Instantly deploy any ML model on any Kubernetes cluster whether it be Tensorflow, Keras, sklearn, R and more with one click
Choose to deploy machine learning model to production for batch predictions or real time predictions
Connect via flexible interfaces including SDK and REST API for deploying models
Monitoring, alerts and Continual Machine Learning
Enhance performance of machine learning in production with custom alerts detecting model decay, bad input, model drift and more.
Set triggers to automatically retrain and update your model with natively integrated continual learning
Automatically manage the upkeep of your service with zero downtime
Model management in production
Monitor and track predictions, ML health and system health using production-grade environment
Safely deploy new machine learning model version to production with integrated canary-release mechanism
Experiment with multiple models and advanced A/B testing capabilities
Easily export prediction data for continuous research
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