Apple Photos seems to be using just Core ML[1] for on-device recognition and it does a pretty good job. As for Android, we plan to use tflite, but the accuracy is yet to be measured. And if customers do install our desktop app, we will be able to improve the indexes by re-indexing data with the extra bit of compute available.
We don't feel that the entire UX of a photo storage app will "suck" because of a reduced accuracy in search results, and we think that for some of us the reduced accuracy might not be a deal breaker.
Up until recently I’ve used Apple Photos happily since it provided a good combination of convenience plus the privacy of on-device recognition. You have a compelling product if you can convince customers you are as reliable and more trustworthy than Apple. You do face the disadvantage of not being the default option for iOS/macOS but that should be balanced by being available cross-platform in Android, Linux, Windows.
We don't feel that the entire UX of a photo storage app will "suck" because of a reduced accuracy in search results, and we think that for some of us the reduced accuracy might not be a deal breaker.
[1]: https://developer.apple.com/documentation/coreml