[throwmeawaysoon]

poking around on your socials, it seems like you've been building for ~5 years, and are just now officially launching, after i guess a capital injection from yc.

since the core ip is "deep" as you say, i'm guessing it cost quite a bit to develop, unless you built out all of the components yourself, which, while possible, seems unlikely given the technical complexity of each piece (you, and whoever else is on the engineering team, seem smart but this looks like "research edge" tech along several dimensions).

so i'm curious whether you paid the development costs up front (either using your own money or FFF) or if you validated and raised in small pieces. if the latter, i'm curious how one does that for such a complex product/service.

lots of assumptions in the above - feel free to disabuse me of my ignorance.

[sjbase]

> capital injection from YC

We raised a series A in 2019 led by Green Visor (who has been excellent btw, and with us from the start)

> it seems like you've been building for ~5 years ... i'm guessing it cost quite a bit to develop

Yep, you're spot on that it's a complex product. The biggest cost has been making it feel for the user like it's not. What that boils down to is an enormous amount of iterative feedback and development w/ the industry. Between that and the regulatory process, a lot of the "cost" has been more duration than cash burn. We've kept things lean from the start in anticipation of that.

> unless you built out all of the components yourself

We've developed the tech in house, with some hands on help from our friends at Imandra mentioned in the OP. On the research piece: that's been happening in the background for many years, and we're definitely building on the shoulders of giants in the worlds of mechanism design, algorithmic game theory, and deep learning. We're lucky to have some great academic advisors involved (like Kevin Leyton-Brown since the early days) as well.

[throwmeawaysoon]

>We've developed the tech in house

i'm not often impressed but that's quite impressive. kudos to you.

i currently work on deep learning compilers (as a phd student) but i'm interested in basically all of these things (compilers, combinatorial optimization, auction theory). i know lpage expressed that you're hiring but i'm curious what roles you're hiring for (your careers page is light on details).

[lpage]

We're still a small enough team that we're more focused on talent than roles. As an example of what that means, our stack is polyglot (rust, OCaml, elixir, python), and we don't assume or require that folks have worked in any of those languages before. We invest heavily in learning and teaching.

It sounds like you have a very relevant background, so please email us if you're interested in discussing further!