Prepared for Kishore Vadla, Adelaide
Know who's on the floor, what's in the coolroom, and get your Fridays back.
This is what we heard in our conversation with Siva and Sujith, and how we'd fix it. We'd start with one café and about 35 staff, using products we already run for other clients.
One Saturday, rostered against what actually happened
How a shift becomes a pay run today
Domino's stores already run on the franchise's own systems. The Caffe Primo stores and the other restaurants in the northern suburbs don't, and that's where the hours go.
- Shifts go out on WhatsApp. Whoever puts a hand up first gets the shift. There is no roster to check hours against.
- Staff sign a paper register. They write the time they say they arrived. Phone-based check-ins were beaten by leaving the phone in the store.
- Someone types it into Excel. That's one sheet per café, every week.
- The sheet goes to the accountant. They import it into MYOB and run payroll. Overtime that nobody approved is already in there.
Half a day
of the owner's time every week, spent on timesheets across five cafés.
$25k
a year lost on ingredients. An extra 20 g of cheese per pizza adds up across every store.
No days off
in weeks. When the owner isn't on site, breaks stretch and shifts run long.
Three products we already run, in your order of priority
We won't build one big project. We'll deliver it as a program: each piece goes live on its own and proves itself before the next one starts. All three are Quantana products running for other clients today, so this is adapting what works, not starting from scratch.
First
QTimesheets
Timesheets and rostering, straight into MYOB.
Already in daily use by our team and by PX4 in Australia.
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The quick win
Timesheets that go straight to MYOB
Staff clock in and out on their phone or a tablet at the counter, and breaks are recorded as they happen. At the end of the week the manager approves, and it goes into MYOB through its API, or failing that as a one-click import file. No retyping, and no Excel.
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Next
Open shifts instead of the WhatsApp group
Open a slot and every eligible employee gets a notification. Staff nominate themselves, and the first to accept is locked in. Worked hours are then checked against the roster, and overtime needs approval before it reaches payroll.
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Next
Say what you did, by voice
Staff can speak their day ("prep from 8 to 10, then the lunch line") and it becomes a timesheet entry without anyone typing.
Second
AI Store Manager
Keeps an eye on the store when you're not in it.
Built on Godseye, our video analytics platform running in hospitality today.
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At the staff door
Check-ins nobody can fake
A swipe card, fingerprint or face check-in records the real arrival time. The register can't say 8:00 when it was 8:30, and nobody can sign in for someone else. It feeds QTimesheets directly.
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On the floor
Breaks and overstays, flagged as they happen
With smart cameras on the existing NBN line, it watches for a lunch running past its limit or someone still on at 7 when the roster said 6. You get an alert, and staff get a reminder that their shift has ended. That applies to the head chef too.
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Later
Customer insight from the same cameras
See how long customers wait before someone comes over, how long the counter queue runs, and a heatmap of the day that shows when to run a happy hour.
Third
KitchenOS ingredient menu system
Every dish knows its recipe, so every sale moves stock.
Just delivered for Meal Kraft, building on what we did for Ketosure in the US.
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Start here
Recipes linked to stock
We load your menu with ingredient quantities per dish. Each order through the POS (RedCat) deducts what it used. Staff do a quick count morning and evening, and the gap between expected and counted shows the waste, the cheese included.
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Then
Deliveries in, orders out
Scan a supplier's delivery docket in the morning and the stock is received automatically. When something runs low, one tap sends a purchase order to the right one of your seven suppliers.
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Then
Forecasts from what actually sells
Because stock is tied to dishes, we can see that fish and chips peak in November and order for it, rather than just noticing you bought more fish.
What the AI Store Manager sees
This is public shopping-centre CCTV run through Godseye. People are detected and tracked anonymously, and the boxed area is a zone: the system counts who enters it and for how long. In a café that zone would be the counter, the kitchen pass or the staff door.
- Faces found
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- Busiest moment
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- Average in frame
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- Longest stay in the doorway
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The figures are indicative. This is a crowded mall entrance filmed at 6 frames a second; a café with proper cameras gives cleaner numbers. Beyond staff tracking, the same feeds can show quiet periods worth promoting. Wednesday 3 to 5pm might be one. They can also show tables waiting too long for service. These are for later; staff time comes first.
Try both, working
These are live prototypes loaded with a sample week at Munno Para. Open them side by side: a face check-in at the staff door shows up in the manager's timesheet straight away.
Starting with one café
We'll prove it on one store of about 35 staff, then roll it out to the others. Timings are indicative until we've seen your data.
- This week
Live demo of QTimesheets and KitchenOS, set up with your café's data, then a two-page proposal with timing and cost.
- Weeks 1–3
Timesheets live at the pilot café. The first pay run goes to MYOB without retyping.
- Weeks 3–6
Menu and recipes loaded, POS sales deducting stock, and daily counts showing the variance.
- After that
Open-shift rostering, then the AI Store Manager at the pilot café, then the remaining cafés.
To set up the demo, we need
- One weekly timesheet spreadsheet as it goes to the accountant, with names removed
- Which MYOB product the accountant uses
- The menu with ingredients and quantities per dish
- The supplier list, and a sample delivery docket
- The POS details (RedCat) and the current camera and NVR model
And when the systems are running
Our team in Hyderabad can take on the back office, on Adelaide hours: payroll prep, supplier orders, admin, and keeping these systems running. One dedicated team that already knows your stores, instead of a person borrowed through the accounting firm.
Quantana, with Siva and Sujith