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Whitespace has built an established track record in defence and is now expanding its work across policing and the wider emergency services. As organisations explore how AI can support frontline teams, improve decision-making and make better use of operational knowledge, the company believes the starting point should be the problem rather than the technology.
Ahead of The Emergency Tech Show, Whitespace discusses the opportunities for AI, the importance of sovereign technology and what emergency services can learn from defence.
Where do you see the biggest opportunities for AI in emergency services?
There are huge opportunities, but we think the most valuable ones start with real operational problems rather than AI itself.
Emergency services generate enormous amounts of information through incidents, investigations, case files, reviews and day-to-day operations. Yet staff can still spend significant time finding information, applying guidance, checking work and moving between systems.
Our work in policing has already highlighted some of those pressures. In a recent client discovery, for example, officers were working across complex case-file requirements, multiple systems and tight operational deadlines, with many quality problems only being identified later in the process.
AI can help organisations use information more effectively, reduce avoidable rework and support people at the point they need it. The opportunity now is to move from experimenting with AI towards secure, governed capabilities that deliver real operational value.
Why is sovereign AI important for emergency services?
Emergency services handle highly sensitive information, so organisations need confidence in where their data is processed, how AI is deployed and who remains in control.
For us, sovereign AI is about retaining that control. It means being able to deploy AI within appropriate security and governance boundaries rather than relying on technology that requires sensitive operational information to leave those environments.
Collective, our sovereign AI operating system, provides the foundation for developing and deploying governed AI capabilities within those security and operational boundaries.
That is something we have already had to solve in defence. Operational Learning, a capability built on Collective, has been deployed in completely offline, secure environments where security and operational assurance are essential.
The technology still needs to be useful, but for policing and emergency services, trust, security and governance have to be built in from the beginning.
How can AI help emergency services make better use of operational knowledge?
Emergency services are already capturing enormous amounts of learning. The problem is that it can be spread across reports, documents, systems and individual experience, making it difficult to find and reuse later.
AI can help connect that information and make it easier for people to retrieve relevant learning when they need it.
That is the problem our Operational Learning capability, built on Collective, is designed to address. It helps organisations capture, connect and reuse knowledge generated through operational activity, so lessons can become part of organisational capability rather than simply sitting in a document or archive.
The goal isn’t to replace experience or professional judgement. It is to make the organisation’s existing knowledge easier for people to access and apply.
How can AI support faster, more informed decision-making?
AI can help by bringing the right information, guidance and context to people earlier in the process.
Our policing discovery work has shown how easily people can become overloaded by complexity. In one recent engagement, we mapped 61 case-file rules alongside multiple systems, guidance documents and decision points that officers were expected to navigate while managing operational workloads.
One opportunity for AI is to help surface what is relevant, identify missing information or highlight something that needs attention before it creates a problem later.
But the person remains responsible for the decision. We see AI as supporting assured decision-making, helping officers, staff and leaders understand the information available to them more quickly while keeping professional judgement and accountability with the human user.
What can emergency services learn from your work in defence?
One of the biggest lessons is to start with the operational challenge, not the technology. In complex operational environments, you first need to understand how people work, what information they rely on, what the security constraints are and what outcome you are trying to improve.
That is the same approach we are taking into policing through Solutions Engineering. Our work with one policing organisation began by getting underneath the problem before thinking about the technology. We mapped the case-file journey end-to-end, spoke to the people doing the work and pinpointed where quality was breaking down, allowing us to identify where AI could make the biggest practical difference.
Collective then provides the underlying operating system on which governed AI capabilities can be developed and deployed around those operational needs.
The other lesson is that AI has to work within operational reality. Systems may be disconnected, data may be imperfect and human checks may exist for important reasons. Successful AI capability needs to accommodate those conditions rather than assume them away.
What do you hope visitors take away from The Emergency Tech Show?
We want visitors to see what operational AI can look like when it starts with a genuine problem.
We’ll be demonstrating Operational Learning, built on Collective and developed and proven in defence, alongside examples of our policing work that show how we work with organisations through Solutions Engineering to develop bespoke AI capabilities around specific operational challenges.
Together, they show two sides of the same Whitespace approach: proven capabilities that can be applied to policing and the ability to develop new capabilities where organisations have different operational needs, all underpinned by Collective.
But we’re also interested in hearing from visitors. We want to understand where teams are losing time, where information is difficult to use, where knowledge is being lost and where existing processes are creating unnecessary operational pressure. Those conversations are often where the most useful applications of AI begin.
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Meet Whitespace at the Microsoft Partner Pavilion throughout The Emergency Tech Show on 16-17 September at NEC, Birmingham. Register for your free ticket here.
