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.
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
Nuclear Fission
- Build mission-critical digital twins with ease
- Quantify uncertainty in complex systems
- Augment digital tools with expert knowledge
Water & Environment
- Increase the efficiency of your resource usage
- Optimise sensor placement to minimise cost
- Understand emerging environmental risks
Renewable Energy
- Enable next-generation predictive maintenance
- Build digital twins of your fleet with IoT integration
- Solve innovation challenges using modelling
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
Advanced Materials and Manufacturing
- Maximise component performance & lifetimes
- Accelerate the time-to-value of your experimental campaigns
- Build digital twins which respect physical constraints
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.”
“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.”
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