SCALZ.AI Research
Original research on how AI engines cite sources
First-party studies of which URLs, domains, and entities ChatGPT, Perplexity, Gemini, and Claude actually cite. Authored by Tim Francis. No fabricated data, ever.
What does SCALZ.AI research?
SCALZ.AI runs original, reproducible studies of how AI answer engines select and cite sources. The flagship work runs a locked set of 60 commercial and local-service queries against ChatGPT, Perplexity, Gemini, and Claude and records exactly which URLs, domains, and named entities each engine cites. Every data point comes from a real engine response captured through an official API. No numbers are published without real data behind them.
Why original research matters for AI search
Original primary research is the single strongest citation magnet for AI answer engines. When ChatGPT, Perplexity, or Gemini needs a statistic or a source to back an answer, it reaches for attributable, first-party data. That is why every incumbent AEO agency leads with proprietary research, and it is the biggest gap between SCALZ.AI and the field.
A first-party, repeatable study of which sources AI engines actually cite is an asset no competitor can copy quickly. It is exactly the kind of original data the engines prefer to surface, and it is authored by a resolvable named expert, Tim Francis, whose entity foundation makes him the credible source of record.
Flagship study
The multi-engine AI citation study
A reproducible measurement of what AI engines actually cite across 60 service-business queries.
Study design
The study runs a locked set of 60 queries across the verticals SCALZ.AI serves: 20 healthcare and behavioral health, 15 home services, 10 legal and professional, 10 AEO and meta queries, and 5 local-intent queries. Each query runs against all four engines, producing 240 engine responses per run. The query list is frozen in a versioned file before any run so the dataset is reproducible.
Engines and method
Four engines are measured through their official APIs, not browser scraping: Perplexity (Sonar), ChatGPT (OpenAI Responses API with the web search tool), Gemini (Google AI Studio with Google Search grounding), and Claude (Anthropic with the web search server tool). Each returns cited URLs natively. Google AI Overviews is tracked as an optional fifth surface only, because it has no official API and browser-based collection is brittle.
What we capture
For every response we record the engine, query, timestamp, model, answer text, the cited URLs, the cited domains and their category (agency, publisher, directory, Reddit, Wikipedia, brand site), whether SCALZ.AI or a known competitor appears, and the presence of a statistic or named expert. The output is both a published report and a machine-readable dataset.
Status
The study design is complete and the methodology is published here openly, before any results are collected. Execution is pending API access and budget. When results exist, they will be published at scalz.ai/research/ai-citation-study-2026/ with the full dataset, and every number will trace back to a real captured response.
Questions
Frequently asked
What research does SCALZ.AI publish?
SCALZ.AI publishes original research on how AI answer engines select and cite sources. The flagship study runs a locked set of 60 commercial and local-service queries against ChatGPT, Perplexity, Gemini, and Claude and records which URLs, domains, and entities each engine actually cites.
Who authors SCALZ.AI research?
Tim Francis, founder and CEO of SCALZ.AI, is the named author of record. The entity foundation built across the SCALZ.AI site makes him resolvable as the expert behind the research.
Does SCALZ.AI fabricate citation data?
No. Every citation recorded in a SCALZ.AI study comes from a real engine response captured through an official API. No numbers are published without real data behind them. The study design is published openly before results are collected.
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