The AI that lets a restaurant manager ask a database a question - and get an answer in plain English.
It is 6 a.m. somewhere with a Whataburger in it. A district manager opens her phone, types "which of my stores wasted the most produce last week," and reads a sentence back. No spreadsheet. No analyst on a Slack thread. No Tableau dashboard that someone built in 2019 and nobody trusts anymore. Just an answer. That sentence is Expo's entire reason for existing.
Expo is an AI platform for multi-unit restaurant operators. It plugs into the dozen systems a chain already runs - point of sale, inventory, labor scheduling, guest feedback - and pulls them into a single place that anyone can interrogate in ordinary language. The pitch on the homepage is blunt: "Stop pulling reports. Start asking questions."
Restaurants are drowning in data and starving for answers. A regional chain might generate millions of transactions a month across Toast, Restaurant365, Crunchtime, Square and DoorDash. All of it is technically available. Almost none of it is usable by the person who actually decides whether to cut a shift or reorder tomatoes.
That gap - between data that exists and data you can use at 6 a.m. - is the problem Expo built a company around. The numbers were always there. Someone just had to make them talk.
Walk into the back office of any growing restaurant group and you will find a smart, exhausted person exporting CSVs. They are not a data scientist. They became one by accident, because the numbers wouldn't assemble themselves.
The modern restaurant runs on software - and that is exactly the trouble. Each system is excellent at its one job and oblivious to the others. The POS knows sales. The inventory tool knows food cost. The labor app knows hours. None of them talk, so a manager who wants to know "are we losing money on the lunch rush" has to become a translator between four vendors before breakfast.
The traditional fix was business intelligence: hire an analyst, license Tableau, build dashboards, wait. For a chain with thin margins and high turnover, that is a luxury and a bottleneck. By the time the report arrives, the lunch rush it described is two weeks cold.
Expo's read on the industry is unsentimental. The insight that saves a location is usually simple, usually available, and usually trapped behind a tool only the IT department can drive. Remove the driver, and you remove the wait.
Will Pacio knows the back of house from the inside. Before he founded anything, he cooked in Thomas Keller's kitchens - The French Laundry, Per Se - the kind of places where a quarter-second of inattention ruins a plate. He later opened his own fast-casual chain. So when he talks about restaurant busywork, he is describing chores he has personally done at 2 a.m.
His co-founder, Dave Lu, arrived from the other side of the table: Yahoo, Apple, eBay. Together they first built Pared, a marketplace that filled restaurant shifts - more than 200,000 of them across San Francisco, New York, Washington and Philadelphia, staffing everyone from Halal Guys to Michelin dining rooms. They learned the industry by solving its labor crunch.
Then they made a bet that looks obvious in hindsight and was not at the time: the next restaurant crisis was not finding people, it was the mountain of data those people couldn't read. So they rebuilt the company around AI and renamed it after the one person in every kitchen whose whole job is coordination - the expo, the expediter who stands between the line and the dining room and makes sure the right thing reaches the right place at the right time.
Pictured in spirit: two founders who agree the most important tool in a restaurant is the one nobody notices working.
Expo doesn't ask you to replace anything. It asks the tools you have to start cooperating.
POS, inventory, labor and guest feedback pulled into a single intelligent view - the whole operation on one screen.
Query your business through conversational AI, including Claude and ChatGPT. No SQL, no analyst, no waiting on a report.
Dashboards scheduled and delivered across teams before the morning shift - the answers arrive before the questions do.
Connectors for Toast, Restaurant365, Crunchtime, Square, DoorDash and dozens more systems out of the box.
Will Pacio and Dave Lu launch a marketplace to fix restaurants' hardest problem at the time: staffing.
Early backing from investors including CRV and True Ventures.
Capital from CRV and Bossa Nova to scale the shift-filling marketplace.
From Halal Guys to Michelin kitchens across SF, NYC, DC and Philadelphia - and a machine-learning profit lift announced for Romano's Macaroni Grill.
The company rebuilds around operational AI and rebrands to Expo.
Recognized at the Multi Unit Restaurant Technology Conference.
A demo is easy. Names on the customer list are harder. Expo has both.
A customer roster that runs from drive-thru to white tablecloth - which is the point. The data problem doesn't care what's on the menu.
Illustrative breakdown of the cost areas Expo helps operators interrogate. Directional, not a financial statement.
Expo states its mission plainly: make restaurant life easier and more profitable, by automating the busywork so staff can get back to the part of the job that is actually hospitality. The founders' wager is that the best restaurant technology is invisible - it does the chore and disappears, the way a good expediter never ends up in the customer's photo of the meal.
It is a hospitality argument dressed as a software argument. Every hour a manager spends reconciling spreadsheets is an hour not spent on the floor, with the guest, with the team. Expo treats that reclaimed hour as the real product. The dashboard is just how it gets delivered.
The advisor list reads like the wager is shared. Yelp co-founder Jeremy Stoppelman, chef Thomas Keller, and DoorDash and Square veteran Gokul Rajaram have all lent their names - a rare three-way handshake between the worlds of food, reviews and payments that Expo is trying to stitch together.
Skeptics will note that "AI for restaurants" is a crowded phrase in 2026. Expo's answer is that it didn't arrive from a pitch deck. It arrived from a kitchen, by way of a staffing marketplace, with a decade of scar tissue to show for it.
Restaurant margins are thin and getting thinner. Labor is scarce and getting scarcer. The chains that survive the decade will be the ones that can see clearly and decide fast - which, increasingly, means the ones whose data can hold a conversation.
Return to that district manager and her phone. A few years ago, the question "which store wasted the most produce" would have meant an email, a wait, a half-built dashboard, and a meeting where everyone quietly distrusted the chart. Now it is a sentence, asked into a box, answered before her coffee is cold. She closes the app and goes to fix the actual problem - the one in the walk-in cooler, not the one in the spreadsheet.
That is the change Expo is betting the company on. Not smarter dashboards. Fewer of them. The numbers were always there at 6 a.m. Expo's contribution is that, finally, they answer when you ask.