ShiftOps AI Intelligent Workforce Recovery

**ShiftOps AI Intelligent Workforce Recovery** Manufacturing operations often face unexpected employee absences, unfilled shifts, and scheduling conflicts. Finding qualified replacements manually can be time-consuming and error-prone, especially when managers must consider employee availability, approved leave, role requirements, overlapping shifts, and working-hour limits. ShiftOps AI is an intelligent workforce recovery assistant designed to help operations managers respond to these challenges through a structured, transparent, and auditable workflow. **How It Works** When a staffing shortage occurs, a manager creates an incident for the affected shift. The system evaluates available employees using deterministic scheduling rules, identifies eligible replacements, and explains why other candidates are excluded. The manager can then create a staffing proposal, review the recommendation, approve or reject it, and apply an approved change. Before updating the roster, ShiftOps AI revalidates eligibility to prevent stale or conflicting assignments. Scheduling changes and audit records are committed transactionally. **AI and AMD Integration** ShiftOps AI includes an AMD Token Factory integration designed to generate grounded explanations from validated staffing information. The architecture prevents language models from overriding eligibility rules or directly modifying schedules. If remote inference fails, the system uses a clearly labelled deterministic fallback. **Technology Stack** React, TypeScript, Vite, Node.js, Express, Prisma, PostgreSQL, and an AMD Token Factory integration adapter. **Business Value** ShiftOps AI supports faster staffing decisions, reduces the risk of invalid assignments, and improves management accountability through human oversight and traceable audit records. The prototype demonstrates an end-to-end workflow from staffing incident to approved schedule update, with reproducible tests and synthetic manufacturing data.