The point is that you can split the work in two: the one you mentioned, creating and training the model, and a separate step of shaping it with reinforcement learning. Which is quite expensive, because it uses human operators in one of its steps. But apparently you can duplicate easily enough this with an API of an already educated engine, which makes the second step not be a moat anymore.