Prealize Health:
Knowing what comes next changes everything
Prealize delivers the most advanced predictive analytics in healthcare. Founded in partnership with Stanford University, our AI technology is powered by a single market‑leading transformer model built by leading data scientists and engineers.
Purpose built for healthcare, Prealize enables precision underwriting, proactive risk management, and better member care.
Inform underwriting strategies and care management decisions
Insurance underwriters and actuaries gain increased underwriting confidence and drive higher win rates.
Care managers make more informed decisions, conduct earlier interventions, improving outcomes and reducing costs.
Care managers engage members with targeted, high-value interventions, enhancing the member experience.
Our AI-powered predictions are up to 5x more accurate than other solutions


This precision in prediction uses our industry-leading MetisAI Model, developed at Stanford University. MetisAI sets a new standard for accuracy in healthcare prediction
The Prealize Advantage:
What Sets Us Apart
Accurately predict financial risk, enabling more precise underwriting for fully insured and level funded groups, for PEOs, and underwriting for stop-loss.
MetisAI: A State of the Art Healthcare Claims Foundation Model
In order to power our Prealize predictions, we have developed a state of the art foundation model based on MOTOR (https://iclr.cc/virtual/2024/poster/18777). This original published method from Stanford University was presented as a Spotlight Poster at International Conference on Learning Representations 2024. Developed by the primary author of MOTOR (and incorporating various additional improvements), MetisAI is carefully tuned to predict long term health issues by using a self-supervised transformer that was pre-trained on thousands of important time-to-event prediction tasks. As a result, we are able to provide more precise predictions compared both to traditional machine learning techniques and alternative foundation models.

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