Our Work
Three 2026 projects — a practical test of AI Visibility Framework across reputation, B2B, and B2C scenarios.
The goal is not a portfolio of publications, but a demonstration of the methodology: which hypotheses were tested, which constraints were identified, and which insights shaped the approach.
«In the new search landscape, the brand that wins is not the one that talks about itself the most, but the one that artificial intelligence knows more accurately, deeply, and reliably.»
Practical knowledge base for AI Visibility Framework
Completed Projects
Filter by segment — see details in the accordion below the cards.
Telecommunications · 2026
Corporate Reputation in AI
Pilot: "Best Telecom PR Team on the Market"
Testing professional reputation management in ChatGPT and Alice AI — how Owned Media, national outlets, and industry platforms shape AI responses.
Facade Systems · 2026
AI Visibility for Project-Based B2B Sales
Assessing methodology fit in a long sales cycle
Evaluating AI's potential across project funnel stages — from engineering interest to supplier selection in the facade systems segment.
Garden Equipment · 2026 — present
Full AI Visibility Framework Implementation
B2C: brand, categories, models, and expert personas
The largest project to date: 100+ prompts, AI Knowledge Factory, AI Expert Personas, and daily AI Visibility monitoring.
New Case Studies in Preparation
This section scales with us — new case studies will appear as projects are published and approved by clients.
Project Details
Determine how AI shapes answers to expert queries, which sources it uses, and whether visibility can be influenced through the digital ecosystem.
At the outset, brand presence varied significantly across platforms and phrasing. AI Search recommendations were theoretical, without data on platform influence.
Work Performed
- AI Visibility Baseline in ChatGPT and Alice AI
- a set of professional queries with phrasing variations
- expert content on VC.ru and Yandex Zen
- placements on RBC and industry media
- repeat measurements after each publication
Results
- ✓National media matter, but are not always the primary source for AI
- ✓Specialized content is often more relevant than major outlets
- ✓Changing prompt phrasing shifts sources and recommendations
- ✓A multi-tier model for managing knowledge sources was developed
The project produced the first validated data on platform-type influence — the foundation for Value for Money and the Knowledge Distribution Framework.
Three Business Scenarios
The methodology adapts to the client's business model — not one template for everyone.
Reputation
Narrow expert queries and corporate PR in AI
B2B
Project sales and long decision cycles
B2C
Category, brand, and the full digital knowledge ecosystem
Every Project Advances the Methodology
Completed case studies deliver results for clients and become a source of data for evolving AI Visibility Framework and the GEO-PLUS platform.
