<?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/D9E80CA6-BBA0-49E2-95BD-F02AF7A0B314" ns1:id="D9E80CA6-BBA0-49E2-95BD-F02AF7A0B314"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/ADFED439-C742-47AE-BF84-E052AB330560" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D4CD786F-E65A-40B4-9E3C-4E6E05E9480C" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D4CD786F-E65A-40B4-9E3C-4E6E05E9480C" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2018-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/EE276BC5-CABE-4573-91A3-29B2A0A35282" ns1:rel="FUND" ns1:start="2017-12-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">971578</ns2:identifier></ns2:identifiers><ns2:title>Volition - a machine learning decision support platform for Innovate UK</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Small Business Research Initiative</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The Volition platform is a secure cloud based web application designed to help Innovate UK make better use of its existing operational data using machine learning (ML). It will be driven by a blend of ML capabilities, natural language processing (NLP), advanced information retrieval techniques and data visualisation. The Synoptica approach is unique in that we automatically find and extract additional data from the web from a variety of structured and unstructured sources and use this to enhance the ML analysis of Innovate UK’s existing data. This platform will use ML to automatically: 1) Provide ‘smart’ assistance with assessor allocation for submissions using state of the art ML/NLP profiling and keyword extraction. 2) Automatically detect and highlight re-submissions, duplicate and reassessed applications 3) Scan the web continuously finding evidence that indicates a company's (and / or consortium’s) ability to successfully deliver the project described in the submission. 4) Allow Innovate UK to make the best use of its existing data by extracting data ‘signals’ - and connections between these signals - presented in an easy to understand graphical interface. This approach will surface insights and latent connections to help Innovate UK better understand their own data.</ns2:abstractText></ns2:project>