Incident modelling, at its core, is about deconstructing uncertainty. 

Whether it’s forecasting the spread of an oil spill, or predicting the impacts of CBRNe release in an urban environment, the aim is to understand the uncertainties, risks, and impacts. 

In most scenarios, this means considering hundreds of variables. And behind each of those variables are more uncertainties and probabilities. 

What was on the surface a single question, becomes a multi-dimensional query. “How many people might be impacted by an industrial leak”, becomes “how will the material spread”, which spirals into, “what are wind conditions, and how does the material behave, and how many people are nearby, and what exposure levels are dangerous, and how do all these answers affect one another” and on and on. 

Suddenly, decision-makers can no longer see the wood for the trees. The original, mission-critical, question becomes shrouded in confusion. And with many solutions, even if you get results, the actionable intelligence is buried amongst a sea of statistics and probabilities and likelihoods.

We use incident modelling to unearth clarity in uncertainty, with simplicity

Our job, our aim, as incident modelling and simulation experts is to bridge the gap between software and science, and between science and application.

We model the uncertainty, and simplify it, to create science- and technology-backed applications that provide improved situational awareness and decision support.

This involves 4 core stages;

1. Cutting through the complexity to understand the foundational challenge;
2. Building the modelling solution that can analyse the challenge variables to infer possible outcomes;
3. Translating the data-based outputs into meaningful explorations of the original problem;
4. Visualising the output in an intuitive manner as part of a decision support dashboard.

Incident modelling experts grounded in science

We achieve this not primarily by being experts in security, CBRNe, marine pollution, or the other domains in which we operate. While we have specialist team members, with robust domain knowledge, we also have much more.

We achieve this because we are experts in providing solutions to solve challenges in these environments.

What we provide is the deep-seeded technical knowledge of the complexity surrounding modelling challenges, and the unique ability to translate them into clear outputs. This way, we provide strategic decision support and allow our users to focus on the operational mitigation and response.

With decades of experience, and a suite of technical skills in our team, including software development, AI, physics, maths, engineering, statistics, data science and analytics, we know how to design, combine and develop systems that get to the root of your problem.

Our team – backed by their duly earned PHDs and concrete scientific acumen – builds the foundational technology to produce situational awareness (in context), which unveils actionable intelligence for any incident.

For decades, backed by this expertise in science and software, we have excelled at delivering situational awareness in the Environmental, CBRN, Cyber, and Space domains.

The agility of truly clarified scientific proficiency

Our roots in science mean we can see the wood for the trees.

We understand that sometimes the simplest model can be the most suitable choice.

Rather than getting distracted by the environmental variables, we use them to our advantage. We strip overarching challenges back until we uncover the core, technical issues. This then gives us a clear foundation where we can use our cross-sectional scientific knowledge to answer tough questions, through modelling.

This technical expertise equally gives us the ability to be agile in the way others can’t. So, we can build solutions for a wide range of worldly challenges – including security, defence, environment, digital and more.

Our solutions are all founded on this expertise, and they are equally built on the same underlying architecture, intelligently designed to be agile, flexible, and actionable for a huge range of situations.

Each model relies on our core understanding of the science behind uncertainty, change, and possibility. We fully comprehend how to employ accuracy levels and probabilistic algorithms, to leverage situational analysis and visual analytics, to apply physics and statistics, to determine which models suit which environment, and so on.

This allows us to adapt our modelling and simulation algorithms, models, and capabilities, to align to the challenge at hand. From here, we have the tools to build completely automated and integrated solutions for almost any domain.

We further understand the overall need. That users don’t need reams of statistics, or a maze of data points. They need strategic decision support tailored to their question and their end application.

This is why we build in capabilities so analysis can be performed automatically. So that the outputs are displayed in human-first visual formats. So that in-field agents can access rapid insights. So, the user is delivered situational awareness with the least friction possible, allowing the fewest steps between receipt and action.

A cross-sector innovation approach

As a company, we are always looking for new applications of our software. Our innovation hub actively seeks avenues where we can use science to clarify different problems, while our consultancy works allows us to fluidly explore new domains.

Our most recent solution, SpaceAware, was created in this way. As the Earth’s orbit becomes increasingly saturated by satellites, space debris, and other objects, the risks posed to earth if satellites are disrupted are growing. Yet this is relatively unchartered territory for analysis. We saw a need in the Space market for actionable intelligence to validate these uncertain environments.

Taking the foundation of our already validated models, we were able to turn complex 3rd order risk modelling into straightforward insights about the impacts for users of satellite applications on earth.

These models originated as vulnerability assessment algorithms within the CyberAware platform, which would model weakest attack paths and exploitable entry points in an organisation’s digital infrastructure.

Ultimately, the visual analytics and core framework of both Cyber- and Space-Aware are the same – but the picture they’re looking at is entirely different.

Similarly, our application of wearable devices demonstrates the diversity of our work. Starting with Zoazi, a running app that involved monitoring performance, this technology developed into military wearables to monitor soldiers’ physiological status on a mission.

This is a great example of how our cross-skilled team, and capabilities, are incredibly suited to easily move between sectors, with far few barriers than some alternatives.

Trusted with the most complex and sensitive challenges

Our agility, our deeply grounded knowledge, and our vast range of expertise has been the driving force behind many long-lasting partnerships.

We have been involved in projects with government agencies, military and defence organisations, critical national infrastructure (CNI), and more, for decades. Our team is trusted to make cutting-edge innovations possible and applicable, by building a foundation of complexity with an exterior of clarity – putting the power of maths, physics, programming, AI, ML, and more, into the hands of every user.

This unwavering ability to deliver has built our reputation of consistency, stability and loyalty with every one of these partners.