Limbix (by BigHealth)
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
Predictive AI and machine learning for precision healthcare risk management and underwriting.
Lumiata, now integrated into the AKASA ecosystem (specifically within the Retrace and Unified Revenue Orchestration platforms), is a specialized AI engine designed for the healthcare industry. Its technical architecture centers around a proprietary Clinical Knowledge Graph and deep learning models trained on billions of healthcare data points, including claims, clinical labs, and pharmacy data. In the 2026 market landscape, Lumiata positions itself as the backbone for healthcare payers and providers to move from reactive to proactive financial management. By utilizing multi-layered neural networks, it transforms fragmented healthcare data into high-fidelity risk scores and cost predictions. The platform's 'Health AI Lab' allows actuarial and clinical teams to build, test, and deploy custom models without the need for extensive data science infrastructure. Its primary value proposition lies in its ability to predict disease progression and associated costs with higher precision than traditional actuarial methods, directly impacting the accuracy of underwriting, stop-loss insurance, and value-based care contracts.
A multi-dimensional scoring engine that correlates clinical history with future cost projections using deep neural networks.
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
Predictive clinical and operational intelligence to fight death and waste in healthcare.
Predictive medical data and clinical insights for streamlined enterprise underwriting.
The professional medical network for clinicians, providing HIPAA-compliant AI and telehealth solutions.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A low-code environment for health actuaries to build custom risk models using pre-cleansed healthcare features.
A relational database of over 150 million patient journeys used to contextualize individual claims.
An AI-driven decision engine for group and individual health underwriting.
Models specifically designed to predict catastrophic high-cost claimants for re-insurers.
Identification of patients likely to miss quality metrics using predictive profiling.
Analyzes engagement patterns and satisfaction signals to predict disenrollment.
Slow manual underwriting leads to high customer acquisition costs.
Registry Updated:2/7/2026
Under-reporting of patient complexity leads to lower reimbursement.
Unexpected high-cost claims disrupt financial stability for self-insured employers.