An AI-generated scheduling tool built for a real retail store. It turns hours of manual spreadsheet wrangling into a compliant, budget-aware two-week roster in minutes.
Every two weeks, the store manager rebuilt the roster from scratch in a spreadsheet, reconciling contractual hour guarantees, shifting statutory-holiday hours, labor budgets, and role coverage all at once, entirely from memory and habit.
STAT shift codes.Needs a compliant draft fast, a quick replacement during call-ins, and confidence that guarantees and budgets are met without doing the math themselves.
Needs consistent scheduling patterns, fast approval on time-off, and confidence their availability window is actually respected.
I sat with the scheduling process directly, translated every contractual and operational rule into an explicit constraint set, and specified how an LLM could generate a compliant draft a manager could trust. I then built the application end to end: the rules engine, the AI integration layer (designed to work across multiple model providers), and the editing surface managers actually use every two weeks.
Direct client-to-API calls, designed to work across Gemini, Claude, and GPT models. Every response is forced into a structured JSON schema: a shift-code grid plus a plain-language rationale for every decision.
Enforces REG/RPT/PT hour bands, statutory-holiday shift codes, and role coverage before a draft ever reaches the manager.
Break generation runs client-side rather than through the LLM: deterministic, and immune to model drift. Flags overlapping breaks for employees sharing a role.
One click scans the roster for a valid replacement, respecting availability, hour caps, and time-off, then logs the absence automatically.
Compiled store constraints (availability, holidays, budgets, roles) go to the model as a single context. It returns a shift-code grid plus its reasoning, which the manager reviews inline before publishing.
The manual reconciliation (hour guarantees, statutory shifts, break conflicts, budget ceilings) now happens before the manager ever opens the board. They spend their time adjusting a draft and handling call-ins, not building the schedule from a blank grid.
Multi-location switching + a shared employee pool to borrow staff across nearby branches.
SMS/email schedule publishing plus an employee portal for manager-approved shift trades.
POS-driven traffic forecasting and direct payroll export (ADP, Ceridian).
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