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02Case study

Under development

Maria Multi Servizi

A workforce operating system for distributed teams.

Sector
Security & service companies · workforce operations
Where
Italia

An advanced workforce-management system for security and service companies whose people work across many sites. Under development: worker management, location awareness, shift and hour tracking, attendance, activity confirmation and AI-assisted alerts for supervisors.

Illustration of coordination between distributed workforce sites

  1. 01 · Workforce

    Dozens of workers, many of them alone on site, with shifts that change weekly.

  2. 02 · Locations

    Sites spread across a region. Each has its own expected coverage and checkpoints.

  3. 03 · Shifts

    Shifts define what should happen and when: start, rounds, handover, end.

  4. 04 · Signals

    Check-ins and confirmations become signals. Silence where a signal was expected is information too.

  5. 05 · Alert

    A missing signal raises an alert and requests an activity confirmation from the worker.

  6. 06 · Supervisor

    The supervisor sees exceptions with context and decides. No surveillance — accountability with dignity.

01 · Problem

When dozens of workers cover dozens of sites, a supervisor cannot know in real time whether a shift started, a round was completed or a site was left unattended. Information arrives late, by phone, and gets reconstructed afterwards.

02 · System

Workers, sites and shifts live in one model. Expected actions — start of shift, checkpoints, end of shift — generate signals. When an expected action does not happen, the system raises an alert and asks for an activity confirmation. Supervisors see exceptions, not noise.

03 · Technology

Next.js and NestJS services on PostgreSQL, a mobile-first worker interface, rule-based signal evaluation with AI-assisted anomaly detection planned, and an audit log for every alert and confirmation. Designed with data minimisation: the system records expected actions and confirmations, not continuous tracking.

04 · Impact

Goal: supervisors understand whether expected actions occurred — early enough to act. Attendance and hours become reliable data instead of reconstruction. Currently under development.

  • 1

    Model for workers, sites and shifts

  • 0

    Continuous location tracking

    by design

  • 24/7

    Signal evaluation

    planned

Capabilities

  • Worker management
  • Location awareness per site
  • Work-hour tracking and attendance
  • Shift definitions and expected actions
  • Alerts on missing signals
  • Activity confirmation requests
  • Operational oversight for supervisors
  • AI-assisted monitoring — planned

Stack

  • TypeScript
  • Next.js
  • NestJS
  • PostgreSQL
  • Mobile web
  • Rules engine
  • AI monitoring (planned)

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