Built for retail only
Store shift schedules, built by AI agents
Give it your staff, their availability and your store traffic. Get back a schedule that covers the rush, then let employees ask for changes in plain language. A concept for retail stores, not a working product yet.
Made for retail, and only retail
Supermarkets, grocery and chain stores with hourly staff on the sales floor, at the checkouts and behind the counters. No restaurants, no warehouses, no generic workforce tool.
One schedule from three inputs
Employee list, availability and store traffic go in. A draft schedule that covers the busy hours comes out.
Employees talk to it directly
“Can I swap Thursday for Saturday?” The assistant checks the rules and proposes a change for the manager to approve.
Built for sliding shifts
Staggered starts and ends that follow the day’s traffic are exactly what made manual scheduling painful.
How it would work
From a spreadsheet to a schedule your team can talk to
Four steps, one idea: the agent does the puzzle, people make the decisions.
Describe the store once
Staff, availability and traffic go in once: from the spreadsheets you already keep, the till export or your own estimate of the busy hours.
- Roles, contracted hours, rest rules
- Recurring and one-off availability
- Traffic by hour from footfall, receipts or a best guess
Shifts that follow the rush
The agent drafts sliding shifts: more people on the floor at lunch and after work, fewer when the store is quiet. Every busy hour is covered and no rule is broken.
- Coverage checked hour by hour against traffic
- Gaps and overtime shown, not hidden
- Choices explained in plain words
Employees ask in plain language
“Can I swap Thursday for Saturday?” The assistant finds who can cover without breaking rest, hours or availability, and asks the colleague.
- Swaps, days off, later starts
- No pressure on colleagues to say yes
- Nobody sees more than they need to
The manager keeps the last word
The manager gets one ready-made change instead of a chain of messages, and approves or rejects it in one step. The published schedule updates for everyone.
- Every change re-checked against the same rules
- One decision instead of an afternoon of calls
- Nothing is approved automatically in the first version
Who it is for
Made for store managers, not for every business with shifts
Our whole focus is retail. The rules, the traffic model and even the words in the product are built around a store.
Supermarkets and grocery
Long opening hours, two traffic peaks a day, deliveries in the morning and a till that must never stand empty.
Small store chains
Two to twenty stores, one or two people doing all the scheduling, usually in a spreadsheet, usually on a Sunday evening.
Specialty and convenience retail
Drugstores, DIY, fashion and convenience stores with hourly staff, students and part-timers on sliding shifts.
Tools such as Deputy already build schedules from demand. Our angle is narrower: conversation instead of configuration, the change loop after publication, and sliding shifts in stores. Deputy and our angle →
How we plan to reach stores
Start with stores we know, then let one store bring the next
A go-to-market hypothesis, not a plan in motion. Each step has to prove itself before the next one.
Pilot with managers we know
Stores that ran sliding shifts with us, on their real data, free, until the schedule is one they would publish.
A free schedule check
Upload your current schedule spreadsheet and get back the uncovered hours, the broken rest rules and a draft that fixes them.
Useful content for managers
Sliding-shift templates, rest-rule checklists and peak-hour staffing guides that store managers actually search for.
Retail communities and franchises
Retail associations, franchise networks and trade events, where one conversation reaches many stores at once.
Partners who hold the data
Point-of-sale and footfall-counter vendors and retail consultants: they already have the traffic data and the trust.
One store, then the chain
A manager who saves an evening a week tells the area manager. Expansion inside a chain is the cheapest sale.
Nothing is built yet
The next step is a small prototype on one real store’s data. If you run a store with sliding shifts, the open questions are where to start.
See the open questions