Curaberg offers an AI‑driven fraud detection platform that ingests claim submissions, EHR data, and billing logs to generate real‑time risk scores via a sub‑second API and native HL7/FHIR connectors. The system includes an interactive dashboard for anomaly visualization, automated alerting, immutable audit logs, and continuous model retraining to maintain HIPAA‑compliant detection accuracy for health insurers, provider networks, and government payers.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare payers and providers incur significant financial losses due to fraudulent claims, and traditional manual review processes are slow, labor‑intensive, and prone to error. The lack of real‑time, data‑driven detection tools makes it difficult to identify emerging fraud patterns before they impact cash flow and patient trust.
Solution
Curaberg delivers an AI‑driven fraud detection platform tailored for the healthcare ecosystem. The system ingests claim submissions, electronic health record (EHR) data, and billing logs, then applies reinforced pre‑trained machine‑learning models to generate real‑time risk scores for each transaction. An integrated risk‑management dashboard lets analysts visualize anomalies, drill into contributing factors, and prioritize investigations. The platform offers a RESTful API and native HL7/FHIR connectors for seamless embedding into existing claims processing pipelines. Automated alerting and audit‑trail generation reduce manual effort while maintaining compliance with HIPAA and industry reporting standards. Continuous model retraining incorporates new fraud patterns, ensuring detection accuracy evolves with emerging threats.
Target Audience
Primary customers are health insurers, provider networks, and government payers (e.g., Medicare/Medicaid administrators) that process large volumes of medical claims and require automated fraud mitigation tools.
Features
- Reinforced learning models pre‑trained on multi‑regional claim datasets, fine‑tunable for specific payer rules
- Real‑time risk scoring API delivering sub‑second latency for high‑volume claim streams
- Configurable rule engine that combines AI scores with deterministic business rules
- Interactive dashboard with drill‑down visualizations, trend analytics, and customizable alert thresholds
- HL7/FHIR and REST connectors for direct integration with EHR, PMS, and claims adjudication systems
- Immutable audit logs and role‑based access controls to satisfy regulatory compliance
- Scalable cloud infrastructure with end‑to‑end encryption and HIPAA‑certified data handling
- Model explainability layer (e.g., SHAP values) that surfaces feature contributions for each risk decision