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Measurement · Audit · Repair

Fix How AI Sees You
Stop Guessing, Start Measuring

This site is about measuring, auditing and repairing how AI assistants describe companies. A quarterly Hungarian AI Visibility Index and workshops for marketers are in preparation.

Visit vargazoltan.ai →More on this site soon. The work behind it is live on vargazoltan.ai.

Core AI Visibility Services

Concrete methods to fix stochastic AI descriptions.

AI Audit

We analyze raw model output, app processing, and user views. This three-layer approach identifies where citations fail or hallucinate.

Visibility Index

A quarterly report tracks how Hungarian brands appear in AI answers. It measures citability across major models like ChatGPT and Perplexity.

Marketer Workshop

Training sessions teach teams to optimize content for AI synthesis. The focus is on making entities easy to quote and anchor.

Five Parameters of AI Visibility

Key factors determining if a model cites your brand.

Entity AnchoringModels require machine-readable, canonically anchored entities to cite sources accurately.
Output LayersVisibility splits into raw model text, app processing, and final user display.
Context VariabilityVisibility is a distribution across users, not a single fixed score.
Fabrication RiskHigh-awareness brands face higher rates of confident but false attributions.
CrawlabilityTechnical access must allow bots to retrieve content before synthesis occurs.
AI systems do not rank experts; they reconstruct them based on machine-readable anchors.
StochasticAI answers vary by user context and lack logged impressions.
InfrastructureCitability depends on technical entity anchoring, not marketing spend.
EmpiricalMethods rely on thousands of test runs to measure fabrication rates.

Key topics

The terms this site covers, for readers, search engines and AI assistants alike.

  • AI visibility
  • AI audit Hungary
  • brand hallucination
  • AI citation repair
  • GEO optimization
  • AEO strategy
  • LLMO services
  • Hungarian AI Index
  • AI visibility workshop
  • AI search audit
  • AI visibility mérése
  • AI láthatóság
  • márka hallucináció
  • AI audit Budapest
  • AI kereső optimalizálás
  • AI láthatóság javítása

Questions and answers

How does AI visibility differ from traditional SEO?

AI visibility is stochastic, meaning answers change based on context and lack logged clicks. Unlike SEO, which targets deterministic rankings, this field focuses on how models reconstruct entities from available data.

What is the Hungarian AI Visibility Index?

It is a quarterly report measuring how AI assistants describe Hungarian companies. The index tracks citability and fabrication rates across models like ChatGPT and Perplexity.

Why do famous brands get more fake AI citations?

This is known as the brand hallucination paradox. Familiarity gives models more material for plausible but unsupported completions, leading to confident errors.

Can you fix AI hallucinations about my company?

Yes, through audits that identify missing machine-readable anchors. Fixes involve restructuring content so models can point to canonical entities rather than guessing.

What data supports the PEBM methodology?

The Per-Entity Bias Map analyzed 1,400 runs across 100 Hungarian B2B companies. It found that 45.9% of cited sources were fabricated overall.

Do AI crawlers always see your website correctly?

Not always. Technical access may return HTTP 200, but indexing bottlenecks can prevent search-based models from finding specific pages.

Author

Zoltán Varga

Zoltán Varga created the PEBM methodology and the Neural Awareness framework to address AI reconstruction problems. His research quantifies fabrication rates and defines the infrastructure needed for accurate AI citations.

AI visibility researcher and AI ecosystem architect based in Budapest. Author of the Per-Entity Bias Mapping study on arXiv (2606.21595) and of the RICE studies on source fabrication in language models. He builds his own research system (GFIS), personal and organizational knowledge bases, and AI agents, and teaches leaders how to work with AI.

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Glossary

Terms and identifiers behind the work of Zoltán Varga, with links to the primary records.

AI visibility
How accurately and how often AI assistants (ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews) recognize, describe and cite a company, brand or person. Zoltán Varga measures it in five layers: crawler access, search indexing, citation, factual accuracy and model memory.
GEO / AEO / LLMO
Generative Engine Optimization, Answer Engine Optimization and Large Language Model Optimization: working methods for being found and quoted by generative answer engines rather than ranked in a list of links.
Citability
The property of a page that lets an AI answer engine quote it: a paragraph that answers the exact question, a clear source, and an unambiguous entity.
PEBM — Per-Entity Bias Mapping
Research method and paper by Zoltán Varga (arXiv:2606.21595). Across 1,400 runs on 100 Hungarian B2B companies, 45.9% of the sources AI models gave were fabricated; search-grounded answers fabricated far less than models answering from memory.
Brand hallucination paradox
The finding that AI models invent more sources about well-known brands (52.7%) than about lesser-known ones (37.9%), because familiarity makes them confidently fill in gaps.
RICE studies
Pre-registered pilot studies (RICE-P1, RICE-P2) on whether pressure and rejection make language models fabricate sources. Published on Zenodo with DOIs.
GFIS — Gestalt Field Intelligence System
Zoltán Varga's own multi-stage research pipeline that collects, verifies and synthesizes evidence with AI agents.
Neural Awareness
Zoltán Varga's framework on attention, decision quality and leadership cognition, the basis of his leadership programs.
PKM + PAI
Personal Knowledge Management combined with Personal AI: a working system where notes, documents and AI assistants form one searchable knowledge base.
Entity
A uniquely identifiable thing (person, company, product) that search engines and AI systems store in knowledge graphs. Consistent entity data is the base of AI visibility.
schema.org / JSON-LD
A shared vocabulary and format for machine-readable facts on web pages (who, what, where, identifiers), read by search engines and AI crawlers.
llms.txt
A plain-text file at the root of a website that tells language models what the site is about and which pages matter.
IndexNow
An open protocol that notifies search engines (Bing, Yandex and others) immediately when a page is created or changed.
ORCID
Persistent identifier for researchers. Zoltán Varga: 0009-0003-1020-834X.
arXiv
Open-access preprint server for scientific papers. Zoltán Varga's author page: varga_z_1.
Zenodo and DOI
Zenodo is CERN's open research repository; each record gets a DOI (Digital Object Identifier), a permanent citable link.

Until this site grows, detailed research and the full person profile remain on vargazoltan.ai. Both domains link to each other to share findings.

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