Technical clarity
We review crawlability, index controls, canonical URLs, metadata, internal links, and the route-level evidence search systems use to interpret your site.
AI search visibility & entity clarity
Make your business easier to discover and describe accurately.
We improve crawlability, indexing signals, entity consistency, structured data, source-worthy content, and measurement so search engines and AI assistants have clearer evidence about your business.
Entity consistency
We map your organization, people, services, and source material so public facts agree across your site and systems that may reference it.
A responsible visibility claim
No consultant can guarantee that a search engine or AI assistant will rank, cite, or recommend a business. We improve the technical and authority signals that make accurate discovery and attribution more likely.
Working model
Visible decisions, accountable ownership, and a measurement plan.
Business entity
Business entity and public-source relationship mapWebsiteSchemaSources
Public signals help systems understand—not guarantee—visibility.
Clear discovery begins with a consistent entity.
Search engines and AI systems form an understanding from multiple public signals. The website, structured data, founder profiles, business listings, published resources, and external references should agree about who the business is, what it does, who leads it, and where authoritative information lives.
No single file or schema property creates visibility by itself. The objective is to reduce ambiguity and strengthen the technical and public evidence available to systems that crawl, retrieve, and summarize information.
Improved signals are not a guaranteed citation.
Search rankings, AI citations, recommendations, and generated answers are controlled by external systems and can change without notice. Boyer Impact Systems improves the clarity, accessibility, consistency, and corroboration of public information. It does not guarantee that a particular system will rank, cite, recommend, or describe the business in a specific way.
Technical clarity and public corroboration.
Crawl and index review
Robots directives, sitemap coverage, canonical URLs, rendered HTML, metadata, status codes, internal links, and page discoverability.
Entity architecture
Organization, Person, Service, Article, Book, and WebSite relationships with stable IDs and accurate properties.
Profile consistency
Business name, founder identity, descriptions, services, and website references across verified public profiles.
Content evidence
Useful service explanations, original resources, authorship, dates, and claims that can be supported.
Measurement plan
Baseline queries, indexed-page coverage, referral sources, branded discovery, and repeatable rechecks.
Questions
Questions about this engagement
Is JSON-LD enough to make an AI system cite us?
No. Structured data helps machines interpret relationships, but it must agree with visible page content and credible external sources. It is one signal among many.
What is the role of llms.txt?
It can provide a concise, machine-readable guide to important public pages, but support varies and it does not control whether a system retrieves or cites the site.
Can you guarantee a ranking or recommendation?
No. The engagement improves the signals that support accurate discovery and understanding, but external search and AI systems determine their own results.
What can be measured?
The work can track crawlability, index coverage, structured-data validity, branded search results, referral traffic, profile consistency, and changes in a repeatable set of discovery checks.