Prealize Health:

The most advanced predictive analytics in healthcare. We are powering the future of healthcare with confidence and accuracy in action

Founded by two industry thought leaders from Stanford University and through continuous partnerships with Stanford, Prealize is committed to transforming healthcare from reactive to proactive, reducing healthcare costs, and enabling more people to live healthier lives.

Our predictions include:

Knowing each member’s future health events and when those events will happen
Identifying members who are most likely to engage and their preferred engagement channels
Predicting trends and future costs and how they impact group risk, premium underwriting, and stop-loss

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

Trains on your data or ours, resulting in higher accuracy and precision
Consistently delivers more accurate predictions than traditional models
Predicts the likelihood of a health event AND when the event will occur: Time-To-Event (TTE)
At Prealize, we’re transforming healthcare from reactive to proactive, creating a new paradigm for healthcare predictive analytics.

The Prealize Advantage:
What Sets Us Apart

A Proactive AI Foundation Model Solution
Built and trained exclusively on healthcare data, our model accurately predicts the next health event and Time-To-Event (TTE) to enable effective action
Validated Technology with Proven Accuracy and Precision
Developed at Stanford University and through a continued partnership, we deliver 5x accuracy over traditional predictive and AI models
Continuous Learning
Healthcare is dynamic and so are our models. We’re committed to ongoing refinement and improvement, ensuring our predictions remain ahead of the curve

Accurately predict financial risk, enabling more precise underwriting for fully insured and level funded groups, for PEOs, and underwriting for stop-loss.

Financial Risk Management
Accurately predict financial risk, enabling more precise underwriting and stop-loss
Care and Condition Management
Precisely identify who will have health events, the drivers of those events, as well as their timing and cost
Member Engagement
Unambiguously determine members’ propensity to engage, channel preference, and drivers of engagement

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), a recently published method from Stanford University which 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.

Latest News

April 30, 2025
Demystifying Model Artifacts: Do AI Models Store Patient Data?
As AI continues to revolutionize healthcare, one question keeps surfacing: Do trained AI models store patient data? Healthcare payers and…
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April 14, 2025
Taming the Hydra: Predictive Analytics as Your Condition Management Superpower
How Time-to-Event Prediction Turns Chronic Care Chaos into Precision Medicine The Problem: Chronic Care is a Game of Whack-a-Mole…
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April 8, 2025
Ensuring Fairness in Healthcare AI: Why Gender and Age May Not Indicate Bias in AI Predictions
Artificial intelligence (AI) is transforming healthcare, offering advanced predictive models that help provide proactive care, improve…
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