WYnova

Lachenmeier: AI-validated working and driving hours

WYnova developed an AI system for Lachenmeier that cross-checks the teams' GPS data against planned tasks and cut the time spent reporting working and driving hours by around 90%.

Client
Lachenmeier
Sector
Industry
Team
Forward Deployed Engineer on site
Contact WYnova
AI validation of working and driving hours at Lachenmeier
Illustration of the validation system: GPS cross-checked against tasks
~90%

less reporting time

Real time

visibility for managers

GPS × tasks

cross-validation

Danish labour law

reduced risk of default

The challenge

At Lachenmeier, the reporting of tasks and driving hours was manual and inconsistent, affecting technicians' pay and creating a risk of non-compliance with Danish labour law.

Key obstacles

  • Manual data

    Inconsistent reporting with no transparency.

  • Time recording

    Working hours difficult to determine accurately.

  • GPS discrepancies

    Differences between the recorded route and the work carried out.

The solution

An AI validation system that cross-checks GPS data against planned tasks, integrates time records and flags inconsistencies, developed with a Forward Deployed Engineer on site.

Lachenmeier · horas e conduçãoReal time
  • Technician A: client visit Reported 7.5 hours · GPS 6.0 hours · discrepancy Validated
  • Technician B: maintenance Reported 8.0 h · GPS 8.1 h Validated
  • Technical C: installation Reported 6.5 hours · GPS 6.4 hours Validated

Discrepancies routed to the manager for review

Illustration of the validation developed for Lachenmeier: GPS cross-checked against planned tasks. Hours are illustrative.
  1. 01

    GPS

    Collection of the teams' routes and locations.

  2. 02

    Planned tasks

    Integration of the work plan and scheduled hours.

  3. 03

    AI validationAI

    Cross-checks GPS data against tasks and flags inconsistencies automatically.

  4. 04

    Signage

    Inconsistencies routed for human validation.

  5. 05

    Visibility

    Managers with real-time information to make decisions.

The right automation protects technicians and gives managers the information they need to make decisions.

Results

~90% less reporting time, more accurate and consistent records, real-time visibility for managers and a lower risk of non-compliance.

What we learned

When reporting affects pay and legal compliance, AI should flag the exceptions and leave the decision to a person. Human validation preserves accuracy and the teams' trust.

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