We call businesses
so you don't have to.
At scale.

“He paid €7.80 for a pint of Guinness in Dublin and decided he'd been overcharged.”

— Vice, April 2026

In early 2026, Matt Cortland built an AI voice agent named Rachel and had her call more than 3,000 pubs across Ireland to ask the price of a pint of Guinness. The result was the Guinndex — a live, continuously updated index of Guinness prices. One pub owner saw their listing and lowered their prices.

That story proved something fundamental: the physical economy is full of data that has never been digitized. Not because it's impossible to access — but because no one had built the right extraction layer. That data lives in people's heads, on whiteboards, behind a register. The only way to get it is to ask.

Dialed is what happens when you apply that idea to every category of local business, at national scale, with a compounding data asset that gets more valuable every day.

The internet digitized information. Search engines made that information findable. But the physical economy — prices, availability, wait times, inventory, appointment slots — was left behind.

Gas prices change twice a day and no one tracks them at the local level in real time. Restaurant wait times are invisible unless you're standing at the host stand. Medical appointment availability requires calling ten offices by hand. HVAC and plumber same-day rates exist only in someone's head.

Insurance underwriters are making policy decisions on businesses they've never visited. Fleet operators are routing trucks without knowing which stations are cheapest right now. Decisions worth billions of dollars are being made on missing or stale data.

All of that data is accessible via a 45-second phone call. We place those calls.

Dialed exists to make the physical economy as transparent as the financial markets. If Bloomberg can tell you the price of a bond in real time, Dialed should be able to tell you the price of a tank of gas, the wait at your nearest urgent care, and whether a plumber can come today.

We're starting with Oahu, Hawaii — an isolated market with high price sensitivity, strong local community, and a finite number of businesses to call. If the model works here, the playbook is copy-paste national.

The data we're building doesn't just have consumer value. It has B2B value, enterprise value, and — as the historical record accumulates — investment-grade analytical value. The dataset is worth more than the infrastructure that builds it.