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
“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