@capo
AI-native restaurant operations · for multi-store operators

Run more stores. Without working more hours.

A virtual GM and a team of specialized AI agents handle hiring, inventory, execution, training, and analytics across every location — so multi-store ownership stops being a 70-hour week.

10·
Specialized agents
24 / 7
Working in the background
3+
Stores · multi-location native
POS · Indeed · cameras
Plugs into your stack
Section 02 · a day in the chair

By store #3, the owner becomes the operator. Capo gives the day back.

Pre-Capo: the owner spent the day reacting — phone buzzing before coffee, fires from every store, real work pushed to nights. Post-Capo: the morning is a 20-minute review of work the agents already did.

Before · the owner's reactive day
After · the owner's morning
06:45 · phone buzzing before coffee · manager texts · "out of avocado", "Maria called out"
07:00 · Capo flagged avocado low 2 days ago · vendor order in, arrives 11am · Maria's shift — bench texted at 5am, cover confirmed, manager notified
08:00 · log into Indeed · 50 overnight applicants · scroll, screen, message back · half are wrong fit
07:05 · all 50 resumes already screened overnight · 4 PASSES · approve 2 · interviews auto-booked
10:30 · new menu launches today · drive to both stores · check plating · check FOH placement · correct on the floor
07:10 · Floor Watch already verified the launch at both stores · plating on-spec · 1 minor flag, manager scheduled to correct by 07:40
14:00 · staring at last week's waste spreadsheet · can't tell which store is bleeding it
07:15 · waste traced to source · Capo: "halve braised pork prep at Phoenix · saves ~$30/day" · vendor order already adjusted · awaiting your approve
21:00 · couch · realize tomorrow's catering wasn't briefed · text manager mid-dinner
07:20 · catering brief already pushed to the right store this morning · close laptop · day on growth
See the full Ricemill day
Section 03 · why ai-native

AI bolted onto an ERP isn't AI-native. This is.

An AI-native product was designed around the agent first — not a forms-and-tables backend with a copilot bolted on the side.

Traditional SaaS
Capo · AI-native
Log in. Click through menus. Pull a report. Read the report.
Ask in plain English. Get the answer plus a recommended action.
Each module configured separately. The data doesn't talk.
Agents collaborate. Your virtual GM dispatches HR, Inventory, and Floor Watch automatically.
Train your staff to use the software.
The agent comes to you. You only need to approve.
You see the problem in a report. Then you go fix it.
The agent resolves the problem before you realize it's a problem.
Section 04 · meet your agents

Ten specialists.
One copilot in front.

You only ever talk to Capo. It briefs the rest. Each specialist owns a domain — hiring, inventory, the floor, training — and shares a single data foundation.

Section 05 · how it fits together

One virtual GM.
A team behind it.

Capo is in command. Specialized agents each own a domain, report up, and call each other's tools. They share a single data foundation. You only ever talk to Capo — it briefs the others.

You
Owner
Virtual GM
Capo · chat interface
cross-domain routing
Agent
HR
Agent
Inventory
Agent
Floor Watch
Agent
SOP Author
Agent
Forecast
Agent
Memory
Data layer
POS · delivery · Indeed · cameras · inventory ledger
Section 06 · differentiators

Why nobody
else has built this.

Single-store products stretched to multi-store don't reach. Generic chatbots forget you. Restaurant ERPs don't watch your floor.

01

Cross-session memory.

The agent gets smarter the more you use it. ChatGPT starts from zero every time. We don't. Preferences, store nicknames, the KPIs you watch, your industry-specific terminology — remembered, scoped to your account.

02

Multi-store native.

Central kitchen + multi-store dispatch / receive / reconcile, designed from day one for ≥3 locations. Not a single-store product stretched to fit a chain.

03

Camera-aware.

A Pi bridges to your existing NVR. The agent literally sees your floor — not just an API into your POS. FIFO scans, prep cadence, idle equipment — observable.

04

Built by operators.

We run a 2-store chain on Capo every day. Ricemill is customer #1 — every feature ships against a real P&L before a buyer ever sees it.

Section 07 · the numbers

We built it for ourselves first. Here's the math.

Ricemill is a 2-location concept that runs end-to-end on Capo. Numbers below are pulled directly from Riceman production. Updated as the deployment evolves.

30%
Waste reduction · YoY
40+ hr/wk
Owner time saved
+10%
Margin lift · this month
Read the full Ricemill case study

See what your stores look like with an AI ops team.