Entopy and Essex researchers to advance AI integration in supply chain

A new partnership between University of Essex researchers and data analytics specialist Entopy, will use artificial intelligence (AI) to help deliver operational and predictive intelligence across complex, real-world environments.

Entopy's micromodels technology is designed to address key challenges associated with implementing AI in real-world operational environments. Having seen success in the supply chain and logistics sector, this new Knowledge Transfer Partnership (KTP) will develop aspects to enable the technology to serve other use cases and market verticals.

The Innovate UK funded KTP will help push the boundaries of AI innovation through a 30-month collaboration worth over £260,000.

The project is set to use new AI models and advanced techniques to enhance the capabilities of Entopy’s proprietary software platform.

Toby Mills, CEO of Entopy said: “We are excited to formalise our partnership with the University of Essex. From day one, it was clear that this relationship would flourish, with alignment of research focus and a healthy dynamic between the teams.”

The KTP will build on developments enabled by funds recently awarded to Entopy through the prestigious Freight Innovation Fund Accelerator (FIF). This programme, funded by the Department for Transport and delivered by Connected Places Catapult, is designed to support and finance innovators to trial their solutions within real-world environments and prepare their businesses to go to market. FIF identified a major challenge in delivering predictive insights to the sector.

The FIF funding has enabled Entopy to demonstrate their software capabilities to supply chain and other markets and extend the use of their platform to help address the issues caused by lack of large-scale cross industry data collection and sharing.

Part of the solution, and central to the KTP, is the development of multiple independent predictive models, which use specific data sets and machine learning techniques, to build accurate models and deliver predictive outputs for larger problems.

These can then be orchestrated to deliver holistic and dynamic predictive capabilities to more complex problems and evolve as new data and learnings are unearthed.

Advanced approaches being integrated will include novel federated learning, which is a new standard for training AI models from multiple sources while meeting the latest regulations for handling and storing private data. Meanwhile micromodels are designed to address specific challenges or provide targeted solutions within a larger framework.

Toby continues: “The next milestones for our micromodel’s technology focus on broadening use case applicability, building a library of generalised models and developing novel federation techniques. This is incredibly exciting, extending our technology capability to support the delivery of highly effective operational intelligence across multiple sectors.”

Professor Haris Mouratidis and Dr Mays Al-Naday from Essex’s School of Computer Science and Electronic Engineering and the Institute for Analytics and Data Science will be working on the KTP with a research associate based in the company.

Professor Haris Mouratidis, Director of the Institute for Analytics and Data Science said: “We are very excited to work with Entopy on this Knowledge Transfer Partnership. The project will enable us to combine our world leading research on micromodel technology and federated learning with Entopy’s leading intelligence platform to provide innovative solutions to a fast developing, but also highly complex, sector that Entopy is operating.

“The project is part of a larger scale collaboration with Entopy around data science, artificial intelligence and cybersecurity aiming to revolutionise predictive intelligence in complex operational environments.”

KTPs offer a unique opportunity for businesses and organisation to access funding for innovation and growth, through collaboration with Essex. Discover more about working with world-leading academics from the University of Essex by visiting: www.essex.ac.uk/business or emailing innovation@essex.ac.uk.