Turning MongoDB into a Predictive Database involves leveraging the power of artificial intelligence (AI) and machine learning (ML) to enable rapid insights from patterns detected at rates faster than manual analysis. A partnership between MongoDB, Inc. and MindsDB aims to enhance the ability to streamline predictive capabilities for data science and data engineering teams within organizations. The MindsDB AutoML framework provides methods to optimize performance, including adjusting hyper parameters and enabling novel upstream automation of data cleaning, data pre-processing, and feature engineering. By integrating with MongoDB Atlas, users can generate predictions directly in the database, accelerate development speed, and simplify deployment workflows. To get started with MindsDB, users can access a cloud-managed version or install it locally using Docker. The framework provides tools for connecting to MongoDB, training machine learning models, and querying the results. With MindsDB's predictive capabilities inside MongoDB, developers can build machine learning models at reduced cost, gain greater insight into model accuracy, and make better data-based decisions.