<?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/08B6CCF7-23EE-4EC9-BC8D-3342CFCD6F89" ns1:id="08B6CCF7-23EE-4EC9-BC8D-3342CFCD6F89"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B9292233-A913-4939-A02F-340265C5BC7F" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B9292233-A913-4939-A02F-340265C5BC7F" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2019-12-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/20097EC6-8A31-4DC3-868A-49F0FD0DF508" ns1:rel="FUND" ns1:start="2019-06-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">133846</ns2:identifier></ns2:identifiers><ns2:title>MesslyFLOW - AI and machine learning powered clinical and non-clinical decision support tool for doctors</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>ISCF</ns2:leadFunder><ns2:abstractText>&amp;quot;MesslyFLOW is an AI and machine learning powered clinical and non-clinical decision support tool for doctors. This will provide doctors with rapid and reliable access to critical information, both clinical (national and hospital clinical and antibiotic guidelines, treatment policies) and non-clinical (making referrals, booking scans).

Currently, doctors struggle to access information critical to their jobs. This information is spread across disparate locations such as hospital intranet, paper resources, online resources (such as NICE and BNF) and numerous doctor-apps such as Induction and is not easily accessible by doctors on the move.

MesslyFLOW will aggregate, ingest and sort information from multiple sources and apply an intelligent layer to assess what information or action is needed. Information is passed to the doctor and, where appropriate, the action (such as completing a form) will be initiated. Doctors will make queries through a voice and text interface on mobile devices.

This will integrate with resource databases via APIs to ensure data is up to date, and interface with and hospital processes. Future development will integrate into hospital EHR systems to integrate patient information.

This enables faster, more reliable access to the information needed to best treat patients and efficiently operate within the hospital. Making doctors more efficient and effective will reduce workforce demands to save money and, most importantly, enable better care for patients.

The aim of the Feasibility Study is to assess the commercial and technical viability of this approach, including defining the technical roadmap and architecture, go-to-market plan and pricing, as well as defining the business plan and steps to commercialisation.

This is innovative because no AI-powered clinical decision support tool is currently in use within the UK, although this technology is being used in patient-facing solutions.

This will subsequently be expanded to other healthcare workers and potentially other industries outside healthcare, and internationally.

Messly operates the largest and most active medical professional network in the UK, with over 15,000 registered doctors. Doctors use Messly to connect, share information and stay up-to-date, including access to certain clinical and non-clinical resources and information. Messly has high credibility and brand reputation amongst doctors. We also operate Messly Locum (ML), a technology that helps NHS Trusts find and connect with doctors to fill temporary shifts in their hospitals. This launched in late 2016, and is now live in 7 NHS trusts.&amp;quot;</ns2:abstractText></ns2:project>