The Kepler platform enables you to bring AI and Machine Learning (ML) projects to market faster with your existing teams and technological investments. It does this by combining advanced ML — including Deep Learning — with intuitive design, all within a self-serve framework built to help you create, train, and deploy AI projects, fast. This helps accelerate AI adoption by automating the end-to-end ML process, effectively enabling users with no ML experience to leverage cutting-edge ML capabilities to solve hundreds of business-critical use cases, including: Demand Forecasting, Churn Prediction, Lifetime Value Prediction, Predictive Maintenance, Sentiment Analysis, Anomaly Detection, Session / UX Optimization, and User Intent Prediction.
The Automated Data Science Workflows within the Kepler platform automate the complex and time-consuming data science steps that exist across the ML process so that users can produce AI models to predict with accuracy, forecast with precision, and illuminate new insights. The Kepler platform’s ML capabilities are constantly optimized and seamlessly integrate with key production environments. It is optimized for Azure, and is running on Azure Kubernetes Services (AKS), leveraging Microsoft Azure Compute, Database, Security, and Storage services.