<?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="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/202BEB1C-0F61-4F96-A601-662771BF7FC0" ns1:id="202BEB1C-0F61-4F96-A601-662771BF7FC0"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/B9774CFC-FBC9-47DF-A42F-1F677E447091" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/451EEFAB-C2E1-444C-A3B1-CBFC243E8190" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/451EEFAB-C2E1-444C-A3B1-CBFC243E8190" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/EAF5A676-B2D2-4042-9558-0906A07AEE3A" ns1:rel="FUND" ns1:start="2023-05-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10074639</ns2:identifier></ns2:identifiers><ns2:title>Developing a filter layer to sit between users and LLMs called the AI Firewall</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Grant for R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Our project is focused on conducting a feasibility study to develop a layer that sits between a language model (LLM) and individual users to act as a filter between the user input and the model itself. This layer will be designed to check for dangerous prompts, confidential information, and other potentially problematic content that may be inadvertently processed by the model.

What makes our project innovative is that it addresses a critical issue in the deployment of AI language models, namely the potential for harmful or unethical outcomes when models are trained on data that may contain sensitive or dangerous content. By implementing this filter, we can help to ensure that language models are used responsibly and ethically, without compromising their overall effectiveness and utility.

Our filter will be designed to be highly flexible and adaptable, allowing it to be easily integrated with a wide range of different language models and applications. This flexibility will be key to ensuring that our solution can be widely adopted across different industries and use cases, from healthcare to finance to education and beyond.

Another key innovation of our project is that it will be designed with end-users in mind, making it easy and intuitive for individuals to understand and use effectively. This user-friendly approach is critical to ensuring that our solution is widely adopted and integrated into a range of different applications and systems.

Overall, our project represents an important step forward in the development of responsible and ethical AI language models. By implementing a layer that acts as a filter between users and models, we can help to prevent harmful outcomes and ensure that language models are used in a responsible and ethical manner. With its flexible design, user-friendly interface, and potential for wide adoption, we believe that our project has the potential to transform the way that language models are used and deployed across a range of different industries and applications.</ns2:abstractText></ns2:project>