An AI-generated scheduling tool built for a real retail store — turning 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 across three providers, and the editing surface managers actually use every two weeks.
Direct client-to-API calls to 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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