You don't mean 100% accuracy, that means mistakes are impossible. Perhaps your error rate is very rare, but it's a bit concerning you don't attempt to quantify it.
I disagree. If we consider a single customer with a particular application, we probably imagine an iterative process like this: the customer supplies some sample images, the system gets a few wrong, they add special cases, fine-tune the hyperparameters, whatever, and after all this they literally get 100% on the customer's holdout data. If that happens for several customers then the GP statement is justified (no other number is possible for these customers).
Possibly you're thinking of a single error rate across all customers? For other customers, as stated, it's not 100%. But taking an average across multiple customers is not meaningful when some are counting pearls and some are counting crops.
Suppose it depends on which part of the chain he attributes error, plausible lighting or poor positioning - anything that is an employee duty - does throw it off and then they scrub it.
But yeah. Still.
Possibly you're thinking of a single error rate across all customers? For other customers, as stated, it's not 100%. But taking an average across multiple customers is not meaningful when some are counting pearls and some are counting crops.