The frequency and scale of both natural and man-made disasters are increasing globally, impacting millions and causing billions in economic losses each year. According to the United Nations, natural disasters have quadrupled over the past 40 years. Current crisis preparedness training still relies on outdated methods, like pen-and-paper exercises or high-cost field exercises that can only reach a limited number of responders. At INNOVATION LABS we believe that efficient preparedness training can save lives. This is why we developed the Scenario Builder, an intuitive tool that enables agencies to create dynamic and realistic disaster scenarios for preparedness training. Supported by AI, integrating real-world data from multiple sources and visualizing critical elements like equipment, vehicles and roles on a dynamic map, trainees’ situational awareness and decision-making is tested, honing their skills to create actionable intelligence. Trainers can modify the scenario based on real-time decisions, ensuring that the training stays relevant and challenging. The Scenario Builder has evolved through rigorous end-user testing and feedback within several EU-funded projects, to ensure that it meets the real-world needs of emergency responders. AI-assisted insights from scenario evaluations provide continuous feedback to improve collaborative preparedness and response strategies. In the long term, we aim to revolutionize how global disaster response is prepared, by equipping agencies with actionable intelligence that leads to faster, more efficient responses, ultimately saving lives and enhancing resilience against future crises.
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The ambition of Scenario Builder is to transform crisis preparedness from static planning exercises into a data-driven, collaborative training environment that produces actionable intelligence for emergency management. The tool aims to enable trainers and crisis managers to design, execute and analyse complex scenarios that realistically represent the cascading and multi-agency nature of modern crises. Our primary objective is to provide a digital platform for creating structured dynamic scenarios composed of incidents, events, resources, organisations and operational actions. Trainers can build detailed timelines of evolving situations and dynamically modify scenarios during execution, introducing new events or alternative developments. AI technologies assist in generating scenario elements and supporting dynamic scenario evolution, enabling trainers to rapidly construct realistic exercises that reflect operational uncertainty and support decision-making across operational, tactical and strategic command levels. A second objective is to aggregate and visualise multi-source information in a single operational environment. Scenario elements such as resources, organisations, incidents and situational data are displayed through interactive visualisations and maps, allowing participants to interpret information quickly and coordinate responses. By structuring and contextualising this information within evolving scenarios, the tool supports the generation of actionable intelligence that guides decisions during crisis response. Scenario Builder aspires to enhance systematic evaluation and continuous learning. AI-assisted analysis generates recommendations to improve training efficiency and scenario design, allowing lessons learned to inform future exercises and strengthening preparedness and inter-agency cooperation. We believe that Scenario Builder transforms emergency preparedness training, enabling more effective responses that can help save lives.
The Scenario Builder introduces a novel, digital approach to crisis preparedness training by replacing static, script-based exercises with a dynamic and interactive scenario modelling environment. Unlike traditional exercises, scenarios can evolve dynamically during execution, as trainers introduce new elements, inject events or select alternative developments in response to trainees’ decisions. This enables exercises to realistically reproduce the cascading and unpredictable nature of real crises. A key innovation of the platform is its ability to integrate real-world data streams and predictive models within the training environment. Environmental data, situational information and outputs from modelling tools can be incorporated into the evolving scenario, allowing participants to interpret operational data and translate it into coordinated response actions. By structuring and visualising this information through interactive maps and dashboards, the tool converts multiple information sources into actionable intelligence for decision-makers. The Scenario Builder also supports large-scale collaborative exercises through a virtual environment, allowing any number of participants to engage simultaneously across operational, tactical and strategic levels. Artificial Intelligence further enhances the platform by analysing exercise outcomes and generating recommendations for improving training effectiveness and operational coordination. These AI-driven insights help trainers refine scenarios and identify lessons learned, supporting continuous improvement in preparedness.
Emergency preparedness exercises are largely dependent on static, manual tools like paper plans and spreadsheets, which limit the ability to design complex, evolving scenarios and introduce inconsistencies, errors, and delays. These tools also hinder collaborative drafting and provide limited flexibility during execution, reducing their effectiveness in preparing responders for real crises, and do not enable in-depth trainee evaluation. Scenario Builder addresses these issues by offering a digital environment where trainers can rapidly design, modify, and execute structured preparedness scenarios. Components (incidents, assets, roles, organizations, etc.) can be reused or imported, saving preparation time and enhancing consistency. AI-assisted scenario generation helps trainers draft exercises based on organizational plans, risk registries, and procedures. Trainees can utilise the tool remotely from any location, enabling in such way the conduction of virtual Table-Top exercises, enabling cross-border training with reduced logistics costs. Trainees interact with the scenario through maps, assets, communication channels, and situational updates, enabling realistic practice in decision-making and team coordination. The platform integrates with simulation tools and command-and-control systems via message brokers and REST interfaces, acting as a central orchestration layer. This allows simulated data to be delivered through the same interfaces used in real operations, enhancing realism. Finally, Scenario Builder supports structured post-exercise evaluation. Trainers, evaluators, and trainees assess performance against predefined objectives, while AI-assisted analysis aggregates results and offers recommendations to improve future training. By digitalising the full lifecycle of preparedness exercises, it enhances the realism, scalability and efficiency of training while strengthening inter-agency collaboration and operational readiness.
The Scenario Builder was developed by a diverse team of experts, including software architects, data scientists, and machine learning engineers, who implemented its core functionalities. Domain experts from emergency response, law enforcement, and crisis management co-designed the tools functionalities, ensuring that it meets real-world operational needs.
The Scenario Builder was developed by a diverse team of experts, including software architects, data scientists, and machine learning engineers, who implemented its core functionalities. Domain experts from emergency response, law enforcement, and crisis management co-designed the tools functionalities, ensuring that it meets real-world operational needs.