Massive increases in analytical throughput together with reductions in costs have enabled multi-omics studies to be routinely performed at a scale not previously imagined. Two main barriers hamper our ability to reveal the mechanism behind a specific genotype-phenotype link: the cross-talk between multiple molecular layers cannot be properly assessed by a reductionist approach that analyses each omics layer in isolation; and the ever-growing amount of buried information in scientific literature and public omics datasets cannot be extracted without intelligent computational approaches. GLOMICAVE project addresses the need for building systems that allow streamlining both the experimental design and the analysis and integration at a systems level of large-scale omics experiments by maximizing the utility of pre-existing massive omics datasets and scientific literature to increase the understanding of biological systems as a whole. The main outcome will be a multi-omics data analysis cloud-based platform, relying on Big Data Analytics and Artificial Intelligence techniques – and using large-scale publicly available and experimental omics datasets, enhanced with an automatic processing of scientific literature, to assist experts and non-experts in identifying and understanding new links between genotype and phenotype which apply to different domains. GLOMICAVE integrative approach will be validated in 3 different industrial sectors (livestock, agro-biotechnology and environment) addressing specific challenges in 6 business cases, which will pave the way for further uptake in other business areas. The success of GLOMICAVE builds upon the expertise of a multidisciplinary team of 14 partners with expertise in omics sciences; standardization; bioinformatics; environmental assessment; mathematical modelling; AI and BDA; plant and animal physiology; food quality, microbiology; bioengineering as well as ethical, legal and social aspects.