As today’s systems engineers are faced with an overflow of data and a significant increase in the complexity of systems, Spatez is bringing the power of Artificial Intelligence (AI) to help address the need for getting requirements right the first time. Currently in beta development stage, this move will allow engineers to improve their requirements definition process by flagging incomplete and ambiguous requirements while providing guidance to the author on how to improve them. Think man plus machine, combining the expertise of engineering teams to perfect their requirements with the help of AI.
When thinking in terms of systems of systems and teams of teams, requirements management is critical to the success of any engineering project. Getting requirements right the first time greatly reduces the cost and cycle time of validation by senior engineers. The cost of errors in defining requirements increases exponentially as the project moves through subsequent stages, particularly at the enterprise level. Watson AI will use natural language processing (NLP) and understanding to analyze a requirement’s text, suggesting improvements that leverage industry best practices for writing high quality requirements