<?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/C9C7F7B0-5FDB-446F-BF0B-ED265F5519A0" ns1:id="C9C7F7B0-5FDB-446F-BF0B-ED265F5519A0"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/61411A6E-8BEC-4335-8382-62B6FF87232E" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/C0A48433-49BC-4986-BF66-ABEEED9A6F57" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/75213F12-1D97-4468-8983-3882B1BF54DC" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/C0A48433-49BC-4986-BF66-ABEEED9A6F57" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/480A2B33-73DE-4533-87AD-E05BCD14261E" ns1:rel="FUND" ns1:start="2023-07-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10078199</ns2:identifier></ns2:identifiers><ns2:title>LogiAI: Enhancing supply chain management with AI-powered demand forecasting and inventory optimisation for logistics</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>LogiAI, a progressive inventory management and demand forecasting system, harnesses the power of AI to revolutionise the ecommerce landscape. Developed collaboratively by Pogo Digital Ltd and Digi4u Ltd, LogiAI stands as a trailblazer in predictive analytics, ensuring businesses of all sizes can streamline their operations, minimise waste and maximise profitability.

At its core, LogiAI employs a four-step approach. Initially, it collects and pre-processes ecommerce customer and sales data, setting a solid foundation for its analytical operations. Next, LogiAI creates specific features to be used in the training of its AI model, employing advanced machine learning algorithms to ensure sophisticated and accurate prediction capabilities. Finally, committed to a path of relentless improvement, LogiAI learns from its own predictions, adjusting its models and strategies based on feedback and actual outcomes.

LogiAI's dynamic AI model has the capability to anticipate future demand and accordingly adjust inventory levels, or trigger alerts when inventory falls below a predetermined level. This feature not only bolsters operational efficiency but also aids in waste reduction, driving enhanced profitability for businesses.

A defining aspect of LogiAI is its cost-effectiveness and scalability. Powered by open-source software and existing data sources, LogiAI offers a viable solution for businesses of all sizes, making advanced AI capabilities accessible without a hefty price tag. Its adaptability extends to customisation, catering to the unique requirements of individual ecommerce entities, and continuing to evolve as fresh data emerges.

Data quality remains a key focus for LogiAI. Through stringent data cleaning, validation, and profiling processes, it ensures the data informing its AI model is accurate, reliable, and primed for successful outcomes.

In essence, LogiAI embodies an innovative, reliable, and economically viable solution for ecommerce businesses seeking to bolster their efficiency and profitability. By offering an AI-driven approach to inventory management and demand forecasting, LogiAI supports businesses in maintaining a competitive edge, keeping them ahead of the curve in an increasingly digital and dynamic commercial environment.</ns2:abstractText></ns2:project>