Move machine learning model from development to production at a fraction of cost

Deploy to any cloud, on-prem or hybrid based on the infrastructure of your choice by determining the cost for managing the computing resource and monitoring the performance of machine learning models

Onboard faster with readily available deployment pipeline templates

Kubernetes based deployment with reproducible CI / CD pipelines makes it easier to onboard any new environment like QA, Pre-Prod or onboard new team with machine learning models along with the infrastructure needed to train the model and run the inference for the model

Download our white paper to learn more about how we overcame MLOps Challenges

ML Platform – SageMaker Vs AIQ