Industries
AI agents for restaurants, hotels, and multi-unit hospitality operators
AI for restaurants and hotels should do the jobs that pull your people off the floor. The GM is the report. The phone rings during service. The group-sales inbox has forty unanswered inquiries and the one that mattered was Tuesday's. We build AI agents that do those jobs inside the POS, PMS, and accounting system you already run, with a person on anything that touches a guest or a dollar.
If this sounds like your operation, you're in the right place
Multi-unit operators run on people who know things: the GM who assembles the weekly numbers from three systems and a notebook, the host who answers the phone between seatings, the sales manager who lives in an inbox. Each of those people is expensive, and the work is not why you hired them.
The systems are already there. Toast or Square knows every check. The PMS knows every room night. QuickBooks or Restaurant365 knows every invoice and every payroll run. What is missing is the layer that reads across them and does the routine work, so your people can do the part that needs a person.
AI for restaurants and hotels: the agents we build
Reservation and phone agent. Answers every call during service, takes and confirms reservations into your reservation system, answers the twenty questions every restaurant gets (hours, parking, private dining, allergens from your menu data), and transfers anything unusual to a person. Systems: phone, reservation platform, POS. P&L line: covers booked from calls nobody could answer, host hours.
Group-sales inbox triage. Reads every inbound inquiry, pulls dates, headcount, and budget, checks availability, drafts the reply and the proposal from your templates, and queues it for the sales manager. Follows up on the schedule you set. Systems: email, PMS or event software, CRM. P&L line: group revenue, response time, inquiries that go cold.
Multi-unit P&L roll-up. The visibility agent. Daily and weekly: sales, labor as a percent of sales, prime cost, comps and voids, by unit and by daypart, from POS and accounting into one page on the owner's phone. Systems: Toast, Square, QuickBooks, Restaurant365, scheduling. P&L line: the margin problem you see on Tuesday instead of at month end.
Invoice capture to accounting. Vendor invoices from email and photos, extracted, coded to the right unit and GL account, matched to deliveries where you track them, queued for approval. Systems: email, Restaurant365 or QuickBooks. P&L line: bookkeeper hours, duplicate payments, food-cost accuracy.
Labor scheduling exceptions. Watches the schedule against forecast and actual sales and flags the shift that is overstaffed or the unit that is about to cross an overtime threshold. Systems: scheduling, POS, payroll. P&L line: labor cost.
A person reviews anything that reaches a guest with a problem in it or moves money, until the agent has run in parallel long enough to earn your trust.
How this fits a multi-unit operator
The value compounds with units. One restaurant's GM assembling the weekly numbers is a few hours. Eight units is a full-time job that nobody was hired for, done eight slightly different ways. The roll-up agent does it once, the same way, every day, and the owner sees all eight on one page with the outlier flagged.
The same is true of the phone and the inbox. One host missing calls during service is a few covers. Across units, and across a season on the coast, it is a line on the P&L. We rank all of it in the assessment so the first thing built is the one that pays.
Systems we work inside
Toast, Square, Clover. OpenTable, Resy, SevenRooms. Cloudbeds, Mews, Opera. QuickBooks, Restaurant365, MarginEdge. 7shifts, HotSchedules. Microsoft 365 and Google Workspace. If it has an API we use it; if it does not, we work from exports and say what that limits.
Built for the season, not the average
Coastal and destination operators do not have an average week. The phone agent, the inbox agent, and the labor-exception agent are set up around your calendar: they scale up for the summer and the holiday weekends without adding staff, and the owner report shows each unit against the same week last year, not against a flat budget. The assessment scores use cases on what they are worth in your peak, because that is when the missed call and the overstaffed shift cost the most.
Proof
The visibility agent for a multi-unit hospitality operator looks like this. The POS, the accounting system, and the scheduling tool each feed one store nightly, without a person exporting anything. On Monday morning the owner and each GM open one page: sales and labor by unit, food and beverage cost against target, covers and average check, AR from group and event business, and the three numbers that moved most since last week, with the reason attached. Anything outside the limits you set, a unit over labor target, a deposit that did not land, a vendor invoice that does not match, goes to a named person as an exception. The GM stops being the report.
That pattern runs in production today. For a Houston trucking company, the same digest-and-exception workflow watches every inbound container across their TMS, their tracking provider, and Microsoft Teams; dispatch reads one page and handles only the exceptions. The hospitality version swaps the port portals for the POS and the reservation system.
Founder-built by Jonathan Klein and Chip Ray, based in Houston. Insured: cyber liability, technology E&O, and general liability.
How we decide what to build first
A two-day AI Readiness Assessment at your operation. Day one, we walk the units with the GMs, the host stand, and the office. Day two, we score every candidate on P&L impact and risk and hand you a ranked backlog you keep. Then we quote the first build against written acceptance tests. If it misses them, the build fee is waived.
From $10,000, credited once against your first build. Build workstreams are fixed-fee, from $10,000. Managed plans from $1,200 a month. Prices verified September 2026. Full pricing →
What happens after go-live
POS and reservation vendors change their APIs. Our managed plan monitors every agent, fixes it when a vendor changes something, and includes engineering hours each month. How managed AI works →
Frequently asked questions
It identifies itself as an assistant when asked and never pretends to be a person. It transfers to a host or manager for anything unusual. Guests care that the call was answered and the table was booked.
Toast, Square, OpenTable, Resy, SevenRooms, and the major PMS platforms have APIs we work with. If yours does not, we tell you what that limits before you commit.
The assessment starts at $10,000 and is credited once against the first build. Agent workstreams are fixed-fee, from $10,000, quoted before work starts. Managed plans run $1,200 to $2,200 a month.
Yes. On site across Texas, remote across the US.