Operational Proof
Case Studies
How AI Visibility Architecture, Entity Lock Protocol™, and the BackTier Visibility Path™ show up in market. Each study below is structured around the same five measurement layers — Ranked, Cited, Included, Selected, Referred — so the constraint stays visible.
Public case studies are published as they meet the acceptance bar: a clean-session AI test across ChatGPT, Gemini, Perplexity, and Google AI Overviews must return consistent identity and recommendation behavior across at least one full re-test cycle. Studies below are intentionally structured rather than narrative — they document mechanism, not marketing.
Published studies
Personal entity · Live study
Re-resolving a legal name change across seven machine stages
Jason AI Wade → Jason AI Wade
- The constraint
- The name 'Jason Wade' resolves to the wrong person in every major AI system — volume and fame beat correctness, and no amount of SEO moves the resolution.
- The intervention
- Change the strongest fact any system weighs — the legal name — then measure how the new entity cascades through Discovery, Recognition, Classification, Citation, Inclusion, Selection, and Recommendation using a fixed prompt set run on a regular cadence.
- What was observed
- Discovery confirmed within ten days of the first crawlable instance. Google AI Overviews recognized the new name as a person and attributed founder status and the seven-stage framework correctly within days of the experiment page shipping — while book and podcast credits still resolved under the prior name, the exact half-updated middle state the study set out to catch.
Evidence: Live seven-stage tracker
Local entity · NewsMediaOrganization
Locking a local publication as a citable place entity
Lake Wales Guide
- The constraint
- Local publications are structurally invisible to AI systems: thin structured data, no typed place entities, and nothing for a model to corroborate against.
- The intervention
- Engineered the publication as an entity-resolution environment from the start — machine-readable place entities, structured local data, and editorial coverage built to be extracted, dated, and attributed.
- What was observed
- The publication holds durable citation performance in AI answers and search for its coverage area, and serves as the standing local proof surface for the frameworks.
Evidence: lakewalesguide.com
Search performance · City guides
Entity-structured city guides that hold search positions
Florida Slice
- The constraint
- City-guide content is a commodity category — thousands of near-identical pages competing on the same queries, with no structural reason for a machine to prefer one source.
- The intervention
- Built each guide around typed city entities, consistent structured data, and answer-shaped content rather than keyword pages.
- What was observed
- The guides hold SERP positions in their category — the search-layer proof that entity structure, not volume, is the durable advantage.
Evidence: floridaslice.com
How studies are structured
Every published study reports across all five measurement layers of the BackTier Visibility Path™ — Ranked, Cited, Included, Selected, Referred — and identifies which layer was the binding constraint at the start of the engagement and at the acceptance test. The intervention is always anchored to Entity Lock Protocol™.