Companies/TOMRA Food (ANZ) Limited

TOMRA Food (ANZ) Limited

manufacturingmature3/10researched

HQ

Leuven, Belgium

NZ Employees

50-100 (estimate, part of 200+ AU/NZ team)

Industry

sensor-based food sorting and post-harvest processing equipment

NZ Presence

Head office at 4 Henderson Place, Onehunga, Auckland; Field Research Centre in Hamilton/Waikato; Research Orchard in Waikato; additional hub in Papamoa; focuses on sales, service, customer support, and R&D for food sorting solutions.

AI Focus Areas

optical sortingdeep learning (LUCAi)machine learning for defect detection

AI Maturity Evidence

Develops proprietary AI technologies integrated into sorting machines since 2019, including LUCAi deep learning models for fruits/nuts, TOMRA 4C AI-powered sorter combining ML and deep learning, publishes AI guides for food industry customers.

Transformation Opportunities

AreaOpportunityImpactComplexity
OperationsAI-driven predictive maintenance analyzing sensor data from deployed sorters to preempt failureshighmoderate
R&DAI simulations and generative design for optimizing sorter hardware and software configurationshighcomplex
SalesAI-powered recommendation engine matching customer crop data to optimal sorting solutionsmediumsimple
ServiceAI-optimized technician dispatching and route planning using real-time field datamediummoderate

Decision Makers

Paul Slupecki

Head of TOMRA Food APAC / Director

LinkedIn

Oversees NZ operations including sales, service, and R&D; strategic leader for regional growth and technology deployment.

Wayne Puckey

Digital Transformation Leader

LinkedIn

Leads digital initiatives in Auckland; purpose-driven focus on transformation aligns with AI workflow enhancements.

Nicolaas Marinus Cornelis Buyck

Director

Serves on board of TOMRA Food (ANZ) Limited; influences operational and investment decisions.

Tech Stack Signals

optical sensorshyperspectral imagingAI/ML frameworks (deep learning, machine learning)embedded softwarefield research facilities

Competitive Landscape

Market leader in sensor-based food sorting; competitors (e.g., Bühler, Key Technology) are rapidly adopting AI/ML for similar applications, pressuring continuous innovation in sorting accuracy and speed.

AIA Fit Assessment

  • --Clear NZ operations and R&D presence with growth signals
  • --High budget and technical hiring indicate investment capacity
  • --However, mature internal AI capabilities in core products reduce reliance on external consulting
  • --Enterprise scale suggests preference for in-house development

Hiring Signals

Total Roles

1

Remote

No

Levels

senior

Skills Sought

systems engineeringsensorsfood technology

Company Timeline

2026-02-08

First tracked

Engagement Angle

Leverage AI to supercharge your field service operations—predictive dispatching could cut sorter downtime by 30% and boost NZ customer satisfaction.

Recommended AIA Service

Process Automation Sprint

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