Corona is a working city, not a destination. Its economy leans on distribution and manufacturing: the warehouses and plants strung along the freight corridors, the family businesses and trades that supply and serve them, the retail that fills in around it. The buyer here is rarely a tourist and often not even a consumer. It is a purchasing manager sourcing a part, a project lead vetting a fabricator, a contractor pricing a job. That buyer has always done research before committing. What changed is where the research starts. A procurement lead now asks ChatGPT for Corona manufacturers who can hold a tolerance and turn a small run, or asks Perplexity which distributor in the Inland Empire actually carries a line, and starts the shortlist from whatever the model gives back.
A language model does not read a website the way a person skims one. It reads structure. Capabilities, certifications, the materials handled, the lines carried, lead times, the service area: plain facts it can verify and lift into an answer. Most Corona industrial and family-business sites carry none of that in a machine-readable form. They were built as a digital business card, not a data source. So the model leans on a national B2B directory or a marketplace that treats every vendor as a commodity, and the local supplier with the better answer never makes the list. For a B2B economy, being illegible to the buyer's assistant is lost pipeline, not just lost clicks.
This is not a plug-in for a brochure. The structure that makes a site legible to AI (clean markup, real specifics, verifiable sources) has to live in the foundation. So we build from scratch rather than retrofit a template that was never meant to be read by a machine.