Learning Experience Platform

Our client, a precision manufacturing company with eight hundred employees across three production facilities, was implementing AI-assisted quality control systems on their production lines. The new technology promised to reduce defect rates by over forty percent, but only if the entire operations workforce could be trained to work effectively alongside the AI tools within a single quarter. The company's existing training infrastructure, a collection of PowerPoint presentations delivered in classroom sessions, was entirely inadequate for the scale and speed required.

Previous training initiatives had struggled with low engagement and completion rates. The company's last major upskilling effort, a compliance training rollout the prior year, achieved only a forty-six percent completion rate despite being mandatory. The workforce was diverse in terms of technical literacy, shift schedules, and primary language, factors that made a one-size-fits-all approach impractical. Floor supervisors could not afford to pull entire teams off the line simultaneously, and the company needed training that workers could complete at their own pace without disrupting production output.

The stakes were high. The AI quality control systems were already purchased and scheduled for deployment. Without a trained workforce, the multi-million-dollar investment risked being underutilized or, worse, misused in ways that could compromise product quality rather than improve it.

The learning management system was architected as a progressive web application that runs on any modern browser, eliminating the need for app store installations on shared floor devices. We implemented an offline-first data strategy using service workers and local storage, so employees can continue training during network interruptions that are common in industrial environments. Completed modules sync automatically when connectivity is restored.

The adaptive learning engine uses a lightweight assessment algorithm that evaluates performance across knowledge checks, practical exercises, and time-on-task metrics. The algorithm maps each worker's demonstrated competencies against the target skill profile for their role, dynamically selecting the next content module from a library of over two hundred micro-lessons. Each micro-lesson is designed to be completed in five to ten minutes, fitting within the natural break points of production schedules.

Content was developed in close collaboration with the client's quality engineering team to ensure technical accuracy, and all modules were reviewed by frontline supervisors for practical relevance. We created three language tracks with localized content, not just translated text but culturally adapted examples and terminology that resonate with each language community within the workforce.