Ruy Ramos
Product Experience Lead at Crystallize
Bio
Ruy has spent 15+ years where product data, content, and commerce meet, starting as a developer and moving through product management to opening new markets.
As Crystallize's first hire in Stockholm, he is building the Swedish market: partner ecosystem, customers, and the local case for content and commerce modeled as one thing.
Blog Posts (1)
Machine-Readable Product Data
AI does not need another product description explaining that Midnight means black, Pro means the expensive version, and usually ships quickly means somewhere between tomorrow and the end of the universe.
It needs product data where identity, attributes, relationships, variants, price, availability, language, and context are explicit.
That is what machine-readable product data means: product information structured so crawlers/agents/and who knows who else can reliably identify, query, compare, filter, transform, and act on it without first interpreting marketing copy.
And today, this matters beyond traditional SEO. Search engines consume structured data. Shopping platforms consume feeds. Applications consume APIs. Retrieval systems consume structured metadata and embeddings. AI agents increasingly consume tools and resources through protocols such as MCP.
The mistake is in trying to create a separate “AI catalog” for each of them.
A better architecture starts with one canonical product model and projects it into the formats different machines need: