DataRobot is a US software company whose platform helps organisations build, operate and monitor AI applications. It became known for automated machine learning (AutoML), which trains and compares many model variants automatically – for example to predict customer churn or demand. Today the company also focuses on running and governing AI agents (as of October 2026).
Machine learning is a branch of artificial intelligence in which computers derive patterns from data instead of having every rule explicitly programmed. Depending on the task, models learn from labelled examples (supervised), from unlabelled data (unsupervised) or through rewards (reinforcement). Applications range from spam filters and demand forecasts to product recommendations. Quality depends heavily on the quantity and quality of the training data.
A machine learning pipeline is a defined sequence of steps that turns raw data into a deployable model: collecting and cleaning data, preparing features, training, evaluating, deploying and monitoring. Automating these steps makes results reproducible and lets new data be processed with little effort. A retailer, for instance, can retrain and test its sales forecasting model every week using the latest figures.
Amazon SageMaker is the Amazon Web Services (AWS) cloud service for building, training and deploying machine learning models. In late 2024 the original service was renamed “Amazon SageMaker AI”; since then, “Amazon SageMaker” has referred to a broader platform for data, analytics and AI with the SageMaker Unified Studio interface (as of October 2026). It is used mainly by data science teams running models on AWS infrastructure.
MLflow is an open-source platform for managing the entire life cycle of machine learning models, originally introduced by Databricks in 2018. It records experiments with their parameters and metrics, manages model versions in a registry and simplifies deployment. More recent versions also support tracing and evaluating applications built on language models. Teams can therefore trace which model was produced with which data and settings.
