To apply Machine Learning techniques to develop scale adoption of a novel eProcurement Analytics Service.

To apply Machine Learning techniques to develop scale adoption of a novel eProcurement Analytics Service.

A project to establish a regional supply hub, using Artificial Intelligence to match suppliers to requests and enabling councils, charities and businesses to buy local. This will develop innovative applications of AI, teaching the machine to avoid learning inappropriate discrimination from humans (so making the platform suitable for public procurement) and combining geographic proximity with other factors to determine which suppliers best meet the buyer's needs. The project builds extensively on prior development of AI systems and uses existing collaborations, so reducing the project risk and increasing the probability of successful implementation and exploitation. It is led by Applegate Marketplace Ltd, partnering with Ghyston Ltd and the University of Exeter Institute of Data Science and Artificial Intelligence.

Petroc's Techknowledgey Transfer project will test the concept of providing support to SMEs through student projects. Young people on a range of Level 2 and 3 business, administration, enterprise and accountancy courses will work within SMEs, to combine each young person's digital confidence and knowledge and understanding of the latest technologies with the SMEs experience and expertise within their field of business to create and embed models of business and administration technology usage, tailored to each individual business, which are user-friendly and sustainable and which lead to genuine business efficiencies, freeing up business owners and managers to increase productivity and profitability, as well as benefiting from an improved work-life balance. Participating businesses will initially benefit from a 1:1 diagnostic session to identify areas where technology adoption could improve the efficiency and effectiveness of their business and administration processes, followed by up to two masterclasses to learn about relevant technology options and network with peers in similar circumstances. As this is a research trial, approximately half of all participating businesses will then be randomly selected to work with a student, who will embed the use of one or more identified technologies within their business and administration processes. Students will be selected on a competitive basis for each participating SME to ensure a good match between student and business, and both the student and business will be support by expert tutors and/or business mentors. We will undertake a robust evaluation of the impact, comparing and contrasting the short, medium and long-term effects on those businesses that are selected to engage with a student, and those that are not, primarily assessing the extent to which each option results in businesses adopting the use of business and administration technologies on a long-term and effective basis.

Supply chains have been disrupted by the outbreak of COVID-19, causing difficulties in getting vital equipment - face masks, visors, respirators, spare parts for medical devices and food production facilities - to where they're needed. This project uses Artificial Intelligence (AI) to match up those able to supply these items with the demand. It builds extensively on previous investment which created an online supply portal and an AI matching engine (identifying which suppliers are likely to be able to fulfil a request for goods or services and allocating them to it). By creating a next-generation matching engine the project increases the volume of enquiries the portal can handle and the speed at which they can be processed through the automation of remaining human interventions, and also makes the portal easier to use for non-specialist staff. The project will: - increase the volume of vital equipment reaching the front line during the crisis; - establish a capability to respond to disrupted supply chains in future emergencies; - strengthen the potential to displace slow, expensive and outmoded approaches to procurement; - extend an existing academic-commercial partnership, increasing knowledge and understanding of commercialising UK research in AI. The work builds on the existing, strong partnership between Applegate Marketplace Ltd and the University of Exeter Institute for Data Science and Artificial Intelligence. The extension to the project will enable the commercialisation of the work, bringing the benefits of the technology to a wider community.

A project to evaluate the use of Machine Learning to extend eProcurement in the management of tail end spend. Applegate operates a software-as-a-service eProcurement service called “Applegate PRO”. This allows buyers to submit quote requests for any b2b product or service. This project will investigate the applicability of Machine Learning to identify the most relevant suppliers to match against each quote request.