The Machine Learning Partner for Industry

We help organisations across energy, engineering, and transport become AI-enabled in their digital transformation journey, by combining solution engineering, all-stages training, and the twinLab machine learning platform.

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digiLab

Industry’s leading engineering teams trust digiLab

The twinLab platform contains powerful modules for end-to-end ML workflows

Predict

Predictions unseen scenarios

Recommend

Optimise your sampling

Calibrate

Connect models and data

Automate

Query and understand your data

The twinLab platform scales from limited to complex data

Leverage existing knowledge and expert opinion
Quantify uncertainty in mission-critical systems
Integrate physical and engineering constraints
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twinLab

“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

Our solution engineers understand your data challenges

We meet you where you are with data, whether you haven’t yet started collecting, or have decades of analysis to explore
We speak your language, utilising in-house domain experts
We work in sprints to accelerate time-to-value, and support your teams towards self-managed deployment
  • Dr Andy Corbett

    Head of Research and Development

  • Dr Ross Allen

    Senior Technologist

  • Dr Dorothea Seiler Vellame

    Data Scientist

  • Dr Mikkel Lykkgaard

    Principal Scientist

  • Dr Anna Anderson

    Senior Data Scientist

  • Dr Nikolaos Papadimas

    Machine Learning Scientist

“digiLab’s innovative approach to using the data from cutting-edge sensors enabled us to discover how Machine Learning can gain us energy and cost savings, whilst also driving efficiency and water quality. ”

Nicholas Dade
Principle Scientist
South West Water

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