<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/21F186EE-BBE7-4F91-9440-F2825E2E9894" ns1:id="21F186EE-BBE7-4F91-9440-F2825E2E9894"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/62633C98-9179-476E-AC70-ED41AB933BF0" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D003E323-702D-4D01-B260-209F7DA9929E" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D003E323-702D-4D01-B260-209F7DA9929E" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/851482B4-A4DD-482C-803E-4B084B90BADF" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-03-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/AD81869B-692B-4B61-B65F-04388915C6A9" ns1:rel="FUND" ns1:start="2023-09-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10077383</ns2:identifier></ns2:identifiers><ns2:title>“ChainAI: AI-Enabled Customised Workflows for Smarter Supply Chain Management”</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The project will leverage the use of Data Performance Consultancy's new data platform Buttress, which is a digital twin framework and which has received funding previously from Innovate UK and we will look at how Artificial Intelligence (AI) and Machine Learning (ML) techniques can enhance the offer of Buttress specifically in a number of verticals but for the purposes of this application we will be looking at Transport and specifically Supply Chain Management (SCM) in the Logistics space

The proposed ChainAI project aims to explore the feasibility of leveraging AI solutions to create custom workflows for SCM that optimise each stage of the process, improving efficiency, effectiveness, and performance in SCM and ultimately enhancing supply chain operations and outcomes. The project will require a deeper insight into supply chain data to identify key patterns, trends, and opportunities for improvement. By gaining a thorough understanding of the supply chain process at a granular level, the project will pave the way towards producing AI-generated workflows that are tailored to the specific needs at each stage of the process, from planning and sourcing to production.

We will look to include various data sources based on legacy systems, new applications and hardware such as secure Industrial Internet of Things devices based on a new ISO Standard the Open Connectivity Foundation.</ns2:abstractText></ns2:project>