<?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/900D2838-B5AC-4A1C-B003-396DCE7D2EC4" ns1:id="900D2838-B5AC-4A1C-B003-396DCE7D2EC4"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/10BCC3AF-B193-4C4C-8CD3-0C8318661CFB" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6F0A0357-9415-4A94-AB4E-1D4BA5F02832" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6F0A0357-9415-4A94-AB4E-1D4BA5F02832" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2016-08-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/3FA1E109-B2F7-4BEE-A850-4DB12A3CDFE3" ns1:rel="FUND" ns1:start="2015-12-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">710777</ns2:identifier></ns2:identifiers><ns2:title>Artificial Intelligence for Email Security</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>GRD Proof of Concept</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>For most organisations email is the main artery of communication and a channel across which
highly sensitive information is communicated and shared. Email is a highly vulnerable facet
of an enterprise’s overall information infrastructure given the frequency and ease by which
workers send emails every day and entire cyber security initiatives can be rendered redundant
by a simple misaddressing error.
Founded by a team of Imperial College trained engineers, ex-Investment Bankers and current
finalists of the 3D Fintech Challenge 2015, CheckRecipient is an email security platform used
by world-leading organisations to prevent confidential information being sent to the wrong
person. Currently, there are two modules, CheckRecipient RuleBuilder, which allows
organisations to design and implement customised, rule-based email communication policies
and CheckRecipient AI, which performs a historical analysis of a sender’s email account to
learn sending patterns and predict when an incorrect recipient may have been copied in on an
email by mistake.
Having developed and sold both of these products to a set of early customers, we are now
looking to substantially transform CheckRecipient AI by incorporating natural language
processing and machine learning technologies applied to the textual content present in email
data to improve both the accuracy of predicting misaddressing errors and also develop the
functionality of the product to protect against other email security risks.
There is a strong market demand for an email security platform that is both able to work
autonomously and with minimal disruption to the end user. Currently there exist a number of
platforms on the market that look for predefined, specific text patterns (such as presence of
social security numbers), but there are no products currently available that are analysing
complex and unstructured textual content in emails to infer meaning and determine sensitivity
and appropriateness for a set of recipients.</ns2:abstractText></ns2:project>