<?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="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/C5A2D485-1B79-4FF4-9F6E-36A6B7E6D31F" ns1:id="C5A2D485-1B79-4FF4-9F6E-36A6B7E6D31F"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/22129D50-2BB5-4336-86AD-CC0051C134BC" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/88CFC1A3-CB71-46B1-A9B9-DA793E720584" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/88CFC1A3-CB71-46B1-A9B9-DA793E720584" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2026-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/CD8D8E67-569A-43E2-9AB9-D6DE6BD0B429" ns1:rel="FUND" ns1:start="2025-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10173412</ns2:identifier></ns2:identifiers><ns2:title>Preventive Behavioral Intelligence Platform for Cross-Sector Safety</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Fast Start Response</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>GangoAI is developing the UK's first preventive behavioral intelligence platform to revolutionize workplace safety across multiple sectors. Current safety measures are fundamentally reactive, responding after incidents occur rather than preventing them. This project will develop breakthrough AI technology to predict and prevent workplace accidents by monitoring human behavioural patterns in real-time.

Workplace accidents cost the global economy over $3 trillion annually, with 13% directly attributed to human factors like fatigue and distraction. Traditional safety systems rely on environmental monitoring or post-incident analysis, missing the critical window when behavioural deterioration begins but before visible risk appears. Our early pilot validation reveals 60% of workplace breaks fail to restore worker performance to baseline levels, indicating massive unaddressed inefficiencies.

GangoAI will create a dual-engine AI platform combining computer vision with advanced machine learning to detect subtle changes in human behaviour that precede safety incidents. The system uses privacy-preserving edge computing to analyse movement patterns, posture changes, and attention indicators without storing personal imagery. Our breakthrough approach will establish individual behavioural baselines and population-wide intelligence to identify when someone transitions from safe to at-risk states.

Initial pilot testing has collected 2.06M+ behavioural data points across hospitality and manufacturing environments, with preliminary analysis indicating 75% of monitored individuals show detectable deterioration patterns. We have tracked hundreds of individuals in hospitality settings and captured 62,491 movement frames from manufacturing workers, suggesting our core algorithms could adapt across multiple sectors.

While our pilots show promising behavioural pattern recognition, we lack the scalable platform technology needed for commercial deployment. Current implementations require manual configuration and cannot share individual baselines across multiple locations---essential for real-world applications where workers move between sites.

This New Innovators funding will enable us to develop the missing commercial platform infrastructure: automated deployment systems, enterprise integration APIs, and secure cross-location baseline sharing. We will transform promising pilot results into scalable technology that can validate commercial viability across sectors.

The project will deliver a commercially-testable AI platform ready for enterprise pilot validation across diverse workplace environments. This represents a fundamental shift from reactive to preventive safety management, with potential commercial applications including transport drivers (&amp;pound;30/month), manufacturing workstations (&amp;pound;300/month), and hospitality venues.

By developing the first truly preventive human-behaviour monitoring system, this project will position the UK as a global leader in AI-powered workplace safety innovation, targeting the &amp;pound;265M UK addressable market where traditional reactive solutions consistently fail to prevent accidents.</ns2:abstractText></ns2:project>