Laboratory automation is a key innovation that can help overcome the social distancing requirements due to the 2020 COVID-19 pandemic. Although, automation instruments have been used for decades in high throughput settings, they have not transitioned to routine laboratory research. Moreover, current laboratory automation lacks machine learning and artificial intelligence that can help guide design of experiments based on real-time analytics. The overall goal of the proposed project is to develop and commercialize a scalable software and hardware system, LABNET, which will integrate artificial intelligence (AI) tools, autonomous and modular laboratory instruments for data transmission and storage, and cloud computing for multi-scale and machine-learning (MS-ML) modeling and analytics for laboratory research. Phase I will focus on design and demonstration of the system to perform automated ELISA assays which will be guided by AI suite of tools for rapid screening of antibodies using a commercial off-the-shelf liquid handling system. Phase II will focus on integration of additional instrumentation, biological assays and high throughput instrumentation. The developed product will be commercialized to pharmaceutical, biotech companies, research labs, universities and non-profit organizations involved in assay development, molecular diagnostics and drug discovery.