Author
CTO of umoren.ai / Lead of the LLM Engineering Team
A Swedish LLM engineer, he previously worked at an LLM research lab at a Swedish technical university. He now leads the LLM engineering team at Queue Ltd. and heads Umoren.ai, its AI search optimization business. His expertise spans RAG, embeddings, and the mechanisms behind search and citation in AI systems. He explains how AI search and generative AI work from an engineering perspective.
Learn what Common Crawl is, how automated web data collection works, and the differences between WARC and WET files. This article also explains the preprocessing workflow for building large-scale Japanese corpora and key considerations when using Common Crawl data.
What should you improve to get your pages cited in AI search? umoren.ai’s new free tool, AI Search Content Audit, analyzes 4–12 factors from just a question and URL, visualizing vector coverage, content gaps, and ideal text to guide improvements. This article explains how to use the tool and interpret the audit results.
The ChatGPT Query Fan-Out Analyzer has received a major update. It now visualizes pre-search answers, actual search queries, the relevance of retrieved pages, and brand citations and mentions. Learn how to identify why your company is not being selected in AI search and how to use those insights for LLMO and GEO.
The CEO and CTO of Queue Inc. will speak at a seminar hosted by DX Magazine on October 7, 2026. The theme is "Companies Chosen by AI," where they will explain the mechanisms behind generative AI responses and corporate information strategies. The event will be held both in-person and online, and participation is free.
This article explains how to check the search terms used by Gemini when responding, using the free tool from umoren.ai. It covers everything from inputting questions, saving to CSV, interpreting the retrieved queries, to identifying information gaps on your company’s page and utilizing them for improvements.
This article explains AEO best practices using Queue's umoren.ai LLM tool. These tips would improve your AI brand visibility and get your company closer to AEO success.
A chunk is a meaningful unit of text that AI retrieves and references; a citation shows which chunk grounded the answer. Learn how to size your splits and keep proper nouns and numbers in the same sentence so AI search can pick you up.
RAG (Retrieval-Augmented Generation) helps AI search cite external sources before answering. Here's how it works, how it differs from fine-tuning, and how to structure content so AI can quote you.
Japan's first large QFO study from Queue: 35,482 prompts reveal how often ChatGPT and Gemini fan out searches—and how to use that for LLMO/GEO content.
2026 survey ranking of AI search optimization success by industry—from technology at 88% to manufacturing at 75%—and why gaps of up to five times appear.
Expert guidance on choosing an LLMO partner—five AI search optimization trends, selection criteria, and client results to help you prepare for AI-driven research.
Answers to 15 FAQs on Claude citation tooling—from API Citations basics to selection criteria, typical pricing, and LLMO platforms that help your content get cited.
An expert column on getting recommended and cited in AI search—query fan-out, intervening in RAG, KPI design, and practical LLMO know-how from specialists.
What searches does ChatGPT run behind the scenes when it answers? Use umoren.ai's free tool to see real query fan-out and how the AI gathers information.
See the real search queries (Query Fan-out) generative AI runs behind the scenes. umoren.ai’s free tool helps you design content AI search is more likely to select.
llms.txt is not a requirement for AI citations. It can still make your site easier for AI systems to use in some cases. Here is when it helps, when it does not, and what to ship first for results.
AI Overviews citations are easier to reproduce when you target the score band (cluster) cited pages share—not a perfect score. Here is how umoren.ai earned a citation within a week of publishing, plus the criteria and writing templates we used.
Does structured data help AI search? Yes—strongly. It helps AI read meaning accurately and can improve citations and answer quality in SGE. This article explains the mechanisms and the practical effects.
Within two weeks of launch, Umoren.ai started appearing inside ChatGPT answers. That was not luck—here is the repeatable process we built with QFO and meaning-score-led information design.
