Results

- Unified operational view across multiple intelligence sources

- Enhanced cross-border and cross-sector collaboration

- Reduced investigation time through AI-assisted workflows

- Secure, compliant, and interoperable deployment in public-sector environments

The platform represents a strategic asset for long-term institutional adoption and sustainable public safety innovation.

NET: “At NET, we recognize the AVALANCHE platform as a key technological asset enabling scalable intelligence capabilities for the detection and analysis of disinformation and FIMI. NET has played a central role in architecting and developing the platform’s modular infrastructure and AI-driven analytics, ensuring robustness and performance. The platform will equip Law Enforcement Authorities with enhanced data fusion, real-time monitoring and analytical tools in order to support evidence-based operations. NET plans to exploit this result by integrating AVALANCHE into its cybersecurity and intelligence solutions portfolio, further advancing data-driven security services across Europe.”

IML: “The AVALANCHE platform represents a highly valuable and innovative solution for integrating intelligence collection and analysis capabilities into a unified operational environment. IML contributes to the development of advanced analytical components and user-facing functionalities, supporting efficient investigation workflows. The platform will significantly enhance end-users’ ability to process large-scale OSINT data, improve decision-making, and reduce investigation time. IML intends to exploit this KER through integration into security platforms, licensing opportunities, and further development of analytical modules for law enforcement and public security organizations.”

UBI: “UBI considers the AVALANCHE platform a key asset for supporting LEAs in investigating disinformation, FIMI, hate speech and deepfake-related threats across heterogeneous online environments. UBI contributes through AI-driven disinformation detection, advanced OSINT collection capabilities and explainable analytical outputs that help transform large volumes of online data into operationally useful intelligence. The platform will support end users by enabling more structured collection, analysis, correlation and reporting of suspicious narratives, coordinated inauthentic behaviour and emerging information threats. UBI intends to exploit this KER by further enhancing its AI-based security analytics and OSINT capabilities and integrating them into future law enforcement, cyber intelligence and crisis-response solutions.

IDR: “The AVALANCHE platform, our main result, brings together a large number of capabilities currently of high value to potential LEA customers, such as: OSINT collection & analysis, disinformation/FIMI detection, hate speech detection, network reconstruction, secure information exchange and more, all in one platform. For LEAs this means faster investigations, better results, improved cross-LEA data exchange, more actionable insights against disinformation and FIMI, to name a few. We have helped shape the KER (platform) through requirements engineering, use-case modelling, UX feedback, and leading the secure information exchange and data management activities. We also lead training, dissemination and exploitation aspects of the project, aiming to connect technical results with real AVALANCHE adoption. We will exploit the AVALANCHE platform primarily through holistic joint exploitation, since the value for the potential LEA customers lies in the integrated platform itself. We also plan to reuse the requirements, interoperability and secure exchange assets deployed in AVALANCHE in future LEA- and civil security-oriented projects.”

QAD: “The AVALANCHE platformis a novel component for European resilience against disinformation and FIMI. Τhe first platform to unify disinformation, hate-speech and deep fake detection with origin-of-spread analysis designed for law enforcement agencies. QAD delivers three core technical components for the platform. First, it provides OCR (Optical Character Recognition) to extract text from images and videos. Second, it conducts origin-of-spread analysis to track down the initial source of specific web content and map the exact path it took as it was transmitted. Third, it features deepfake detection for identifying manipulated images. Additionally, QAD supports the seamless integration and validation of these tools across the project's pilot phases. End users can triage large OSINT streams at scale, recover text hidden in visual content, trace how narratives and manipulated media propagate, and flag synthetic media with evidence grade outputs for investigations and strategic communications. This transforms time consuming manual searches into evidence grade, explainable outputs for fast and accurate investigations. QAD will exploit our components by collaborating with external stakeholders, such as larger system integrators and solution providers within the consortium to reach Law Enforcement Agencies. Furthermore, QAD will explore the establishment of potential partnerships with relevant stakeholders, potential customers and early adopters.”