Payments
Front of house- Tap, chip, and swipe at the counter or tableside
- Split checks by seat or by item, then adjust tips before batch
- Card-present and online sales land in one daily payout
AI-native restaurant management
Every order on one rail.
TicketRails is an AI-native restaurant management platform. Payments, online ordering, and kitchen display screens run as one system. AI agents take phone orders and learn what each guest likes, so every order can come with the right suggestion.
The stack
Three tools that already know about each other.
Most restaurants run payments, online ordering, and the kitchen on three vendors and reconcile them by hand. TicketRails shares one menu, one order record, and one ledger across all three, which is also what gives our AI agents the full picture.
Online store
Pickup & delivery- Your menu, on your domain, with no third-party commission
- 86 an item once and it disappears from the website and the register
- Set pickup windows so the kitchen never gets twenty orders for 6:30
Kitchen display
Back of house- Route each item to its station: grill, fry, cold, expo
- Ticket times change color as they age, so late orders stand out
- All-day counts show how many burgers are on the line right now
AI agents
An extra pair of hands on the phone and at checkout.
TicketRails is built AI-native, so the agents work from the same live menu, order history, and kitchen status as your staff. They don't need a separate integration to stay in sync.
Phone ordering agent
Answers calls during the rush, takes the order with modifiers, quotes a pickup time based on how busy the line is, and sends the ticket straight to the kitchen. Your staff stay on the floor.
Example call● AI agent
CallerHi, can I get two smash burgers for pickup? One with no onion.
TicketRails agentTwo smash burgers, one with no onion. The kitchen can have that ready at 7:15. Would you like a horchata with it? It's popular with the burgers.
CallerSure, add one.
✓ Ticket #1045 sent to grill · pickup 7:15
Guest recommendation profiles
Every order builds a profile of what a guest likes, when they come in, and what they usually add. The online store, the phone agent, and your servers use it to suggest the item that guest is most likely to say yes to, which lifts the average check.
Example profile● Updated tonight
Maya R.14 orders · usually Thursday pickup
- Orders
- Fish tacos, elote
- Avoids
- Dairy (noted allergy)
- Adds
- A drink on about half her orders
Suggest Horchata, dairy-freeFits her allergy
How it works
One order, from the guest's phone to the pass.
-
Guest orders
A guest picks a 6:45 pickup on your website, or calls and the AI agent takes it, and asks for
no onion. -
Card is charged
Before checkout, the guest's profile suggests an add-on they're likely to want. Payment is authorized in the same system that holds the order, so there's nothing to re-key.
-
Ticket fires
The burger goes to the grill screen and the fries to fry. Expo sees the whole ticket with the modifier flagged.
-
Bumped and picked up
Expo bumps the ticket, the guest gets a ready text, and the sale shows in tonight's report.
Running a restaurant? Tell us about it.
We're working with a small group of restaurants as we roll out. Send us a note about your setup and we'll get back to you.