<?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/2C8407BC-76CC-4D2B-B5E4-AAE86980FE0B" ns1:id="2C8407BC-76CC-4D2B-B5E4-AAE86980FE0B"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/48DA77F5-50B1-45FC-BACE-51E5CB75019D" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/762486C6-97F4-4EC6-896B-BB5B36467F27" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/762486C6-97F4-4EC6-896B-BB5B36467F27" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2021-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/B6982079-D961-4E48-89B6-E7F26953A347" ns1:rel="FUND" ns1:start="2020-05-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">59354</ns2:identifier></ns2:identifiers><ns2:title>Zoggy - A Conversational Chatbot for the Third Sector</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Due to the economic and social impact of Covid-19 pandemic, demand for advisory services from organisations such as Citizens Advice Bureau (CAB) has increased to unprecedented levels. As organisations served predominantly by volunteers, these organisations are understaffed and are unable to meet this demand. This not only impinges on staff fatigue but also results in increased waiting times resulting in inefficiencies. This is representative of many non-profit organisations across the UK and beyond. It is this problem that we wish to solve by using Conversational AI Chatbots.

Large volumes of information which is dynamic in nature due to constant changes in law and guidance, means that standard rule based Chatbots won't be a practical solution. Our Chatbot will use a hybrid approach of configured rules for slot filling, combined with machine learnt stories from content. Our solution will evolve with training and be more effective in answering complex user queries.

&amp;quot;Extension for Impact&amp;quot; - With the help of &amp;quot;Extension for Impact&amp;quot;, we will move the innovation from a demonstrable prototype to a deployable Minimum Viable Product (MVP) that is ready for the market to buy-in and customer deployment.</ns2:abstractText></ns2:project>