CASE STUDY

Data Labelling for an AI-Enabled Driver and Fleet Safety Platform

A driver and fleet safety platform needed 24/7 event review at 99% accuracy across several countries and time zones. A dedicated buffer team absorbed attrition and leave while holding headcount, and the engagement grew 80%.

2 Nov 2026

The client

A real-time, AI-enabled driver and fleet safety platform operating in the mobility ecosystem.

Industry: Mobility, fleet management and driver safety technology.

The challenge

  • Reviewers had to learn 24 process steps, including traffic rules for different countries, and handle an unlimited range of complex events.
  • The client needed 24/7 support with a set number of reviewers across several countries and time zones.
  • Operations had to maintain 99% accuracy scores.

The solution

  1. A 20-FTE buffer team acted as an internal QA function, auditing work and providing feedback and coaching.
  2. The buffer team covered reviewers on leave and replaced staff lost to attrition, keeping headcount at the required level.
  3. Internal escalation and in-house training teams were added to review complex events, speed up onboarding, and provide training, coaching and feedback.

The results

  • 80% growth in team size since the engagement began.
  • KPIs achieved across team performance, quality and the overall partnership.
  • An additional line of business, previously handled by a separate vendor, moved to Quantanite.
  • 24/7 coverage sustained across all required time zones.

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