Some of the project highlights during this period are:
- Scientific and Technical advances across trustworthy AI components. PANDORA delivered major progress in federated representation learning, uncertainty quantification, semi-automated data labelling, synthetic data generation, dimensionality reduction, and energy-efficient continual learning. Several KPIs under Objectives 1–3 were already achieved or exceeded (e.g. +70% federated detection accuracy, +35k× energy gains, +50% improvement in annotation accuracy).
- Deployment of core aArchitecture, data backbone, and first operational testbeds. The project defined the 4+1 PANDORA architecture, delivered the GDPR-compliant Data Collection Mechanism, released initial AaaS/CaaS/IM platform components, and instantiated PANDORA testbeds enabling end-to-end data pipelines for training, inference, monitoring, and orchestration.
-Consolidation of cross-sector pilots and validation framework. All use-case scenarios, requirements, and pipeline blueprints were defined, and GDPR-compliant data flows established.
Work highlights per WP:
WP2 delivered the complete architectural foundation of the PANDORA framework and produced the requirements analysis framework guiding all pilots. Use-case scenarios, business/data/user requirements and pipeline blueprints were aligned across domains.
WP3 advanced key scientific components: synthetic data generation (tSDG/vSDG), uncertainty quantification (QU-MAD), explainability (GENEO & causal models), automated labelling/completion (NNTL-MVI), and dimensionality reduction/fusion (DRFEC). Multiple KPIs were successfully achieved, with validation across industrial datasets.
WP4 developed core methods enabling resilient and energy-efficient AI pipelines, including continual, domain-informed and explainable AI , continual inference acceleration, federated representation learning, and adaptive distribution of inference tasks. Models were validated on real datasets with significant performance gains.
WP5 delivered key platform components, i.e. AaaS, CaaS, Intent Manager, authentication and UI. Initial integration of training, inference, monitoring, and orchestration pipelines was achieved. Testbeds were instantiated, enabling operational deployment of PANDORA components in industrial settings.
WP6 produced complete pipeline instantiation documents for all pilots, with validation procedures and KPI-driven evaluation variables. Preparatory steps for on-site experimentation were initiated across all use cases.
