Teams often face challenges beyond machine learning skills, including data management and overall maturity. Focusing on organizations with at least one model in production helps mitigate risks and ensures foundational elements are in place. The goal is to transform the ML process into a reliable and valuable endeavor, especially for those prioritizing real-time applications.
