Argon Ventures

An extra pair of eyes to assist your workers

Helping manufacturing workers avoid costly assembly mistakes

Retrocausal is an AI-enabled, software platform utilizing computer vision, deployed via off-the-shelf cameras above employee workstations, to monitor, analyze and flag mistakes made during the manufacturing assembly process. Quality control in manufacturing and industrial engineering processes is one of the biggest cost drivers affecting operations and safety, and hiring, training and retaining workers to perform increasingly complex assembly operations is one of the biggest challenges manufacturers face. The American Society of Quality reports that many companies have quality-related costs as high as 15% to 20% of sales revenue, and in some cases those poor-quality costs reach 40% of total operations. According to the insurance carrier Allianz Global Corporate & Specialty, defective products not only pose a serious safety risk to the public but can also cause significant financial and reputational damage to the companies concerned. Defective product incidents have caused insured losses in excess of $2B over the past five years, making them the largest generator of liability losses. Human error is among the top reasons to blame for the poor quality. Retrocausal is designed to address these deep pain points.

Founded in 2020 by a team of strong experts in augmented reality and computer vision technology, Retrocausal identifies when workers make mistakes during the manufacturing assembly process through auditory and visual cues (displayed on a monitor) and provides video examples of correct assembly procedures. Retrocausal’s value proposition lies within its ease and speed of deployment, and it does not require a change in behavior or workflow. The platform accumulates insights from individual workstations into an analytics dashboard to provide average cycle time, yield error rates, and other valuable metrics. This helps supervisors to identify common error patterns, perform root cause analysis, and identify employee training opportunities. Lastly, the solution allows to save and search video records by product numbers to allow for traceability of parts or in cases of a product recall.