
After
Before French-language AI visibility is typically the weakest dimension for most Canadian businesses entering this space
After Your brand begins appearing in AI-generated answers to the specific questions your Canadian buyers ask, in the language they are asking in. French-language AI visibility closes the gap with English-language performance as bilingual LLMO and GEO work takes effect.
Before AI defaults to a generic national description rather than your actual geographic reach
After AI engines begin accurately describing your brand, your geographic reach, and your service offer — in both official languages. An AI that correctly identifies your firm as serving clients across Ontario and Quebec is far more likely to surface in the geographically contextualised queries that Canadian buyers increasingly use.
Before AI visibility is a channel that was previously unmeasured
After You gain visibility into a channel that was previously unmeasured. Monthly reporting on AEO citation rate, GEO brand mention share, and LLMO accuracy score — in both English and French — gives Canadian marketing teams the data infrastructure to make informed AI visibility decisions for the first time.
Before Traditional SEO and AI visibility are treated as a trade-off
After Traditional SEO performance benefits from the programme's underlying signal-building. The authority and entity work done for GEO and LLMO reinforces trust signals that support organic ranking stability, and the structured content built for AEO tends to perform strongly in featured snippet and "People Also Ask" environments in standard search.
Common questions

FAQ

What is the difference between AEO, GEO, and LLMO?

AEO, GEO, and LLMO each address a different layer of AI search visibility. AEO (Answer Engine Optimisation) is about structuring your content so AI engines select it as the direct answer to specific questions — it is the most immediate and query-specific of the three disciplines. GEO (Generative Engine Optimisation) is about building the citation signals and authority patterns that cause AI engines to name your brand when generating broader, synthesised industry answers. LLMO (Large Language Model Optimisation) is about the foundational layer — auditing and correcting how language models internally represent your brand, so that every AI-generated response touching your category is built on accurate, complete brand data. In Canada's bilingual environment, all three disciplines need to be applied to both English and French knowledge domains.

Which discipline should a Canadian business start with?

The starting point is always the AI Search Audit, which establishes where you stand across all three disciplines in both languages. For Canadian businesses, LLMO is frequently the most urgent foundation, particularly for those whose French-language entity data is sparse or inaccurate in major language models. That said, businesses in highly question-driven categories — professional services, SaaS, financial products — often find AEO delivers the fastest measurable return on the English-language side. The audit makes the priority order clear.

Is the bilingual angle standard, or does it cost extra?

Bilingual delivery — English and French — is built into our Canadian programme architecture, not added as an optional extra. This reflects the reality of the Canadian AI search market: a strategy that ignores French-language AI visibility leaves a significant portion of the Canadian addressable market unserved, and for businesses in Quebec or those serving French-speaking buyers nationally, the French-language gap in AI visibility is often their most significant competitive exposure.

How long does it take to see results in Canada?

Timelines for the Canadian market are broadly consistent with other markets: AEO citation rate improvements typically become measurable within six to ten weeks, GEO brand mention share builds over three to six months, and LLMO accuracy improvements surface within eight to twelve weeks as AI platforms update their retrieval systems. French-language results may have a slightly longer lead time because the authority source landscape for French-language AI systems is smaller and more concentrated than for English.

What does this cost?

Programmes are priced in CAD. Single-discipline programmes begin in the range of CAD $3,200 to CAD $5,500 per month. Integrated three-discipline programmes, covering all three disciplines in both official languages, are priced from CAD $7,500 per month. The AI Search Audit is scoped and priced separately. All pricing is confirmed after audit findings are reviewed.

How does this work alongside our existing SEO programme?

AI visibility work and traditional SEO are complementary rather than competing investments. The authority signals built through GEO reinforce the trust and citation factors that traditional SEO depends on. The content architecture built through AEO tends to improve structured snippet performance and "People Also Ask" capture in standard search results. LLMO entity data improvements stabilise the brand representation across both AI and traditional search environments. Canadian businesses running both programmes typically see SEO performance strengthen alongside AI visibility growth, rather than a trade-off between the two.

Our team

The people behind the work

Not a black box. Real specialists you can call, with their names on the work.

Niraj Raut

Niraj Raut

Founder — Ecommerce SEO
Keshab Joshi

Keshab Joshi

PPC Expert
Hawrry Bhattarai

Hawrry Bhattarai

Google Ads Expert
Arogya Rijal

Arogya Rijal

SaaS SEO Expert
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Start here

Start with a clear picture of where your AI visibility stands — in both official languages.

The Canadian businesses that are building AI visibility now are accumulating a citation, authority, and entity data advantage that will be significantly harder to close in twelve months. An AI Search Audit gives you the bilingual baseline you need to act from a position of information rather than assumption.

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Run an AI Visibility Audit