Understand how AI discovers the world.
York Studio investigates how AI systems find, understand, cite, and recommend brands—then builds the intelligence and tools businesses need to respond.
AI answers are becoming a front door to products, services, sources, and ideas. The systems behind them are probabilistic, fast-moving, and still poorly measured.
York Studio exists to make that change legible.01 / The shift
Discovery is no longer just a list of links.
AI systems now assemble answers, compare options, and make recommendations before a person ever reaches a website. Visibility in that environment cannot be reduced to a universal rank—or improved responsibly without understanding the evidence underneath.
02 / Latest research
Work you can inspect,
not just conclusions.
Field guides, research protocols, studies, and method notes for a category that needs better evidence—not more confident acronyms.
View all researchField map
AI search, GEO, AEO and LLMO: a field guide to the terms
A plain-English map of AI search, GEO, AEO, LLMO, AI SEO, and AI visibility—and where each term is useful.
Answer variability
The AI Answer Variability Study
A null-condition study designed to measure how much AI answers move when the world being measured has not deliberately changed.
Measurement
Why one AI visibility score is not enough
A useful AI visibility measurement needs its evidence, sample, method, and uncertainty—not just a number that went up.
03 / The model
Research earns trust.
Trust compounds into intelligence.
The same evidence infrastructure that answers important public questions can power useful commercial tools. Each side makes the other sharper.
Research
Reproducible tests, transparent methods, primary sources, and results that include the inconvenient parts.
Intelligence
Clear analysis of what changes across AI search systems—and what it means for discoverability, trust, and demand.
Tools
Evidence-first software for measuring answers, tracking interventions, and separating observation from inference.
04 / AI Discovery Lab
Protocol in preparationHow much do AI answers change when nothing else does?
The AI Answer Variability Study will measure the null-condition movement of a fixed prompt panel across multiple systems. Its purpose is to estimate background noise, detectable effect sizes, and the limits of before-and-after visibility claims.
Read the protocol05 / Research standard
Confidence should be earned.
York Studio separates what was observed, what was inferred, and what can reasonably be attributed. The boundary is part of the result.
Read the methodologyEvidence before scores
Every metric should lead back to the answer, source, method, timestamp, and sample behind it.
Surfaces stay separate
An API observation and a consumer-product observation are useful—but they are not silently treated as the same thing.
Uncertainty is information
Negative and inconclusive findings are published because a truthful boundary is more valuable than a confident fiction.
06 / The platform
Answer intelligence, built from the evidence up.
York Studio is developing a platform that records what AI systems say, preserves the underlying evidence, measures change honestly, and turns observations into accountable experiments. Early design partners will help shape it.
07 / Accountability
“This field does not need another score nobody can interrogate. York Studio will publish the method, show the evidence, and say when the answer is inconclusive.”
Kristopher York
Founder & analyst, York Studio
The York Studio briefing
The signal, not the noise.
New studies, material platform changes, useful methods, and what the evidence means for people responsible for discovery and growth.
Join the briefing