Palenteer outward results, boosting its revenue guidance for the year to arrange of two point seventy four billion to two point seven five billion, ahead of estimates, with AI demand also helping Palenteer boost its profit outlook. There's been growth in business with government and in commercial customers. AIP Palenteers Artificial intelligence platform and other products has quote transformed the business in a level more than a year. CTO Sean Sanka joins us to discuss. Sean on the call this
transformation that doctor cart was talking about. I've been to a few AIP cons, but as CTO, you're working on it. I think just explain the basics of that. What's changed within Palenteer from a technology perspective and in the domain of artificial intelligence.
Well, what you really see in the market is this massive bottleneck between prototype being and production, and that happens to be where AIP is most differentiated. And that differentiation is built on a decade of deep technical investments, investments like the ontology, the OSDK, the security and business primitives that we built throughout the platforms like functions, actions, automations in this pipeline that we have that's really focused on addressing that. And I think what's changed.
As you've been to these AIP.
Cons is that the market now understands how severe that bubblenek is.
I think your last guest was just talking about that.
Where is so easy to build a charismatic AI prototype. That's about the amount of effort of building a PowerPoint slide, But it's also that amount of utility. And unlike traditional deterministic software, this kind of powerful stochastic genie that is LMS, it requires a lot more work to get to production, maybe ten to one hundred times as much work, and that requires the tool chain that we've assembled with AIP.
I've had a few conversations with your CI his cop about his frustration with the PowerPoint deck versus the reality of shipping products.
We'll put that to one side for now.
Show. There was a heavy emphasis on working with the military in the written materials and on the call. Could you just get the basics of what you'll work with the military looks like present day.
Look In the commercial world, you call it a value chain from the hand of your supplier to the hand of your customer. In the military, it's about a kill chain from censor to shooter. But really at the most abstract level, it's the same thing. We're trying to enable our war fighters to have information, dominance and decision advantage. How can I see you know, to quote Sun Sue, if you know your enemy and you know yourself, you're going to win, and so you know, how can I
see everything there is to know about the threat? How can I understand everything I have to combat and deter any aggression from those threats? And when you look at the geopolitical landscape right now, it could not be more dangerous. Everything that's going on in Eastern Europe, the massive tensions that are that exist in the Middle East, and the ongoing issues that we have and deturing aggression in the Pacific.
Beyond the importance of data, where does plant to sit in the defense ecosystem or even the defense supply chain. Are you sort of very closely aligned with hardware makers, the aerospace community or it is the MOLTI more focused on you just going direct to different arms of the defense base with government.
Yeah, we're touching all of it. One of the things I'm most excited about. I've been calling the first Breakfast as an antidote to the nineteen ninety three last Supper that led to the consolidation of our defense industrial base, where it went from fifty one primes down to five, because we forget that at the dawn of World War Two, we didn't have a defense industrial base.
We had an American industrial base.
Chrysler made missiles, General mills, this Serial company made inertial guidance systems. And so we have this moment right now in defense tech where one hundred billion dollars or more of capital has been deployed, a boluss of founders have shown up. There's a lot of creativity, a lot of energy as a company that's kind of been pathfinding over
twenty years. Not only have we developed our software that gives these warfighters unique advantage like the Maven contract that CDO just recently awarded for nearly half a billion dollars, but really this software infrastructure that's required to deliver modern American software to the battlefield in air gapped environments at speed, at pace, well.
Ahead of the threats of twenty twenty seven.
So we've been working very closely with both traditional primes, integrating our software to their hardware, helping them actually with production. If you think about the fifty percent of our business that's commercial oriented. How do we build jet engines and satellites faster, better, cheaper?
In addition to the new entrants who need to achieve.
Scale and time, value of money is everything for them.
Whenever we have an executive on this program, I always go to our audience and say, you know, what is it that you want to know from? In this case, Palenteer, I would say most of the questions were about warp speed, very basic ones. Why now with warp speed and the obstacles to rolling it out making it sort of more readily available, pervasive out their shop.
Yeah, that's great.
I'm so excited about Warpspeed is what I'm spending all of my time on and really shaping the R and D roadmap around. Speed is our modern American operating system for manufacturing. And the reason why now, you know, for the better part of twenty years we have helped traditional manufacturers build planes, trains, automobiles, and ships.
But most of those folks are.
Stuck in a legacy mode of how they're operating, and you're able to help here or there. But what's unique about the reindustrialization movement that's happening right now in America is that these these founders, they're alumni of Palenteer, of Tesla, of SpaceX, and they understand that the traditional erp plm PLC software doesn't really work. That most of these successful companies have had to build their own software and that
is really an unaffordable journey. So that there's this massive opportunity to take the power of AIP and the historical experiences we have throughout the value chain of production to help our customers bend their atoms better with bits.
I have you know, Ceto, I kind of have some quick fire questions that I've never been able to answer about Palenteer in the first sUAS and since AIP and warp speed over the year. What's the kind of key foundational model LLLM that you've been building on top of. I know you partner as well as sort of think in house about the model or foundation level, but that's a question that comes up quite a lot. Who are you building on top of and working with?
Well, I think all the value is really going to create at the application layer, and what we've seen in production is that you actually need a menagerie of models and you you know, if you think about the most expensive frontier model out there right now, it's a thousand times more expensive than the cheapest open source model for ten percent more ELO ten percent more IQ. As a rough proxy, that's not a compelling price performance trade off. You already see that the first versions of GPT four
have been sunset. You know, we need to think about this problem as Okay, what is the infrastructure I need to make I'm turning my software into something that is now stochastic.
It's not deterministic anymore.
Computer scientists that we have trained, they are all used to writing deterministic code.
You know.
This is this harkens more to how we think about the transition from analog circuits to digital circuits, the sort of error correction you need, the sort of infrastructure you need to think about having so that you can have the abstraction to.
Think about these things as being digital. That's where I think the colony is going to be go ahead. Sorry, And so we're very.
Focused on helping our customers get the right models for the right use cases, auto evaluate that at automatically generate iterations on the prompts that get them there. And part of our theory is that really prompts are for developers, chat is a dead end. We're guiding our customers through this journey here. They get there pretty quickly to realize that we should be thinking of llm's as a new type of run time the way I might write a Python function.
Well, okay, I'm going to write an LEM function too.
Sean, for the commercial half of the business, is there a specific Hyperscale cloud platform or partner that you work with to support its growth.
We're working with all of them. We have deep and very valuable relationships there. So we're very happy with that.
This last year has been about a IP and growth. What's the next twelve months like for Palenter Schaump.
Well, I think it's really about deepening the investments that we have with AIP that are dressing this bottleneck between prototyping and production. You know, if you look at David Kahn at Sequoia's article on the six hundred billion dollar whole and revenue.
I think this is where the whole is.
This is the bottleneck in the market is the most important problem to solve, and the folks who solve at first, and I think we're in the pole position there, have the opportunity to take the entire market.
Sham Sangkas, CTO of Palenteer, it's great to have you back on Bloomberg Technology.
Thank you so much,