Michael Lynch shares his background, mentioning his experience in entertainment, transitioning into technology through computer games, 3D modeling, and eventually founding Praxie after selling a previous company to AP.
Praxie is introduced as a digitization platform aimed at helping companies in the manufacturing sector overcome challenges related to managing processes using traditional methods like whiteboards, huddle boards, and Excel sheets. Lynch emphasizes the importance of digitization for leveraging AI effectively. The platform acts as a unifying, no-code solution that connects machine data, applications, and databases, enabling companies to automate processes and achieve improvement across various applications.
The conversation delves into the current state of AI in manufacturing, with a focus on generative AI revolutionized by models like GPT (Generative Pre-trained Transformer). Lynch explains how Praxie integrates AI as a pragmatic extension of human capabilities within lean processes, enhancing efficiency and decision-making. The platform allows users to input data digitally, enabling AI to analyze, summarize, and suggest actions for process improvement.
The discussion then explores the ongoing digitization process, emphasizing the need to move away from manual methods like spreadsheets and templates. Lynch provides examples of how Praxie facilitates digitization, such as digitizing end-of-shift reporting, 5S, gima, Kaizen, and more. The goal is to create a digital realm where AI can analyze and optimize plant operations.
A demo is offered to illustrate how Praxie works in practice, showcasing features like generating executive summaries, suggesting actions, and building action plans using AI. The platform’s flexibility in modifying forms and generating AI-assisted A3s is highlighted.
The conversation also addresses the potential impact of AI on the workforce, with Lynch expressing a positive view that AI can augment workers and improve their lives. The transition to the next generation of workers is discussed, emphasizing the role of AI in knowledge integration and process optimization.
Toward the end of the interview, Lynch responds to an impromptu question about the data set behind Praxie. He explains the importance of an infrastructural layer before large language models to ensure accurate and relevant information.
The interview concludes with information on how interested parties can contact Praxie for further discussions and demonstrations, emphasizing the practical value and benefits of digitization and AI in the manufacturing sector.
