<?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/069B03B0-CC74-47CC-9AD1-AB6E2A3E40F0" ns1:id="069B03B0-CC74-47CC-9AD1-AB6E2A3E40F0"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/CF664F88-D8C3-4AA2-8469-620D2A0C1AD3" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/250DE6B2-2E15-4D8C-88BF-856086C07382" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/250DE6B2-2E15-4D8C-88BF-856086C07382" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-09-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/FE938D1D-D253-4DC7-8E52-4C0F46AEEAC2" ns1:rel="FUND" ns1:start="2024-03-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10114149</ns2:identifier></ns2:identifiers><ns2:title>EcoTraceAI: A Novel AI-based Platform for data collection and validation for measuring the environmental impacts of the supply chain in the fashion industry.</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>SME Support</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>EcoTraceAI is an AI-powered conversational agent for collecting data across supply chains and using this to calculate accurate and reliable environmental metrics.

Data gathering is achieved using an AI-powered chatbot which automates and simplifies the process. The chatbot uses conversational scripts to interrogate suppliers and extract the data required. The conversation adjusts dynamically according to the user input and data validation. For example, it might ask the user for further information if the data input is flagged as incomplete or outside of expected values.

Supply chain data is combined with other data sources to calculate environmental impact metrics in granular detail. This will allow brands to understand and report on the environmental impacts associated with each individual product. They will be able to improve their environmental performance by identifying and addressing weaknesses in their supply chain. For example, they will be able to identify major sources of negative impacts and address these through changes to their designs, material use, operational procedures and/or supplier choice.

Ultimately, we aim to create a more sustainable and equitable world through data-driven decision-making. Our ambition is to provide fashion brands with the tools and insights they need to measure and understand the environmental impact of their actions and ultimately to drive positive change.

EcoTraceAI will make it the norm for consumers to be able to clearly see, understand and compare the real environmental and social impacts of any fashion purchase. Eventually, we aim to extend this technology to deliver the same benefits across other products and services in any industry.</ns2:abstractText></ns2:project>