MMC has generated substantial interest from the government due to its potential to help meet housing and infrastructure needs that traditional methods have failed to achieve. Many construction companies have incorporated MMC approaches into their delivery offers. However, challenges with MMC remain, especially given the significant range of projects that construction delivery organisations are required to undertake, with variations in the type and size of individual structures. This inconsistency can lead to challenges for the sector. With contractors required to undertake projects with varying MMC needs, there is a limited opportunity for the transfer of knowledge between schemes. This leads to the need for repeated training sessions that consume both time and money and lead to avoidable assembly errors due to a simple lack of knowledge. In addition to this, it is common for companies to use MMC components from different factories/manufacturers, requiring different assembly knowledge accentuating the issue with the constant need for staff training. Our solution, i.e., ARVAST, will minimize/eliminate the need for repeated trainings and errors from new trainees using augmented-reality (AR) in conjunction with deep learning algorithms, video analytics, big data analytics, natural language processing (NLP) and cloud computing.