chronic conditions and coding gaps that may impact care quality and reimbursement. Its core platform uses transformer-based machine learning models to process diverse data formats such as scanned documents, physician notes, and claims data, converting them into structured insights that highlight potential diagnoses and risk adjustment opportunities. The system flags findings for clinician review, providing supporting evidence and explanations to assist with medical coding and documentation accuracy.

Keebler Health’s tools are designed to support value-based care models, where healthcare providers are responsible for managing patient outcomes and costs. By improving the accuracy of disease burden identification, the platform helps organizations optimize reimbursement processes while also enabling earlier detection and management of chronic conditions.