Accurate HCC coding depends on clear clinical documentation and appropriate identification of conditions that are supported within the patient record. Understanding the HCC identifier associated with a documented condition is an important part of structured risk adjustment coding. Chronic kidney disease is one area where careful documentation review is particularly important. CKD HCC coding requires coding professionals to evaluate the documented condition, supporting clinical information, and applicable coding requirements rather than relying solely on a diagnosis appearing in the record. Technology can support these workflows by organizing documentation and helping coding teams identify relevant information for review. RafoDEX AI for HCC coding is designed to support HCC-focused coding workflows and can complement professional review. AI-assisted tools can be particularly useful when organizations manage large volumes of clinical documentation. However, automation should work alongside experienced coding professionals who can evaluate documentation context and resolve complex cases. Effective HCC workflows require more than identifying a diagnosis. Coding teams need to consider documentation completeness, applicable coding guidance, and the relationship between documented conditions and risk adjustment requirements. For organizations managing chronic condition coding at scale, combining specialty-focused technology with professional expertise can help create a structured and consistent workflow. RafoDEX AI provides an automation-oriented approach to HCC coding while maintaining the importance of human review. A well-designed HCC coding process can therefore connect clinical documentation, coding review, and risk adjustment workflows in a more organized manner while supporting accuracy and operational efficiency.