RM新时代登录网址_Smart Healthcare Insurance Solution

Core Advantages

Full-stack in-house technology, deep industry expertise

Top Medical LLM-Driven, Industry-leading Cognition

Powered by the "U2" healthcare-vertical LLM — repeated #1 in MedBench and other authoritative evaluations. Deep medical logical understanding and reasoning truly comprehend medical records, not just rule matching.

Authoritatively Validated Excellence

The DRG smart coding solution co-developed with Peking Union Medical College Hospital achieved 93.6% grouping accuracy — matching human expert coders and proven through top-tier medical institution practice.

Benchmark Large-scale Deployment

Built China's first provincial-level healthcare insurance LLM (Jiangsu), proving large-scale delivery and governance from single-hospital to regional-complex scenarios.

Featured Customers

Trusted by leading brands, proving solution value

Peking Union Medical College Hospital

To be addedUnisound’s Medical Insurance Settlement List Generation Agent has been officially deployed at Peking Union Medical College Hospital. Using AI to extract clinical information from electronic medical records, the Agent combines machine pre review with human verification to generate and validate compliant medical insurance settlement lists. It achieved 92% accuracy in principal diagnosis selection and 93.6% accuracy in case grouping, helping prevent claim denials caused by nonstandard coding and reducing penalty risk by more than 80%.

Jiangsu Healthcare Insurance Bureau

Unisound developed the Medical Insurance Fund Supervision Agent for the Jiangsu Provincial Healthcare Security Administration. Drawing on Unisound’s capabilities in medical NLP, large language models, and clinical record understanding, the Agent jointly analyzes clinical narratives, care pathways, pharmaceuticals, medical consumables, and insurance settlement data. Across DRG, DIP, and fee-for-service payment scenarios, it identifies inconsistencies between clinical activities and claims, then automatically produces supporting evidence and investigation leads for suspected violations. This helps reviewers quickly locate high-priority cases while improving the depth and quality of medical insurance fund supervision.