Transform your Industry with ML

Machine Learning is the next step in digital transformation. We provide the support your organisation needs to become ML-enabled, and offer solution engineering for the toughest challenges.

digiLab

Industry’s leading engineering teams trust digiLab

Fusion Energy

Optimise your R&D testing pathways
Accelerate complex simulations with powerful emulators
Reduce uncertainty in design and prediction
digiLab Fusion

Nuclear Fission

Build mission-critical digital twins with ease
Quantify uncertainty in complex systems
Augment digital tools with expert knowledge
twinLab

Water & Environment

Increase the efficiency of your resource usage
Optimise sensor placement to minimise cost
Understand emerging environmental risks
digiLab Water & Environment

Renewable Energy

Enable next-generation predictive maintenance
Build digital twins of your fleet with IoT integration
Solve innovation challenges using modelling
twinLab

Transport Networks

Increase network efficiency, across road, rail, and air
Enhance safety by understanding zones of uncertainty
Build next-gen traffic management systems using reinforcement learning
digiLab Transport

Advanced Materials and Manufacturing

Maximise component performance & lifetimes
Accelerate the time-to-value of your experimental campaigns
Build digital twins which respect physical constraints
twinLab

How we work with you

Our expert Solution Engineers identify how you can begin applying Machine Learning to your engineering challenges
We provide workshops, bespoke training, and support assistance to help your team to implement ML independently
Solve challenges and create end-to-end workflows using twinLab, the Machine Learning platform built for engineers
  • Dr Andy Corbett

    Head of Research and Development

  • Dr Ross Allen

    Solution Engineer

  • Dr Dorothea Seiler Vellame

    Data Scientist

  • Dr Mikkel Lykkgaard

    Principal Scientist

  • Michelle Fabienne Bieger

    Software Engineer

  • Dr Nikolaos Papadimas

    Machine Learning Scientist

“digiLab built a digital twin of the ATCO environment within three months by combining the best in modern software development practice, unique capabilities in probabilistic modelling, and a deep domain understanding of airspace management.”

Dr Richard Cannon
R&D Lead
National Air Traffic Services

“A lot of SMEs are specialising in AI and data science, but digiLab is the only one we know of built around state-of-the-art methods of uncertainty quantification.”

Dr Rob Akers
Director of Computing Programmes UKAEA
UK Atomic Energy Authority

Read our case studies and explore our demos

UKAEA

Uncertainty Quantification for Fusion

NATS

First-of-a-kind AI for Air Traffic Control

South West Water

Applying ML to Complex Sensor Data

Plasma State Prediction

Reducing simulation times to enable 25+ dimensional emulators

Optimising Tritium Material Testing

Predicting physical material properties to guide future experiments