AnnaData: It is estimated that annually around one-third of food produced worldwide is lost or wasted. Plant pests, pathogens and weeds account for a large proportion of global crop production losses in the pre-harvest stages. Countries in South Asia such as India, which are predominantly agrarian economies, are particularly ravaged by disease outbreaks in vital food crops such as paddy. In recent times, large scale changes observed in weather patterns have further compounded this problem. Current disease detection and management solutions in rice cropping systems rely heavily on visual inspection and manual scouting. Even new approaches, including those based on computer vision based techniques, often rely on “post-facto” detection of crop diseases thus limiting their ability to control crop damage. Hence there is a dire need for decision support tools that can help early detection and timely management of such pathogenic attacks on vital food crops and thereby reduce catastrophic production losses for the farming community. Crosslinks and its partners have conceived “AnnaData”, which is an affordable and robust multisensor system that utilizes deep learning models and hypervision data to accurately detect the occurrence of rice crop diseases much in advance, right in the asymptomatic stages. The efficacy of the AnnaData model has been validated in a lab setting by artificially inoculating the pathogen on a research farm in partnership with Indias National Rice Research Institute NRRI in Odisha state.