We’re here to simplify your journey into healthcare AI and machine learning.
We want to simplify your journey into healthcare AI and machine learning.
Talk to Lumiata
Healthcare data is uniquely complex, offering a wealth of potential benefits as well as challenges, but your data science strategy doesn’t have to be. Built from the ground up specifically for healthcare, Lumiata AI products provide both the tools and collaboration necessary to manage your needs.
I want to…
I want to…
Ready to get started? Check out Lumiata packages to get your data machine-learning-ready and build predictions fast – you can even have us build and train your models for you. We offer the finest in healthcare machine learning in one straightforward partnership.
Lightning AI Model Builder
Friction-free machine learning productivity
Our Lightning AI Model Builder allows you to leverage Lumiata’s flexible infrastructure to train on enormous datasets without server issues or limits to your scientists’ imagination.
- Immediately build high-performing data models from tens of thousands of auto-generated, healthcare-specific machine learning features (all tested and proven with healthcare data).
- Scale as your needs evolve without being slowed down by large, clunky datasets or server issues.
- Improve speed and ingenuity with the ability to have multiple data scientists working on the same data on the same platform – with zero lag.
- Innovate new ML features from a foundation of data enriched by Lumiata’s clinical IP, disease codes, and lab results.
- Low latency exploratory data analysis to query millions of records in seconds – not minutes.
Spectrum AI Model Catalog
Ready-made healthcare ML models that solve real healthcare problems.
Over 100 pre-trained models that can be used as-is or customized to fit your needs.
- You’ll have access to a financial model suite that’s up to 80% more accurate than the nearest competitors’ cost prediction models* as well as a clinical suite that’s up to 65% more accurate than the leading carrier.
- Take advantage of our AI, even if you don’t have a data science team.
- Solve underwriting and pricing challenges with pre-trained ML models built for healthcare.
- Leverage predictions to design care management based on patient and population risks.
- Generate accurate predictions for the onset of 20+ diseases
- Three ways to leverage Spectrum AI Model Catalog:
- Dive into data science with pre-trained models
- Build smarter models with transfer learning
- Have us build a custom model for you
*based on a head-to-head comparison with Wakely and Cotiviti
|Financial Models||Clinical Models|
|-High-Cost Member or Patient|
|-Chronic Condition Management|
Predictive Applications & Healthcare Analytics
Easy-interface predictions and dashboards
Keep up with your dynamic membership and patient population needs with no technical expertise required—all while you access the ongoing data maintenance and hygiene that keep your data machine-learning-ready.
- Bring advanced business analytics and scalable data science productivity—even to non-technical users
- Provide more effective treatments by seeing high-risk patients and their key risk factors
- Identify members likely to develop a disease or at risk of hospitalization in the next 12 months
- Optimize stop-loss underwriting
Healthcare Data Management
Your path to pristine healthcare data.
Lumiata will shine a light on your disparate and duplicate data, enriching and normalizing your assets longitudinally with our clinical IP and Lumiata disease codes.
- Build models free of data quality issues
- Reduce time building models 65-85% —get started in days, not weeks or months
- Free your data team to spend more time on data science and less on data engineering
- Scale the talents of your engineers, data scientists, and analysts
- Centralized Patient360 records
ML Lifecycle Management
Travel the machine learning lifecycle, the easy way.
We manage the data and infrastructure; we handle the model packages and manage ML operations.
- Seamlessly move your models into production
- Accelerate the building, deployment, maintenance, and operations of your ML models
- Invest fewer people in your ML ops
- Get to your ideal models faster with shorter experimentation cycles