The aim of the study “Farm Know” is to create an extensive agriculture corpus to aid research and development in a certain area. The procedure involves scraping 187000 files using different Python libraries and consolidating them into a single parquet file to enhance storage and analysis. Some of the pest management, crop diseases, weather conditions, and farming practices insights that are derived from corpus under analysis are quite noteworthy. The study is essential because it may shift the paradigm on agricultural research owing to the fact that there will be massive data that can undergo rigorous analysis and experimentation. The target users of “Farm Know” are researchers, agronomists, and policymakers which enables greater ease of addressing emerging trends, identifying problems, and devising innovative solutions due to diverse agriculturally related data being consolidated into one platform. This corpus also stands to advance technology in agriculture by enabling machine learning and AI applications. The goal of this research is to foster innovation and new ideas within the agricultural community by stimulating the newfound accessibility provided by integrating all corpuses with agricultural data.