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At Decision Lab we carry out the full range of technology development, from underpinning research to full product development, and we provide consultancy support at all levels. Over the years we developed some powerful capabilities:

  1. EBSD – we developed an industry leading Economic Balance of Supply and Demand (EBSD) that allows water companies to optimise their investment in the water supply. It’s been used by Thames Water, South East Water, Welsh Water and more, as they make their plans and prepare their regulatory submissions.
  2. The next generation water investment model​ – recently we’ve completely reworked the water investment modelling approach to provide a much more advanced capability that considers a very wide range of criteria and also provides plans that can best handle the uncertainties of the future. It’s going to be the modelling core of the 8 water companies in South East England. We do need to come up with a better name though.
  3. We developed ROSE for South East Water after the infamous “Beast from the East” cold weather event, where major burst meant that reservoirs were almost depleted and water supply to customers lost. ROSE identifies risk of reservoir water levels falling below minimum thresholds and determines pumping interventions to avoid this.
  4. CHARM​ – we’ve developed an early infrastructure investment model for the electricity industry. We expanded this into condition modelling for canals and waterways in England and Wales. With CHARM we’ve made this into a product that can be applied to pretty much any industry with infrastructure and decisions to make on maintaining and investing in it. We’ve been supporting a client applying it to a major naval dockyard in the UK.
  5. SCAF​ is one of the first models we produced, and it’s still being used by the client, Rolls-Royce. It models the maintenance and support process for their aerospace engine business. It predicts demand for their services over the next 25 years. It enables them to do business planning for an area that represents 40% of their turnover.
  6. ATOM is a Digital Twin​ of Siemens’s Aero-derivate gas turbine fleet and support systems, which is used for power generation in difficult to reach geographies in the oil and gas sector. It gives complete visibility on the status of the fleet, and can predict what will happen over the next 3 days, 3 weeks, 3 months, 3 years, even 30 years. It allows them to optimise maintenance, plan the supply chain and mitigate risks.
  7. Polymer is a revolutionary version-controlled graph database. Its focus is on tracking  and managing experimental configurations of analytical tools and models, which allows efficient exploitation of results to gain the most value from them.
  8. Foresense is an advanced AI model that predicts rare failures of components onboard aircraft and ships. It uses advanced machine learning techniques to estimate the time to failure and type of failure, so that components can be repaired or replaced ahead of time. ​
  9. Our model to predict lithium deposits. We’ve been working on a fascinating and important project – Satellites for Batteries – for the UK Space Agency, led by the Satellite Applications Catapult. We’ve developed the machine learning core that takes available data and predicts where lithium could be found.
  10. CIAO​ is a powerful meta-AI: it arbitrates the recommendations of lower-level AIs to provide the overall best decision. We’ve developed under Dstl’s Intelligent Ship programme, where it is can resolve conflict between the different AI-supported functions. But it could be applied to just about any situation where different AIs focus on particular tasks but the system needs to make an overall decision.
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Decision Lab
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