Notebook hosting for easy model iteration and development
Register custom algorithms for specific problem types including time-series, vision, and NLP
Use human intelligence and compete with models built by our AI techniques
Evaluate on standard metrics
Use this MLOps model to rapidly iterate on model performance and benchmark against AI generated models
How It Works
Apples to Apples Comparison
In data science, it’s difficult to have an apples to apples comparison; different types of use-cases require different metrics. We introduce standard definitions for these metrics, which makes it very easy to compare against the same test sets.
Compete with the machine, iterate, and improve over time. Insights from this comparison can be further used to refine your own model. We also provide easy integration with open source models by Huggingface; data science teams can test an open source model and easily develop and experiment.
Feature Engineering using our enterprise class feature store. Measure how much it helps increase performance compared to automated techniques.
Use enterprise class MLOps capabilities to bring your own techniques / algorithms to the entire organization.