00:00Well, it's great to have you here. The software space, the application software space has certainly been on our radar
00:04in the last year or so.
00:06Tell us about the quarter and maybe why you think possibly investors are, initially they sent the stock up, but
00:13they pulled back a little bit.
00:15But walk us through the business.
00:17Well, thank you. I'm happy to be here. And, you know, we're delighted with the quarter that we delivered.
00:23Our customers are clearly excited about the offerings that we have.
00:28As you pointed out, we exceeded our expectations, both on top line and bottom line.
00:35We raised guidance for the full year. You know, investors in the markets do what they do.
00:39But from our perspective, our business is doing well and we continue to be confident about where it's going.
00:46And one of the big drivers for actually for any software company that is doing better today is around AI.
00:52And so we're seeing significant interest in our offerings to help our businesses get their arms around controlling and giving
01:02context to AI so they can get better outcomes and get better value.
01:06You argue that's a driver of your business, but I think it's fair to say that a lot of software
01:11companies have been caught up in what analysts are referring to as the so-called SaaSpocalypse.
01:15And the concern that some of those companies that are offered on a per-seat basis or software as a
01:22service companies that are subscription services might be replaced by companies that are created or apps that are created or
01:30services that are created through people using AI to code.
01:34How would you respond to that and your moat making sure that you can still succeed in a world of
01:41Vibe Coding?
01:42Oh, absolutely. So, you know, what we offer is very different than the characteristics that you shared, which is what
01:49makes us excited about what AI can do for our business.
01:52So when you think about AI, right, when you think about even agents built with AI and AI agents running
02:02on top of information, fundamentally, what they need is context.
02:07Because without context, they have no way of getting the right answers and the right outcomes for a business.
02:12They can't be reliable. They hallucinate, et cetera.
02:16So what happens is businesses say, oh, let me take all my data, let me take all my content, let
02:21me take all my documents that I have and try to give it to AI.
02:25And then you end up with tokenomics issues, right?
02:28You're just beginning to see that today, that as these AI companies are finally sort of truly passing the costs
02:36along to the customer of the AI infrastructure,
02:40the tokenomics have gone through the roof and expenses are going through the roof.
02:43So you need to control that as well.
02:45Yeah, I was talking to a friend about this over the weekend.
02:47He has a group subscription to one of these LLMs.
02:50Yeah.
02:51And he's talking about, okay, well, he can burn through the token allotment, you know, in just a couple hours
02:57in a given period of time, you know, or it'll, you know, he can buy more, it'll reset.
03:01But they really have to allocate as, you know, as his enterprise version of this software, he really has to
03:07allocate his token usage.
03:09So, Tim, you're absolutely correct.
03:10And so the question is, that's one way of doing it, but then you can't have an agent that works
03:14like a human being 24 by 7 or more than a human being.
03:17That's the promise of AI, if you have to then control the tokens it can use.
03:21So what we do and what our products do is provide that context to AI in a much more effective
03:30and efficient way.
03:31So we have a data platform business that can aggregate all data, structured and unstructured data, content, as well as,
03:38you know, systems of record data, bring it together, do analysis on it, and provide it in a way that
03:45it's AI ready, dramatically reducing the amount of tokens needed to process that and to answer questions for agents to
03:52run, etc.
03:53In addition to that, we also have other product offerings, what we call around our infrastructure management that help manage
04:01the AI infrastructure that is coming around and make sure that it is secure and reliable and consistent.
04:07So when you think about it, our business is very different than the business of, you know, seed-based applications
04:14and those kind of things.
04:15Our products are not seed-based.
04:17They are based on things like data volume and data consumption, which, as I'm sure you can imagine, is only
04:24growing.
04:25Kind of like having a CFO over your shoulder with every little task that you do and kind of determining.
04:31But, I mean, help me understand because I feel like there's a lot of companies out there, you know, when
04:37we talk about AI.
04:38Is that kind of what it is that, you know, give me an idea or give us an example of
04:43a company that you work with and exactly what you're doing for them?
04:46Yeah, so I'll give you an example, right?
04:47A large organization, one of the, you know, top four consulting firms in the world, has terabytes of data, terabytes
04:56of documents, and they need to use those to address business decisions, business inquiries, analysis for customers, et cetera.
05:06Now, if you upload it all to AI, the context window for AI becomes extremely large and the amount of
05:12tokens consumed becomes ginormous.
05:14Instead, what they do is they use our platform, our platform analyzes that, figures out which documents are truly relevant
05:24for what type of work.
05:25It reduces the actual documents that need to be provided from, let's say, millions of pages down to a few
05:32hundred pages.
05:32And now the amount of tokens will be used is, you know, one thousand, right, or even smaller.
05:38And that completely changes the equation, for example, on the cost, while at the same time, it actually improves accuracy
05:46because the AI doesn't get all the other garbage, 999,000 pages of documents that it really gets confused on.
05:55Hey, Yogesh, before we let you go, how is your team using it and how have you instructed your team
06:00to use AI internally?
06:01Oh, internally, we're using it extensively.
06:04Our development teams are all building products using AI.
06:06Our operations team are using AI to do their work on a day-to-day basis across the board.
06:13We're using it to interact with our customers.
06:15We're using it for all kinds of things, including truly helping sales folks, helping engineering folks, helping finance folks.
06:24Interesting.
06:25It has been a transformational journey over the last three years.
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