How robust is the actual data integration from simply tracking model growth to populating a daily research dataset?
Often, the weakest link is assuming that "tracked" equals usable, especially when new models might have critical security vulnerabilities or break existing API contracts.
Just because a new model is listed doesn't mean it's stable enough for reliable integration, which creates a significant failure mode for any real-world application.
For example, we see this with software updates that are 'available' but frequently cause more problems than they solve, forcing rollbacks.