The rapidly changing nature of the New Psychoactive Substance (NPS) market and the overall large number of substances that need to be monitored have presented challenges for early warning activities in recent years. Since the number of illicit drug classes is growing exponentially over time, the current challenge is no longer to search substances during an investigation, but rather to provide a sort of preliminary identification of the substance as illicit, i.e., to tag it as such, especially when it is a new type of drug. Today several instruments equipped with up-to-date libraries allow for the rapid identification of drugs of abuse. However, this approach suffers from four main problems: 1) The instruments libraries are not updated regularly; 2) The instruments do not easily overcome the matrix effect; 3) NPSs are trafficked and sold in smaller doses, making their detection and identification more difficult; 4) Routine methods of analysis during forensic analysis are no longer effective in screening drugs of abuse, the parent drugs but also their metabolites, due to the lack of structural information and commercial reference materials. NARCOSIS (Non-tArgeted foRensic multidisCiplinary platfOrm for inveStigatIon of drug-related fatalitieS) will provide a set of features for fast, robust, and reliable multidisciplinary approach to harmonise forensic investigations by means of an up-to-date and updateable diagnostic platform with the following key features: 1) A set of selected orthogonal instruments operable both on-site and in laboratories (Raman/SERS, IR, HSI, HRMS) will be adapted to be used with the NARCOSIS platform; 2) Build a comparable and shareable (cross-organisation) reference spectra (meta-spectra) database for faster detection and identification of drugs of abuse; 3) Create an AI-assisted spectra management and integration toolkit for analytical measurements to support the EU Early Warning System to rapidly detect, assess and respond to NPS.

AI is transforming law enforcement, offering new tools for policing but also enabling advanced criminal tactics that challenge traditional methods. The global nature of crime, including cyber threats, trafficking, and terrorism, calls for innovative solutions as LEAs face vast data volumes and increasingly sophisticated criminal activities. AI has raised concerns with deepfakes—highly realistic but fake audio, video, or text that can depict individuals saying or doing things they never did. Deepfakes pose serious risks, impacting politics, economy, and social trust. Examples include fabricated videos of political figures and voice-cloned audio for financial fraud, often spread through social networks to deceive and defraud on a large scale. Forensic institutes and courts struggle to differentiate authentic evidence from AI fabrications, especially in cases involving national security. Despite promising detection research, existing methods fall short as current models rely on limited, non-diverse datasets and produce results with limited legal admissibility. The DETECTOR initiative aims to address these challenges, supporting LEAs and forensic experts in analyzing altered media. It offers an integrated solution through cross-border collaboration among AI researchers, LEAs, forensic scientists, legal experts, and ethicists. DETECTOR’s goals include: developing specialized tools for detecting media manipulation, creating comprehensive datasets, researching digital evidence exchange across borders, engaging stakeholders, informing policymakers, and training forensic experts in digital media and AI. Through these efforts, DETECTOR seeks to safeguard digital evidence authenticity and enhance forensic capabilities to counter AI-driven media manipulation across Europe

IAMI aims to revolutionize entity identification and resolution in security, intelligence, and investigation contexts. It addresses the challenges and limitations faced by current identification techniques and offers a visionary solution through advanced AI-powered software. The project's long-term vision is to propel EU LEAs and security/intelligence organizations into a new era of intelligence, investigation, and forensic capabilities. IAMI's core innovation is the development of an AI-powered software system that can seamlessly integrate with existing case management systems and analytic tools. At the heart of IAMI is the concept of the 'Identity-Attributes-Matrix (IAM)', a 3D construct that encompasses a broad spectrum of multi-modal identity-related attributes, including biometric data, non-biometric identity-related data, and analytic results. These attributes are used to facilitate large-scale entity identification/resolution, including a broader range of entity types, simultaneous and rapid multi-entity identification/resolution, systematic and continuous analysis of flux of probe attributes, confidence in noisy/corrupted probe data, reduced false positive rates, access to contact attributes, and the ability to classify fake identities and bots/avatars. Furthermore, IAMI sets the groundwork for effective collaboration and data sharing across European agencies, including international organizations like EUROPOL and INTERPOL through the establishment of a new EU-Wide IAMI enrolled data collection repository for terrorist threat assessment and awareness which enriches their capabilities and assets. The realization of IAMI's vision will be achieved through the demonstration of the developed IAMI solution. It will be communicated and disseminated among EU LEAs and security/intelligence agencies through project activities, including deliverables, training curricula, workshops, and pilots. IAMI represents a significant step forward in EU fight against terrorism.

The ForMAT project addresses limitations in forensic DNA profiling, particularly in criminal cases, disaster victim identification (DVI), and legal age assessment for asylum claimants. Traditional DNA methods struggle with unsolved cases, mass disasters, and legal age estimation. ForMAT focuses on DNA methylation (DNAm) as a solution, using epigenetic markers to estimate age and lifestyles, as well to predict tissue type. This approach enhances criminal investigations by narrowing suspect profiles and expedites missing person identification in mass disasters, improving the return of remains to families. In asylum cases, DNAm offers a radiation-free alternative for assessing age, reducing reliance on X-rays. ForMAT builds on the VISAGE project, aiming to advance these tools from Technology Readiness Level (TRL) 5 to TRL 7. By developing new DNAm kits and a bioinformatic applicaiton including forensic prediction models, ForMAT enables law enforcement to estimate age, to infer lifestyles and to identify the tissue-of origin from DNA samples. Kits include a DNAm somatic kit, as well as a DNAm germ-line kit for criminal cases, a DNAm DVI kit for guiding in the identification process of human remains, and a DNAm legal age kit for asylum assessments. The integration of Next Generation Sequencing (NGS) technologies, including second- and third-generation sequencing, enhances forensic workflows and ensures high accuracy even with degraded samples. The ForMAT consortium , consisting of 11 EU institutions, leverages expertise across countries and disciplines to bring these innovations to real-world use. Members include leading universities, police bodies, and forensic institutes, committed to scaling up, testing, and validating these tools across Europe. Their involvement in international forensic boards ensures widespread dissemination, aiming for broad adoption of ForMAT’s epigenetic molecular tools in forensic science, ultimately enhancing investigative practices and public safety.