KSMModel.ai Launches KSMModel.app to Improve AI Visibility
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NEW YORK, NY, UNITED STATES, October 16, 2026 /CourierPR/ -- KSMModel.ai, a company that specializes in AI visibility assessment, has launched KSMModel.app, a new platform designed to help businesses improve their presence in AI-powered answer engines and generative engines. The platform evaluates a brand's visibility across two key areas: Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO).
KSMModel.ai’s founder, Dr. Anthony Q. Bowen, explains that the launch of KSMModel.app addresses a critical need in the market.
The platform uses a unique scoring model called the Knowledge Structuring Model™ (KSM™) to assess a brand's AI visibility. The score is calculated using three weighted pillars: Structured Extractability (SE), Entity Salience (ES), and Citation Authority (CA). The formula for the AI Visibility Score is as follows:
\[ \text{AI Visibility Score} = (SE \times 40\%) + (ES \times 40\%) + (CA \times 20\%) \]
Where: - SE = Structured Extractability (40%) - ES = Entity Salience (40%) - CA = Citation Authority (20%)
The platform provides a detailed assessment of a brand's strengths and weaknesses in these areas. It then generates a practical 90-day improvement plan to help marketing teams prioritize their efforts. This plan is designed to move organizations from a baseline score to a higher level of AI visibility readiness.
The platform has already been tested in various industries. In the fashion industry, SoniaNoel.com is being used to evaluate how biography, fashion collections, books, media coverage, events, and product information contribute to AI visibility. In the healthcare vertical, PeptideDoc.com is being used to assess how physician credentials, services, location information, educational content, and authoritative external references impact AI visibility readiness.
KSMModel.app is currently available in beta. Organizations can measure their AI visibility at https://ksmmodel.app and view case studies at https://ksmmodel.ai/case-studies.
The platform does not guarantee AI rankings, recommendations, citations, traffic, or revenue. Assessments reflect publicly observable digital evidence and identify conditions that may support stronger AI visibility readiness.