As anyone that has worked in a factory will know, watching a training video or reading an instruction manual is one thing. Doing the job is another. In a small company with a handful of staff, new employees can job-shadow or simply ask for help. In a plant with 100-plus people, high staff turnover, multiple shifts and multiple languages, things are more challenging, says DeepSight cofounder Nicolas Bearzatto. When knowledge lives in people’s heads rather than systems, high turnover, language barriers, and inconsistent training translate directly into slower ramp-up times, higher error rates, and costly downtime. DeepSight’s pitch is to capture that tribal knowledge once and deliver it back to workers as clear, visual, multilingual instructions—right on the factory floor. Founded in Montreal in 2019 by Bearzatto and Francis Dubé, DeepSight began with an augmented-reality (AR) engine capable of visualizing and manipulating 3D models. Over time, it has evolved into a full knowledge-management and work-instruction platform for industrial environments, with a strong focus on food manufacturing. The core innovation is a rapid knowledge capture system that records experienced operators using smart glasses as they perform tasks, says Bearzatto. The system captures what they see, say, and do, then uses AI to synthesize this data into standardized, step-by-step digital work instructions in minutes. “We were like, let’s take Joe or Bob… you know, that guy that has been in the company for 25 years that knows all the tricks, that knows how to use every machine, and he could retire in…

Continue reading →

As anyone that has worked in a factory will know, watching a training video or reading an instruction manual is one thing. Doing the job is another. In a small company with a handful of staff, new employees can job-shadow or simply ask for help. In a plant with 100-plus people, high staff turnover, multiple shifts and multiple languages, things are more challenging, says DeepSight cofounder Nicolas Bearzatto. When knowledge lives in people’s heads rather than systems, high turnover, language barriers, and inconsistent training translate directly into slower ramp-up times, higher error rates, and costly downtime. DeepSight’s pitch is to capture that tribal knowledge once and deliver it back to workers as clear, visual, multilingual instructions—right on the factory floor. Founded in Montreal in 2019 by Bearzatto and Francis Dubé, DeepSight began with an augmented-reality (AR) engine capable of visualizing and manipulating 3D models. Over time, it has evolved into a full knowledge-management and work-instruction platform for industrial environments, with a strong focus on food manufacturing. The core innovation is a rapid knowledge capture system that records experienced operators using smart glasses as they perform tasks, says Bearzatto. The system captures what they see, say, and do, then uses AI to synthesize this data into standardized, step-by-step digital work instructions in minutes. “We were like, let’s take Joe or Bob… you know, that guy that has been in the company for 25 years that knows all the tricks, that knows how to use every machine, and he could retire in…

Continue reading →

As anyone that has worked in a factory will know, watching a training video or reading an instruction manual is one thing. Doing the job is another. In a small company with a handful of staff, new employees can job-shadow or simply ask for help. In a plant with 100-plus people, high staff turnover, multiple shifts and multiple languages, things are more challenging, says DeepSight cofounder Nicolas Bearzatto. When knowledge lives in people’s heads rather than systems, high turnover, language barriers, and inconsistent training translate directly into slower ramp-up times, higher error rates, and costly downtime. DeepSight’s pitch is to capture that tribal knowledge once and deliver it back to workers as clear, visual, multilingual instructions—right on the factory floor. Founded in Montreal in 2019 by Bearzatto and Francis Dubé, DeepSight began with an augmented-reality (AR) engine capable of visualizing and manipulating 3D models. Over time, it has evolved into a full knowledge-management and work-instruction platform for industrial environments, with a strong focus on food manufacturing. The core innovation is a rapid knowledge capture system that records experienced operators using smart glasses as they perform tasks, says Bearzatto. The system captures what they see, say, and do, then uses AI to synthesize this data into standardized, step-by-step digital work instructions in minutes. “We were like, let’s take Joe or Bob… you know, that guy that has been in the company for 25 years that knows all the tricks, that knows how to use every machine, and he could retire in…

Continue reading →