UpTrain observes the performance of your model and pin-points (any) dip in model’s accuracy to a specific feature combination
UpTrain compares your production data-points’ distribution against your training dataset and detects out-of-distribution cases
UpTrain allows you to define “Signals” as a way to incorporate your domain-specific knowledge which are used to filter out specific subsets of data which can be used to retrain the model
With UpTrain, you can attach your existing data annotation, model training, and deployment pipelines to activate a completely automated continuous model improvement cycle
UpTrain offers seamless integration with all the major ML libraries and MLOps tools, allowing you to get started in less than 5 minutes
UpTrain is built by passionate ML engineers who aim to leverage their past experience and democratize the best-in-class ML observability and Refinement tooling for the open-source community