<?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/09397936-A86C-424C-B7F2-172CEF87F7DF" ns1:id="09397936-A86C-424C-B7F2-172CEF87F7DF"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/934FC161-DB1F-43EA-B5DE-C49C6504B342" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/F2CF3BAF-8CC9-45FA-8502-F635C5CB1DB8" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/F2CF3BAF-8CC9-45FA-8502-F635C5CB1DB8" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2018-09-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/DCA12ECA-B981-4C56-AF56-9BE53D88746D" ns1:rel="FUND" ns1:start="2018-01-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">133178</ns2:identifier></ns2:identifiers><ns2:title>AI-driven data cleansing and enrichment agent</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Rais Opportunities Ltd (rais.io) helps SME eCommerce businesses manage, make sense of and act on their customer data, to improve customer retention and acquisition. In this feasibility study, Rais will explore the possibility of developing state-of-the-art machine learning algorithms that automatically cleanse (auto-management of outliers) and enrich (fill in the blanks and generate new data) customer data. Improved data inputs will dramatically enhance the value of insights and actions which are automatically generated by other machine learning algorithms that Rais is developing, as part of its Virtual Personal Data Analyst software eco-system. Rais intends that these powerful software processes will use a unique combination of bespoke machine learning and computational intelligence techniques to help businesses establish a better data foundation that can enable meaningful insights to be generated. This aims to provide a vital enabling input into an automated machine learning workflow; from data collection through to the prescription of actions to take. This means that non-technical SMEs will be able to spend more resources on acting to build stronger customer relationships and less time on managing and making sense of all their data.</ns2:abstractText></ns2:project>