Statisticians and programmers using multiple software systems (e.g., SAS, R, Python) often encounter differences in analysis results, requiring further exploration and justification. Investigating these discrepancies can be time-consuming, especially when documentation doesn’t fully explain the software’s approach. Reasons for discrepancies may include differences in statistical methods, options, convergence algorithms, and rounding methods. Usually, neither software is incorrect, but they operate differently. As statisticians increasingly use multiple software, identifying reasons for differences becomes crucial. Comparing Analysis Method Implementations in Software (CAMIS) is a collaboration between PHUSE, the R Validation Hub, PSI AIMS, and the R consortium. The project investigates differences and similarities between SAS and R, storing code, case studies, results, differences, and findings in an open-source GitHub repository. This talk will discuss the project’s future roadmap and how you can contribute. By encouraging open-source collaboration, the project aims to become the go-to repository for statisticians and programmers to reference.