Akhil Verghese

Honestly, meanderingly, if that's even a word, pretty much sums it up.

I started my first machine learning projects when I was working at IBM, even though that wasn't my primary role.

And then later on, I was with a bunch of people in San Francisco and we tried to co-found a company there.

was an intelligent assistant for your office.

Unfortunately, this was before the transformer paper and before large language models.

So it was running on a technique called LSTMs and recurrent neural networks.

And they weren't really able to keep context over large document sizes and things like that.

So it didn't really work out that well.

But

Through my time at Google, I started working towards the tail end of it on applications of AI on more complicated customer service problems.

So not your typical like, hey, where's my order kind of thing, but actually investigating audit logs, providing conclusions, spotting security leaks, things that it was really critical not to be wrong on.

And obviously I was trying to adopt best practices from what I could find online.

And I just found that they weren't working that well.

And basically I identified that

we almost need to rewrite the book on how we approach software engineering when it comes to building systems for these very non-deterministic things to function well in, while still preserving the elements that make them special, which is honestly the non-determinism and the fact that they're not predictable as part of, it's a feature, it's not a bug, but at the same time for enterprise systems, you need to build around that.

And that's kind of what led to Krasmo.

It really wasn't well planned or anything.

It was just something that kind of came out of that

other companies started reaching out and asking if I could help out.

I got Google's permission to do that and just moonlighted for a while along with my co-founder.