CoreML supports Keras but not TensorFlow because Keras models form a well-structured subset of all possible TensorFlow graphs. It would be quite difficult to support completely arbitrary TensorFlow graphs, but supporting every Keras layer is relatively straightforward.

To answer your question: I had no knowledge of this ONIX project before the public announcement today. Speaking purely for myself, if I wanted to develop a universal model exchange format, the first step I would take would be to get in touch with the makers of the frameworks that sum to 80-90% of the market share -- TF, Keras, MXNet. But maybe such a strategy was thought to be superfluous in this case -- for instance, because ONIX may not actually be intended as a universal model exchange format.