Genesis 01: a vision benchmark for fashion AI.
Benchmarks fashion-intelligence behavior across CLIP, SigLIP, and DINOv2: uncertainty, impostor detection, and collection cohesion.
Genesis is our research on how AI decides what people buy.
Each numbered study measures one piece of it: how models see products, which brands they prefer, and where they send the buyer.
Dated and sourced. Built from live shopping conversations, model outputs, and routing evidence.
Each study is a different lens on how machines see and choose products.
Together they map the systems now sitting between shoppers and stores: what breaks, what gets favored, and what brands can actually control.
Research papers
Genesis 02: LLMs’ favorites.
Maps how leading language models converge on the same designers, garments, and fashion narratives when taste is inferred from prompts alone.
Genesis 03: AI shopping visibility and the buy path problem.
Follows ChatGPT and Gemini recommendations into the routing layer: official product pages, retailer leaks, and missing purchase paths.
What these studies are really measuring.
The recommendation systems hidden inside current models: the assumptions they make, the tastes they overfit to, and the sales they now influence.
Can a model actually distinguish brand, season, and design family from the image itself?
Which objects and creators recur across models when taste is generated from text?
How likely is a brand to be named in AI-mediated shopping?
Does the model know when it does not know, or does it hallucinate authority?
Genesis 03 follows the buy path.
The latest study tracks what happens after AI names a brand: the buyer lands on the brand’s own page, leaks to a third-party seller, or gets no usable path at all.