I understand that, unfortunately your goal is still in the future (be it a week, month, year, or decade I can't tell you but it's not there today). In the interim (and if you want users while you refine) your search results should at least be on par with Google/Bing/etc. That way the "happy path" is your ML spits out the right answer and no links need to be clicked but if your logic can't come up with an answer or if it comes up with the wrong one you need the results to be a viable fallback.

EDIT: Building on what I said:

I use Github CoPilot and have been very happy with it. It's far from perfect and even when it spits out good code I have to do minor cleanup but it does save me time and "sparks joy" when it works. When it doesn't work it doesn't really get in my way. If CP required I change my entire method of programing, IDE, or if I had to go into a "special mode" to use it then it would be next to worthless to me.

As it stands you don't have a good fallback (regular results). Your product should be additive to what currently exists in the space. Not "a step forward if we guess the correct answer and a massive step backwards if we don't". I 100% believe you can make changes such that the results function as a perfect fallback (I've outlined them in various places of this thread).