AI Engines Don't See Your Brand the Way Your Clients Do.

A brand entity is a structured, machine-readable record that defines your organisation as a distinct, identifiable subject — verified attributes, cross-referenced identifiers, and relationship data that AI engines and search algorithms can consult with confidence. For Canadian businesses, entity records matter in a distinct way: the bilingual information environment means your entity needs to be coherently documented in both English and French-language sources to be recognised as a complete, credible entity by AI systems serving users in either official language. A company well-documented in English Wikipedia but absent from French Wikipedia is invisible to French-language AI queries — including those from Quebec's substantial enterprise market.

No. Both English Wikipedia and French Wikipedia apply notability standards that require significant coverage in reliable, independent sources — national or regional press, industry publications, regulatory filings reported on by credible outlets. Companies with limited third-party coverage in either language may not currently qualify for a standalone Wikipedia article in that language. In those cases, we identify the path to qualification, assess what Wikidata enrichment and Knowledge Graph entries can achieve in the interim, and are direct about what is immediately achievable. We will not pursue a Wikipedia article that the editorial community would decline — that wastes time and can create editorial problems that complicate future attempts.

The Entity Gap Audit and Entity Structure Plan are completed within two weeks. The Core Entity Build — English Wikipedia, French Wikipedia, Wikidata enrichment, and Knowledge Graph submission — takes four to six weeks, with the bilingual complexity adding time relative to a single-language build. The Directory Citation Campaign runs in parallel and is complete within four weeks. Most Canadian clients should plan for a total of ten to fourteen weeks from engagement to a fully deployed bilingual entity infrastructure. French Wikipedia editorial review timelines can vary as they depend on volunteer editorial processes; we manage that process throughout.

Entity Trust Building for Canadian organisations is priced from CAD $6,000 for the complete bilingual programme, covering the audit, entity architecture design, English and French Wikipedia work, Wikidata enrichment, Knowledge Graph submission, 20+ directory citations, and the first quarterly monitoring review. Organisations with more complex entity structures — Quebec-specific legal entity requirements, multiple provincial registrations, regulated industry memberships, or subsidiary relationships — are priced on the basis of the audit findings. All pricing is confirmed in writing before any work begins.

The highest-weight Canadian directory sources for entity trust are those AI engines and Knowledge Graph algorithms treat as authoritative federal or provincial verification anchors. The Canadian Business Register is foundational — it is the federal reference point that other citations should align with. Yellow Pages Canada and BBB Canada carry significant weight for general business entity signals. Provincial corporate registry records (Ontario Business Registry, Registre des entreprises du Québec, BC Registry, ABCA) are important for regional entity coherence. For Quebec and Francophone markets, alignment between your French Wikipedia article, your French-language Wikidata descriptions, and French-language directory citations creates a coherent entity signal that AI systems operating in French specifically value.

AI engines reference structured, authoritative data sources when constructing answers. When your entity record is coherent and well-documented across English Wikipedia, French Wikipedia, Wikidata, the Canadian Business Register, and major directories, AI systems have the structured data they need to include your brand in relevant answers in both languages. The effect is not immediate — Knowledge Graph updates and AI training data refreshes operate on their own schedules — but the foundation you build now determines your entity's representation in AI systems for years. Directory citations typically begin influencing Knowledge Graph data within four to eight weeks. Wikipedia and Wikidata improvements flow into AI training data on longer cycles, but the entity confidence signals they produce begin influencing search algorithm behaviour relatively quickly.