Media Infoline: NeuroRank Opens as a Patent-Pending Platform

Media Infoline published NeuroRank’s global launch announcement on 25 May 2026, when the patent-pending AI visibility intelligence platform opened to the public as a SaaS platform. The release sets out Model Preference Engineering, the monthly practice at the center of the platform, and the enterprise brands and agencies that use it.

 Model Preference Engineering is a monthly practice

The release opens on a problem. Most brands cannot see how AI models describe them, cannot tell why they are omitted or misrepresented, and have had no system to correct it. Model Preference Engineering is NeuroRank’s answer, run as a continuous monthly practice. It diagnoses how models perceive a brand, prescribes specific fixes, conditions the sources AI systems retrieve across owned, earned, and third-party surfaces, and tracks the month-on-month change in observed model outputs.

Each cycle runs five phases. Deconstruct maps the model’s representation of the brand. Diagnose finds the gaps across ChatGPT, Gemini, Claude, and Perplexity. Prescribe sets content and technical fixes, Condition works on the sources AI systems retrieve through the Model Conditioning Loop, and Track measures the change.

 Agencies use it to build GEO practices

The release reports customers among BFSI enterprises and large FMCG brands, with growing use by agencies. For agencies, the release describes two uses: pitching new clients, and running a structured Generative Engine Optimization practice for the clients they already have. For enterprise teams, a growth option adds advisory hours so internal teams can build skills and align execution faster.

The release reports two 90-day results: a leading Indian BFSI brand improved its AI visibility by 30 percent and its citation frequency by 12 percent across the four models. A leading Indian FMCG brand improved its AI visibility by 47 percent. It notes that results vary by brand, category, and starting point. One agency had already onboarded three enterprise clients in the automobile and BFSI sectors.

Results match what a consumer sees

NeuroRank is built to counter logged-in bias, so the answers a marketing team reviews match what a consumer sees. It needs no access to a brand’s CRM, analytics, or internal systems, and it probes the models from the outside in. The release states that the method was stress-tested across more than 350 brands in 65 industries and shaped by feedback from more than 150 leadership teams across Asia, Europe, the Middle East, the USA, and North America.

Ambika Sharma’s statement in the release closed on what the platform gives every brand: