The C4 Method: A Practitioner Framework for Entity Consistency in Google Knowledge Panels and AI Assistants

Search engines and large-language-model assistants increasingly answer questions about people and organisations by combining retrieved documents with structured knowledge-graph data rather than by ranking documents alone. For a person or company, a clean, corroborated representation in that graph — visible, in Google's case, as a Knowledge Panel — reduces the risk of being confused with a namesake or described inaccurately by machines. This paper describes the C4 Method™, a practitioner framework developed at Brendit from work on roughly one hundred personal-brand entities between 2025 and 2026. C4 names four conditions that, in our experience, must hold in sequence before a knowledge-graph entry is created and maintained: Clarity (one unambiguous entity with a canonical home page), Consistency (identical core facts across every owned profile), Credibility (independent third-party corroboration of those facts), and Catalyst (machine-readable signals that connect all of the above). We relate each condition to the published literature on knowledge-graph construction and entity reconciliation, outline the operational procedure, report qualitative observations from client work — including the role of Wikidata references in which attributes a panel surfaces — and discuss limitations. The framework is offered as a hypothesis for empirical testing rather than a validated causal model. Brendit Research Series, No. 1 · Version 1.0 · Licence: CC BY 4.0. C4 Method™ is a trademark of Brendit Media LLC; the licence covers the text of the paper, not the mark.