When I say no training, I mean no training. No gimmicks around data vs derived data, synthetic data, preference data, etc.
Places where I can imagine potential cracks in the literal interpretation of what I said are things like a financial analyst who does a statistical fit to predict revenue next quarter using a model based on last quarter's aggregate token consumption, which in some sense embodies your metadata (the length of your conversations) in a sea of other data. Or perhaps an infrastructure planner who makes a little model of internet bandwidth by time of day to help plan when we need a data center networking upgrade. Maybe things like these are technically training on your data in the most pedantic sense, but definitely not in the sense that most of us mean.
I promise you we're not doing any gimmicks where we transform your data and then pretend ah because it's transformed it's not your data.