Congrats on the launch. I made a tool that has some similar objectives but doesn't present as SQL itself like Trilogy seems to. I'll take a deeper look at Trilogy soon, always interested to see the variety of approaches to this.
Had some more time to drill into this and we've ended up with a very similar approach to a lot of the metadata definition and resolution - I'd love to chat sometime about how you've solved some of the common problems (table selection w/ multiple sources, the constraint vs output projection, aggregation level, etc, etc)
Oh wow yeah, a lot of parallels - thanks for sharing, I'll take a deeper dive in a bit. I think there's a lot of demand and a lot of space for different solutions; Trilogy definitely aspires to hew closer to standard SQL. (I actually really like SQL for the most part!)
I have nothing against SQL of course. The simplified approach of a UI built on top of zillion or tools like it really enables a whole next level of productivity for business users that are never going to learn SQL, but also need more query flexibility than just "dashboards" without having to wait on a BI team for answers -- I die inside a little bit every time I hear of a company doing this. And as you have noted, I also think text-to-semantic-layer is an interesting approach for involving AI/NLP.
I've been pulled away from this project for some time due to an acquisition at my day job but hoping to get back into it soon!
Also full agreement! In an optimistic view, the SQL layer (at a slightly higher level) unifies the top level accessibility tools (NLP, drag/drop chart result builders, etc) with the more tech-familiar level of analysts/engineers, and provides progressive disclosure as you go down the stack and a path to promote the adhoc/SQL level work up to reporting easily.
https://github.com/totalhack/zillion