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Adem Ajvazi

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This article is about the search engine optimization consultant and NLP researcher. For his consultancy, see Northquery.

Adem Ajvazi is a search engine optimization consultant, answer engine optimization specialist and natural language processing researcher based in Copenhagen, Denmark.[2] He is the founder of Northquery, a consultancy that engineers brands into the answers produced by AI systems such as ChatGPT, Gemini, Claude, Perplexity and Google AI.[4] His research on offensive language detection, written with Christian Hardmeier, was presented at the Thirteenth Language Resources and Evaluation Conference (LREC 2022) in Marseille and is published in the ACL Anthology.[1]

Ajvazi has worked in search since 2011, moving from traditional rankings to retrieval and AI citations. His consulting practice is known for a guarantee under which a client does not pay if AI systems have not cited the brand within 60 days of the engagement.[4]

Education [edit]

Ajvazi holds a Master of Science in Computer Science with a specialization in Natural Language Processing from the University of Copenhagen.[2][4] His thesis focused on detecting and classifying offensive language on online social media using large language models built on the transformer architecture, the same family of models behind systems such as ChatGPT, Claude and Gemini.[2]

Through this work he gained direct experience with vector embeddings, semantic similarity, attention mechanisms and retrieval systems, a foundation he later applied in his commercial work on AI search.[2]

Research [edit]

In 2022, Ajvazi and Christian Hardmeier published A Dataset of Offensive Language in Kosovo Social Media in the proceedings of LREC 2022, the Thirteenth Language Resources and Evaluation Conference held in Marseille, France.[1] The paper introduced a new dataset for offensive language detection in Albanian, built from user generated comments on the Facebook and YouTube channels of selected Kosovo news platforms and labelled at the three levels of the OLID annotation scheme.[1]

The study also examined transfer learning between languages. Merging the Albanian and Danish training sets improved prediction on Danish, but not on Albanian, for both offensive language recognition and for distinguishing targeted from untargeted offence.[1] The paper is indexed in the ACL Anthology, the reference archive of the Association for Computational Linguistics.[1]

Adem Ajvazi on stage presenting A Dataset of Offensive Language in Kosovo Social Media at LREC 2022 Click image to view full size
Ajvazi presenting the paper at LREC 2022 in Marseille

Career [edit]

Search engine optimization [edit]

Ajvazi entered search engine optimization in 2011 and has spent 15 years shipping, ranking and measuring websites at scale.[4] Alongside client work he builds and operates a portfolio of content and directory websites, with a focus on programmatic publishing and fast static architectures.

Across his engagements, more than 32 million dollars in client revenue has been tracked through search and AI answers, with figures pulled from client analytics and published with written permission.[4]

Northquery and answer engine optimization [edit]

Ajvazi founded Northquery to focus on answer engine optimization, the practice of making a brand the answer that AI assistants give when buyers ask. The consultancy audits how ChatGPT, Gemini, Claude, Perplexity and Google AI describe a brand, engineers content that language models can retrieve and cite, and tracks the resulting citations week by week.[4]

Published case studies include CarCover.com, which went from absent in AI answers to 138 brand mentions in 60 days with 14 Google AI Overview features, JustPark, which saw organic traffic rise 110 percent alongside 1,300 new AI citations for city parking queries, and Midtown Umbrellas, which recorded an 86 percent lift in organic traffic with 270 new AI citations.[3]

Northquery operates under a guarantee: if AI systems have not cited the client by day 60 of the engagement, the client does not pay.[4]

Method [edit]

Ajvazi frames his process as a loop of three stages: diagnose, engineer, dominate. The first stage maps the real questions buyers ask AI assistants and audits which brands each model names today. The second rebuilds content around brand entity mapping, query to answer matching and citation ready structures that models can lift cleanly, supported by structured data. The third holds the answer through competitive displacement, monitoring across every engine and reporting that ties citations to leads and revenue.[4]

Internally he has codified this into the QED Framework, short for Quantify, Engineer, Demonstrate, the branded methodology behind Northquery engagements.

Views on AI search [edit]

Ajvazi argues that discovery is shifting from pages of search results to short answers. When a buyer asks an assistant, the reply is a shortlist of a few names, and clicks fall when an AI answer appears, so a brand is either inside the answer or invisible to that buyer.[4] He also holds that models keep naming the brands they already trust, which gives early movers a durable head start.[4]

He is critical of optimization that treats language models as a black box. In his view, effective work in this area requires understanding how retrieval and citation actually operate inside the models, drawing on embeddings, semantic similarity and retrieval augmented generation rather than on guesswork.[2][4]

See also [edit]

References [edit]

  1. Ajvazi, Adem; Hardmeier, Christian (June 2022). "A Dataset of Offensive Language in Kosovo Social Media". Proceedings of the Thirteenth Language Resources and Evaluation Conference. Marseille, France: European Language Resources Association. pages 1860 to 1869. Retrieved 30 July 2026.
  2. "About". Northquery. Retrieved 30 July 2026.
  3. "Case studies". Northquery. Retrieved 30 July 2026.
  4. "AI Search Optimization and AEO Engineering". Northquery. Retrieved 30 July 2026.

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