The problem with most capability pages
Most manufacturing capability pages are written for a reader who already understands the industry: dense paragraphs, marketing language, and abbreviations that assume context. A human specialist fills in the gaps. An AI model cannot. Reading the same page, it struggles to extract the specific facts a buyer actually filters on — what is manufactured, at what scale, under which certifications, for which markets.
Illustrative before
“With decades of combined expertise, our state-of-the-art facility delivers world-class solutions across a diverse portfolio, backed by a commitment to quality and innovation that sets us apart in a competitive landscape.”
This sentence appears, in some form, on countless manufacturing websites. It reads as confident. But it contains no verifiable, extractable fact: no product category, no certification, no capacity, no market. To an AI model asked a specific buyer question, it is effectively silent.
Illustrative after
“We manufacture WHO-GMP certified oral solid dosage tablets and capsules, with an installed capacity of [X] million units per month, exporting to [named regions]. Our facility holds [named certifications] and specialises in [named therapeutic categories].”
The restructured version gives an AI model unambiguous facts it can extract and confidently repeat when a buyer asks a relevant question. The bracketed values are placeholders — in real execution, the actual language and figures are always specific to the organisation.
Why this matters commercially
The capability page is often the single most important page for AI Discovery, because it is where a buyer’s specific question meets your specific answer. A page that reads well to humans but says nothing extractable to AI quietly removes you from shortlists you would win on merit. Rewriting it for extractability is frequently the highest-impact single change in an engagement.