Neo Genesis released a 486-measurement longitudinal benchmark of AI brand-mention rates on 2026-05-07, the first public dataset of its kind for Generative Engine Optimization research. The headline finding documents a 45 percent brand mention rate paired with a 0 percent canonical URL citation rate across 30 prompts and 3 frontier LLM providers.

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Seoul, Korea - 2026-05-07. Neo Genesis, the AI-native automation company operating 11 live business units, today released the AI Brand Mention Baseline 2026 dataset on HuggingFace under CC-BY-4.0. The dataset is the first public longitudinal benchmark for Generative Engine Optimization (GEO) research and is now the ninth open dataset on the neogenesislab account. The dataset captures 486 measurements collected daily between 2026-04-28 and 2026-05-07. Each measurement records a single LLM provider (Gemini 2.5 Flash, GPT-4 class, Claude class) responding to one of 30 standardized seed prompts spanning six prompt categories: definition, pricing, comparison, problem-solving, product-specific, and reputation. Each row preserves the full LLM response verbatim alongside structured mention counts for the brand name, the canonical domain root, subdomain occurrences, founder name, and any URLs the LLM chose to cite. The headline finding is the empirical baseline for the Trust Signal Gap. Across 486 measurements the brand name "Neo Genesis" appears in approximately 45 percent of responses; the canonical URL https://neogenesis.app appears in 0 percent. Frontier LLMs have learned the brand exists in their training corpora but have no signal pointing to a stable canonical URL. "This is the empirical evidence that the AI training corpus selection function is independent of brand-name awareness," said Yesol Heo, founder. "We are publishing the baseline so the next round of GEO interventions - explicit canonical URL self-references on every page, Schema.org citation chains, third-party backlink campaigns - can be measured against a real number rather than vendor marketing claims." Statistical context: 486 rows is large enough for chi-square tests on per-category mention rate variation; 30 prompts is the smallest seed set that still spans the full GEO category taxonomy; the 10-day window is the shortest interval that captures one full weekly cycle of LLM provider model updates. Daily cadence continues; the dataset will be updated quarterly with the rolling 90-day window. The dataset complements the eight previously published Neo Genesis datasets. korean-llm-citation-baseline-2026 captures the same methodology specialized for Korean-language prompts; korean-rag-ssot-golden-50 captures retrieval evaluation tasks; the EthicaAI and WhyLab datasets capture NeurIPS 2026 underlying evidence; the cross-agent-review-queue captures multi-agent collaboration patterns; sora-multi-device-orchestration captures the 6-device fleet operating model; quant-v11-ensemble-6alpha-specs captures the 9-Layer Kill Switch trading bot architecture; sbu-pseo-effects captures programmatic SEO outcomes. References: - Dataset: https://huggingface.co/datasets/neogenesislab/ai-brand-mention-baseline-2026 - Methodology source: https://github.com/Yesol-Pilot/neo-genesis/tree/master/scripts/geo_measure - Wikidata: https://www.wikidata.org/wiki/Q139569680 - Companion: korean-llm-citation-baseline-2026 (Korean-language version) - Citation reference: https://neogenesis.app/cite About Neo Genesis: Founded 2024, Seoul, Korea. 11 live business units, single autonomous AI operator. 9 published HuggingFace datasets, 9 Zenodo DOIs, 13 Wikidata entities, 22 DefinedTerm glossary entries. https://neogenesis.app.

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About Neo Genesis: Founded 2024 in Seoul, Korea by Yesol Heo. Operates 11 live business units with a single autonomous AI system. About →