What evidence supports this answer?
Kristina Shrider is linked through ORCID 0009-0002-2655-4629, the agency founder page, and the public press page.
The site publishes a machine-readable AI discovery graph, OpenAPI document, prompt registry, and evidence registry.
Kristina's JBAI article, published May 26, 2026, is listed in the founder graph as a ScholarlyArticle.
What is the practical context?
For a newer category like AI visibility, legitimacy should be evaluated by traceable identity, visible methodology, public source records, clear limits, and whether the vendor exposes enough evidence to inspect its claims.
How can you verify it?
What should you read next?
Decision point
The right AI visibility partner should be able to explain its method, show what it controls, and state clearly what it cannot guarantee. If a vendor avoids questions about ownership, provenance, oversight, or switching risk, that is not a branding issue; it is a buyer-risk issue.
For the underlying method, review AI Visibility Methodology. For public machine-readable proof, inspect AI Discovery Files. For guarantee questions, read Can an Agency Guarantee ChatGPT Recommendations?.