What is Relevance Engineering?+
Relevance Engineering is a methodology for optimising brand visibility in AI-powered search engines — including ChatGPT, Gemini, Perplexity and Google AI Overview. Unlike traditional SEO, which optimises for keyword rankings and backlinks, Relevance Engineering optimises for how language models understand, represent, and cite your brand. As users increasingly ask AI assistants instead of typing queries into Google, being present in those AI responses requires a fundamentally different kind of optimisation.
Why are Polish businesses invisible to English-language AI search?+
Most AI models are trained predominantly on English-language data. A Polish company — even one with an excellent English-language website — is treated as a zero-confidence entity by AI tools trained on UK or US data. The problem is not language: it is the absence of market-specific trust signals. AI models look for UK Companies House registrations, GDPR compliance statements, British industry association memberships, and Sterling pricing. Without these vectors, the AI classifies the business as unverifiable and withholds citations — regardless of content quality.
How is Relevance Engineering different from simply translating my website?+
Translating your website converts words into English but leaves your entity invisible to AI models trained on English-market data — what we call the Translation Trap. Relevance Engineering maps Trust Vectors: market-specific signals that AI models use to verify credibility. For the UK market this means linking your KRS registration to a UK Companies House entry, referencing British industry bodies, and grounding content in UK-specific entities. The goal is Entity Portability — making your Polish entity legible to AI systems in the English-speaking world. Native English writing, not translation, is an essential part of this.
Which AI platforms matter most for UK and US markets?+
For B2B companies targeting the UK and US, the priority stack is: (1) Bing AI and ChatGPT — Bing's index feeds ChatGPT web search, making Bing Places and Bing entity data critical; (2) Google AI Overview — appearing as a cited source gives direct SERP visibility without requiring a click; (3) Apple Maps and Siri — dominant on iOS, which accounts for over 50% of the UK smartphone market; (4) Perplexity — growing rapidly among researchers and business decision-makers. Each platform draws from different data sources, which is why optimising only for Google is insufficient.
What is Share of Model and how is it measured?+
Share of Model (SoM) is the percentage of AI responses — across a defined set of industry queries — that cite or name your brand as a relevant answer. We measure it by systematically posing the same questions your target customers ask to ChatGPT, Gemini, and Perplexity, then recording whether your brand is mentioned or cited. We establish a baseline SoM at the start of an engagement and report changes monthly. SoM complements organic traffic — it measures influence in the growing portion of search that never produces a click.
Does my business need Relevance Engineering if I already rank well in Google Poland?+
Ranking well in Polish Google means your entity is established in Google's Polish data graph — but that authority does not automatically transfer to English-language AI systems. Bing Copilot, ChatGPT, and Siri source predominantly from English-language indexes and training data. A company ranking #1 for agencja SEO Poznań may be entirely invisible to an AI assistant answering "find an SEO agency in Poland" in English. Relevance Engineering bridges that gap by building your entity footprint in the data sources English-language AI models actually use.
How long does implementation take and when are first results visible?+
The entity audit and foundation implementation — Schema @graph, entity synchronisation, NAP consistency repair, Bing Places and Apple Business Connect setup — takes 4–8 weeks. First measurable improvements in AI citation frequency typically appear within 6–12 weeks. Relevance Engineering is not a one-time project: AI models are continuously retrained and updated, requiring ongoing monitoring and adjustment. We work on monthly retainer arrangements with citation reporting so you can track Share of Model growth over time.
How much does Relevance Engineering cost?+
Every project begins with a free Sigfides audit. We scope work only after understanding the specific entity gaps and target markets. Relevance Engineering is available within the Expansion programme (2,000–3,500 PLN/month) and the Market Leader programme (custom pricing), depending on the number of target markets and AI platforms. For companies focused exclusively on the Polish market, a simplified version is available within the Foundation package. The audit is always free.
