enterprise AI

“And that's kind of how we became the number one enterprise AI today.”

“Up to the day, the adoption, I think, the most interesting cases that we've seen are in, like, coding auto-completion. And outside this, I don't think there are a lot of money right now to be made, made already, but many people are trying. It's a lot of POCs.”

“We're going to be on this adoption curve for enterprise AI for a very, very long time.”

“So what the challenge is, is not like some of the other technologies, a product issue, it's more of a change management security challenge.”

“Everyone is being sold A bag of goods and a dream of this sort of AI enabled workforce or Automation, top line, bottom line, and then when it comes to implementation, it's taking six, nine, 12 months, or it comes attached with a five million dollar services bu…”

“For AI to work really well and to get the level of accuracy and low hallucinogenics that you need in enterprise AI today you have to have as much access to the data and metadata and workflow as possible”

“I think, like, 90% of enterprise AI right now is almost like this vapor where, hey, we swear it works, like, look at this amazing demo where we ask, What does the CEO say about the investment? And the minute that they actually go to, you know, try to use it in…”

“On the enterprise side, I absolutely see there being all kinds of specializations because so far in whatever the last 50 years, it's not the case that there's been an equivalent of Google search.”

“When you need to sell AI to a business, you get a real signal of what works, what doesn't work. And you know, we've been using these academic benchmarks for many years. You get some signal, but it's not the same as getting this to do productive work.”

“If you're building something where the hardest part is getting adoption and workflow embedding, and you need to actually change the way a company works, then yes, forward deployed engineers are the only way to do it.”

“On the enterprise, I think things are going to keep going, and especially Cogen. I think we are not going to see a plateau in Cogen. I think that is going to get much better really, really fast.”

“Enterprise is two thirds of the ball game in AI and consumer is one third or less, which is the flip of the last time.”

“On the enterprise side, false positives matter a lot. They matter because if you imagine a future where an agent's going to make independent decisions and act on it, you have zero tolerance for false positives.”

“The real enterprise revenue is going to come from use cases that are required a lot more context.”

“I think this is going to fail because I don't think there is enough talent To do what we want to do in the enterprise. The idea makes sense to on a spreadsheet. It makes sense. Sad is smarter than me, but I, my today, my experience is it's going to fail with a…”

“We are absolutely in a land grab, like, you know, no question. Like every single company in the world wants a product like ours today. And either we get in today or it's going to be like 10 times harder to actually get in the future.”

“I really see people will own their, every single company will own their own intelligence as a must-have. It's not optional.”

“I don't think there's an ROI problem right now. I think we're in a period of exploration and experimentation where there's more tolerance, more patience To get that ROI calculation right now.”