Ensuring transparency and regulatory trust in agricultural and food value chains requires mechanisms that not only document product compliance within the framework of the Digital Product Passport (DPP) but also make it verifiable. This paper presents a hybrid compliance framework developed within the context of the SUSKULT project, combining deterministic rule validation with Retrieval Augmented Generation (RAG) to assess the compliance of fertilizer products according to Regulation (EU) 2019/1009. Organization-specific activity logs are captured in semantically structured JSON-LD, linked to domain ontologies, and processed in a two-tier architecture. The first tier performs deterministic checks, including verification of labeling according to Annex III, and logical mapping of product function categories (PFCs). The second level utilizes a retrieval-based language model that interprets these statements within the context of relevant EU regulations. Initial evaluative tests with synthetic data demonstrate that the hybrid approach delivers more stable and explainable results than purely generative models by generating weighted confidence scores and citable evidence pathways. Integrating the compliance results into the Digital Product Passport creates a verifiable anchor of trust, serving as proof of regulatory conformity and enabling data-driven, transparent, and sustainable value creation in the food and fertilizer sectors.
Gowda et al. (Thu,) studied this question.