AI helps turn fragmented supplier files into structured bilingual product pages. Polished copy, however, never makes up for a wrong measurement or spec.
A new supplier sends over product files. Descriptions arrive in one language, dimensions sit scattered across inconsistent columns and key specifications hide deep inside PDF data sheets.
Before publishing those products, your team still has to gather the facts, verify what they mean and adapt them to fit your catalogue.
AI can take weight off the first draft: proposing cleaner titles, pulling characteristics from spec sheets, standardizing descriptions and producing initial translations. Still, useful output depends on clear business instructions.
Which specifications drive a buyer’s decision in this category? Which units do your customers expect? Which everyday trade terms do they recognize? Those choices prevent fluent copy from masking a mismatch.
Extra discipline matters whenever a source omits a figure or two sheets disagree. An unconfirmed spec should remain visibly open until checked; filling the gap with a plausible guess creates far more rework after launch.
At Progymédia, we build these enrichment workflows around available source documents and your team’s domain knowledge, so staff retain clear review control before anything goes live.
A category or spreadsheet formula often holds decisions refined over years of work. Making them understandable helps shape a tool that respects how your business operates.
What if the real challenge is not making artificial intelligence ever smarter, but making sure it helps us become smarter too?
