European defence fund

Structuring and delivering collaborative European defence R&D programmes

The European Defence Fund plays a pivotal role in enabling collaborative R&D programmes that bring together industry, research organisations and defence stakeholders from different Member States. Success in these programmes requires a strong consortium and a compelling concept. But what determines whether these programmes deliver is also how consortia are aligned, how complexity is modelled and how results are turned into deployable capability. Mews Partners works alongside consortia through every phase, from proposal to exploitation, bringing programme management, systems engineering expertise and advanced modelling.

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WHAT WE BRING TO EDF PROGRAMMES

EDF programmes are collaborative by design: multiple partners across multiple Member States, and potentially competing industrial interests. The resources available in EDF are substantial, yet often constrained relative to the scale and ambition of the projects. Three key dimensions underpin Mews Partners’ capabilities and define the value we bring to the consortium.

Aligning your consortium to make decisions that stick

Aligning a consortium is rarely a technical problem. It comes down to getting every partner, industry, research organisations and end-users to converge on shared objectives and making sure those decisions hold once execution starts.

Operational needs elicitation

We structure stakeholders inputs early, using methods such as the Kano Model and value-driven dialogue, so requirements are grounded in real operational use.

Design trade-off management

We apply methodologies such as Set-Based Concurrent Engineering (SBCE) across the system breakdown structure to map trade-offs, define selection criteria, and drive progressive convergence toward well-founded design choices.

Systems engineering structuring

We deploy MBSE-based methodologies to clarify the fragmented defence problem space, from use-case definition through architecture alignment and the establishment of a single source of truth.

De-risking solutions by modelling complexity

Defence R&D tackles problems where off-the-shelf solutions do not exist. De-risking means modelling complexity before committing resources: simulation, data-driven analysis, and optimisation, used together to investigate the solution space and converge on sound technical choices. Mews Labs, our applied science hub, works directly within the programme to build the models and decision-support tools that make this possible.

Hybrid simulation and data-driven analysis

We combine physics-based simulation with statistical learning to analyse complex defence systems and the organisations that build them.

Optimisation under constraints

We model resources, dependencies and scenarios to support informed decision-making across multi-partner programme structures

Functional demonstrators

We build proof-of-concept tools using AI and simulation to validate feasibility, interoperability and user value before full-scale development.

Turning R&D results into implementable roadmaps

EDF programmes are judged on whether research becomes deployable capability. That transition requires structured planning from day one.

R&D-to-industrialisation transition

We plan end-to-end deployment, manage organisational change and support user uptake from concept through to operational adoption.

Dissemination, communication and exploitation

We initiate DCE activities at the proposal stage, building interfaces between knowledge management, key deliverables and overall programme activities. After project start, we structure exploitation activities at both consortium and individual partner level, connecting project results to relevant users, markets and follow-on opportunities.

Powered by Mews Labs

Mews Labs deploys modelling, simulation, and AI capabilities designed for European defence R&D.

Hybrid modelling of large-scale defence systems Physics-based simulation combined with data-driven methods and statistical learning, used to predict system behaviour, support design trade-offs, and de-risk technical choices across multiple subsystems and operational environments.

Multi-factor optimisation Resources, constraints, and scenarios modelled through agent-based models and multi-scale optimisation to support programme planning and investment decisions.

Structural modelling algorithms Developing advanced algorithms for structural analysis, vulnerability assessment, and impact prediction, as deployed on the PRECISE programme.

GenAI demonstrators Proof-of-concept AI companions and decision-support tools, built to validate technical feasibility and user adoption potential before full-scale deployment.

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Selected EDF projects

European Defence Fund 03/09/2026

RESILIENCE-D2025 | EDF, 2025–2028

RESILIENCE-D-2025 aims to advancing two innovative MCMs against radiological and nuclear (RN) threats by addressing the treatment of Acute Radiation Syndromes frequent in RN exposure scenarios and Multi-Organ Failure (MOF), induced by combined injuries. The two disruptive Advanced Therapy Medicinal Products will be developed up to TRL 6. Developing these Medical Counter Measures in a consortium composed of 10 partners representing five nationalities, with strong confidentialities constraints requires a strong Kowledge Management framework.

We define the consortium's Knowledge Management strategy, from the processes for needs gathering to the archiving of information.

European Defence Fund 03/09/2026

PRECISE | EDF2024 work programme, 2025–2029

PRECISE will address the critical need for sophisticated modelling tools to assess the impacts of military actions on civilian infrastructure. PRECISE, a €15M EDF programme led by GMV with 11 partners across 5 nationalities, will deliver the following capabilities: multi-source data collection and annotation of high-resolution imagery from satellites and sensors, tailored structural knowledge based on AI-driven algorithms to extract detailed information about structures, identifying vulnerabilities and patterns, and simulation of effect prediction models by simulating various scenarios, including the impact of munitions on structures.

We develop the structural modelling algorithms, lead dissemination & exploitation activities, support project coordination cross-WP activities as well as requirement analysis and system design.