With our robust model library pre-trained on billions of healthcare claims, and an unlimited number of algorithms to be added, it’s easy to start learning!

Here are 2 use cases to show how our Supervised and Unsupervised algorithms work:


Supervised learning:  use case

State in the US looking for a better way to identify over prescribers of opioids for their audits
Supervised Learning Image v7

Unsupervised learning:  use case

Use Case for Unsupervised Learning used for a healthcare organization that wanted to match up transactions with their General Ledger to ensure complete payment.

Unsuperversized Learning 2