Q So your example is focused on Google Sheets as the sort of end point. So I'm wondering what other things can you push your data to? Like what, what are the other end points?
A Yeah. Um, some of the first ones we built were sort of analytics warehouses, like being able to, to maintain views in Snowflake or, uh, BigQuery or Postgres itself. Uh, it's super useful to be able to take, uh, if you have like a bunch of SaaS source, uh, SaaS software as a service data sources that you want to bring in and capture and land into your own database so you can work with them there. Um, things of that kind. Quite honestly, uh, we built sheets in about a week. This sheet's materialization, and we built it for this because I couldn't think of a better way to convey what real-time data means than, like, just being able to watch it update. Um, it's not quite as cool to watch me materialize into a Postgres database or Snowflake or something. Um, so, uh, yeah, the, the materialization capability is really to all kinds of systems, whether it's, uh, key value stores or SaaS services or big analytics warehouses or cloud storage or databases or what have you. Obviously, we haven't been able to build all this out yet, but, ah, the, the capability, like, the fundamental sort of protocols and capability are in place for all of that. It sounds like you're not quite in market yet, but when you are, who will you sell to, given that you're, you're serving folks in the, you know, on the engineering staff, but also those who like spreadsheets? Yeah, uh, it's a good question. Um, so w…
AI assessment note: “analytics warehouses, like being able to, to maintain views in Snowflake or, uh, BigQuery”