Onos provides a specialized AI platform for health plans to optimize behavioral health programs by detecting cost leakage and ensuring appropriate care pathways. The platform leverages behavioral health-specific models trained on extensive clinical and claims data to monitor member progress and provider quality. This results in reduced waste, improved clinical review efficiency, and better alignment of care with clinical guidelines.
Funding
$6.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Behavioral health programs often suffer from waste, inefficiencies, and administrative burdens, leading to suboptimal care and financial losses for payers. Fragmented clinical data, manual processes, and a lack of oversight contribute to unnecessary or inappropriate care, fraud, and abuse.
Solution
Onos provides a behavioral health platform designed to minimize waste, streamline operations, and improve health outcomes for payers. The platform aggregates scattered clinical data, including handwritten notes, diagnostic questionnaires, and EHR data, to create a holistic view of each member. By leveraging machine learning models trained on behavioral health care standards, Onos identifies inappropriate care practices, detects cost leakage, and ensures members receive evidence-based care at scale. The platform also streamlines administrative tasks, empowering clinical teams to focus on delivering high-quality care.
Target Audience
The primary target audience is payers in the behavioral health sector, including health plans and managed care organizations.
Features
- Aggregates clinical data from various sources, including handwritten notes and EHRs, to create a 360-degree member view.
- Employs proprietary machine learning models trained on behavioral health data to detect waste and irregularities.
- Transforms care guidelines and plan policies into a machine-readable format to ensure evidence-based care delivery.
- Alerts users to deviations from appropriate care paths and provides recommendations for corrective action.
- Offers a collaborative web application to unify teams across behavioral health programs.
- Integrates with existing systems via flat file/CSV, API, or data warehouse/lake connections.
- Uses Reinforcement Learning with Human Feedback (RLHF) to continuously improve the accuracy of its recommendations.
- HIPAA-compliant platform with locally hosted AI & ML models to protect sensitive member data.