<?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="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/B5BA59FA-AA3D-49A2-A75B-A29EF27D819A" ns1:id="B5BA59FA-AA3D-49A2-A75B-A29EF27D819A"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/A70E116A-C0FD-49DF-9B20-450BAF597D77" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/89399FD6-07AD-4B8E-BD25-8F99258C153C" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/189F1BDE-BC7C-437B-AC3C-AA4AC0B677F0" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/89399FD6-07AD-4B8E-BD25-8F99258C153C" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-05-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/9C29262E-DC63-4B8D-86A8-EB95C24C6973" ns1:rel="FUND" ns1:start="2021-05-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10004727</ns2:identifier></ns2:identifiers><ns2:title>AISmartCorps: AI based smart assistance for enterprise workforces</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Financial service companies acquire huge volumes of data which require checking for, and resolving, errors. This is a time consuming and often overly manual set of tasks that put staff under significant pressures which can lead to resourcing challenges and increased business risks. In addition, as data volumes increase, companies are finding it harder and harder to effectively check every line of data and have to choose where to focus their efforts to minimise risks.

We aim to develop and deploy state-of-the-art AI algorithms for automating error detection and recommendations for appropriate resolutions, thus reducing this significant burden on staff and allowing them to focus on more valuable and skillful tasks for the company. We will develop algorithms for error detection, resolution recommendation as well as 'smart' task allocation based on staff skills, knowledge, preferences, availability and wellbeing indicators.

Not only will this increase staff satisfaction by better managing workloads whilst providing more stimulating and satisfying work, it will also increase company efficiency and reduce the propagation of errors that can lead to increased business risks.

Whilst financial services is our starting point, the algorithms, techniques and platform we will develop are expected to be generally applicable across most if not all data intensive industries where anomaly detection and triage is important.</ns2:abstractText></ns2:project>