Clients wants to understand parent child relationships between medical products that is used in their surgery procedures. This will enable better mapping and usage for inventory and surgery optimization purposes. AAARL created initial cluster analysis on medical product data, with improved results from client semantics. The analysis was based on a specific subset of data filtered by brand and company names and used name/string vectorization. The project aims to use these clusters as a new categorization label in the product master to improve data organization. Additionally, the team explored visualizations, including a graph that shows the relationships between brands, companies, and GMDN codes. Although the visualizations can become complicated, they provide an interesting way to understand the data's relationships. The final goal is to create a dashboard for users to filter the data by various fields.