AI for healthcare
Transparency & explainability
Our modeling approach is completely transparent and auditable, allowing anyone to review and make decisions with no black box.
Trust & governance
With our model management and governance processes, users can know that their models are consistently fair and unbiased for everyone.
Time aware modeling
Time aware modeling allows you to improve prediction accuracy for clinical use, pharmaceutical development, and beyond with applications in time series forecasting and out-of-time validation.
Equip providers
Develop custom AI applications that empower healthcare providers to make smarter decisions, safeguard patients, and enhance the healthcare experience. From care to operations and logistics, improve outcomes and drive efficiency with predictive and generative AI.
- Staffing optimization
- Appointment attendance likelihood
- Social determinants of health identification
- Admission risk
- Hospital/ward length of stay
- Operating theater productivity
- Demand forecasting
- Autonomous virtual primary care
- Diagnostic test requirements
- Healthcare employee churn
- Autonomous clinical coding
- Auto generating clinical documentation
- EHR search and summarization
Support payers
Deliver generative and predictive AI solutions to tackle payers’ toughest challenges—navigating the evolving healthcare landscape, improving member health, and gaining actionable insights to optimize claims management.
- Citizen propensity for surgery
- Behavioral health admissions
- Case management engagement
- Medication adherence
- Prediction of high-cost service
- Accurate cost of care prediction
- Fraud, waste, and abuse detection
- Membership churn and leakage
- Automating patient care navigation
- Healthcare consumer language translation
Accelerate life sciences R&D and impact
Deploy models that accelerate all aspects of the product life cycle, from drug discovery through manufacturing and customer delivery.
- ADMET prediction
- Yield forecasting
- Patient match for clinical trials
- Clinical trial efficacy prediction
- Defective products and defect analysis
- Drug delivery optimization
- Target provider and patient identification
- Personalized marketing
- Revenue forecasting
- Automating clinical trial patient identification
