I'm here with a very special guest Rory Patterson who is the chairman of datab bricks Federal Rory thank you for being here thank you for having me so you guys announced a partnership today with paler which uh I think a lot of people in the paler Community have been waiting for there's been rumors that you guys will be working together paler and data bricks just joined forces this changes everything check this out uh why did you guys decide to partner with paler today yeah this is a great opportunity for our customers and quite honestly customers have been asking about this for quite a while right I actually think when we first started down this path of having this discussion we found that customers were already trying to integrate the two platforms and this was a great opportunity to give them what they want and I think it's a a match made in heaven right I think you take the world's best data platform and you put on top of it the the company who builds the best outcomes and is closest to the business and those two things just bring customers more value so let's take it back a little bit for some people that don't know exactly what datab bricks is I know datab bricks pounder high-tech compan is kind of hard to explain most people understand pter as a ontological operating system that drives decision- making for the business what would you say data bricks is yeah datab bricks has a what we refer to as the data intelligence platform and that's you know endtoend services that inest transform store govern your data um what's really unique about data bricks is that we do all this in an open fashion right so you know Delta Lake which is an open for storage format based on paret it's your dat dat customers get to keep it they own it they can walk away from data bricks at any time and anyone else can look at the data uh then we have an integrated governance uh platform which we call Unity catalog it's like the first of its kind uh it's been in the market for several years and then on top of that you put your app so a data warehouse machine learning models notebooks gen right but it's all contained within one platform so you guys think of yourselves as kind of like an integrated ecosystem for customers to actually build more applications on that like Drive acction ual workflows for the business that Mak sense that's right and how is uh how is that consistent with pound's ontology which is kind of the heart of this partnership yeah I mean I think that customers want to be able to use that ontology and by putting more of the data into one spot right like we we believe that if you you know if paler and data bricks are sitting side by side there's actually less value that paler can bring to the customer and less value the data risks bring toomer yeah put all the data in one location and allow paler to read it apply the ontology upon reading from data bricks and they get all the value that they had before plus access to all the all the rest of the data paler and data bricks together create a force multiplier for businesses instead of treating data storage and decision-making as separate problems this partnership ensures they work as one companies now get both structured governance and real-time analytics in a unified system reducing complexity and increasing impact the end result faster smarter and more scalable decision-making across Industries what is going on right now with data why is there this massive data Revolution you guys are growing crazy fast as a company pter is growing fast as a public company I mean like why is there this insatiable demand for data intelligence yeah well I think one data volumes have been growing for years and customers realize the immediate value of their information but then on top of that there's all this context and all this you know uh unstructured data right that's that's surrounding it so they're trying to get value out of that as well not just the initial like hey you know you feed me something I understand what that is and you know it's like uh super simple it's like Algebra I think there's a lot more context that's around their data and the more they can get access to it first depend on it it has Integrity uh then the more second third fourth level of insights that they can gather from it and I assume insights are kind of what's driving the necessity for companies to even realize that they need a data platform in the first place yeah I mean it's really hard if your executive staff you know business operations is spending all their time answering the first question as opposed to like you know hey I want to know what the you know performance was of this machine or I want to know what the performance was of my business unit and it takes you x amount of time to get to that you don't have the time to then dig in and say well why wasn't it more performant why can't I improve if if it takes you forever to get to the first Insight you don't even have time in your business to get to the second or the third um and what we're finding is as data volumes increase it's not just that you're not asking the right questions it's that the data volumes you need a platform that can keep up with actually returning the results right you're not timing out you're not you know hey I can't run that search because it's so complicated I can't even get to the recommendation and that's for simple things like bi when you get to like machine learning models and more advanced things some of those searches just time out and you actually never get the algorithm you want the explosion in data isn't just about volume it's about speed and complexity companies don't just need access to their information they need real-time insights that drive decision-making paler and data bricks are solving this by making it possible to answer first order questions instantly freeing up organizations to focus on deeper strategic decisions this shift is turning data from a liability into the ultimate competitive Advantage uh AI agents everyone's talking about them it's creating a revolution do you guys see that as a Tailwind right now for datab bricks as a company for sure I mean I think that there's a massive amount of opportunity there and I think we have a unique platform because we already have so much of the Enterprise data you know we're not going after the consumer use case you know ask Claude ask chat that's not trained on Enterprise data correct datab bricks has access to an Enterprise's entire you know Cornucopia of data therefore when we ask questions of that data you know we have ai models that are actually looking inside of our products and contextualizing the information that's inside of it so it's it's not just a question about like hey what was the revenue for X company and you're searching the internet for it you're like no no what's the revenue of my company right what's the information what's the answer to this question on my data specifically we already have all that information so it gives us a big competitive Advantage you guys have a uh big government business pters obvious you've been working in the government for a long time you're the head of federal at datab bricks uh what are the synergies like for pound data bricks in the government yeah there's a ton I would say that most people think that this partnership was founded because of the public sector synergies um although there's a lot of commercial overlap as well um the opportunity here for both companies is to eliminate the perception of competition right the government customers for sure are looking at and saying like do I have to choose paler or data bricks and I think the answer is we should be able to walk into those customers and say no you should have the best of both you feel free to have both of us the real AI Revolution isn't in consumer chatbots it's an Enterprise AI datab bricks has a massive Edge by working directly with Enterprise data making AI models far more valuable for companies that need real-time contextual insights when combined with palente ability to structure and operationalize data this partnership creates a serious competitive Advantage particularly in high stakes environments like defense and government operations why do you think the media has kind of put you guys against each other over the past couple years I mean I think it's great to have competition right right so I think it also tells a story uh in that way but I also think that people don't understand the Technologies right so uh it was pretty interesting a couple months ago sham and I were like just emailing back and forth about like hey what do you think about this and like that night he hacked together a hey here's an integration and it was like 60% of it right yeah it's like 60% of it overnight was like well I think we can just do this and it had already been reading from our Unity catalog and it was like it was pretty impressive that like that quickly uh and then as we walked into more customers there was actually a DOD customer that forced the integration huh on the two of us that we were both in the they're like no no we're only going to do the demo we're only going to do it this way and it worked it was fast and so that really showed us that okay customers not only are wanting this but in some ways they're going to kind of force it either way so why not give them the best solution the best integration uh right out of the box interesting so so so that email exchange with Sham kind of led to him hacking something to to potentially show a a operational workflow and then the DD kind of forced the integration to happen and then you guys decided it just makes sense to work together yeah it was that easy well and we've gone to you know a handful of customers where we were both having discussions and the and the customer would you know at least on our side I'm not sure what's happening on the paler side the customer would be like hey just so you know I'm getting you know a lot I'm having a lot of discussions with paler over here right and it was it was it was just easier to go into that customer and say oh actually here's here's the pitch from both of us right and it didn't all the friction was removed right and they realized oh we could coexist and in in some of these cases we both had some portion of the data estate and now that customer actually gets to put put it together and you know get more value out of it why does the media always try to create rivalry where collaboration makes more sense the reality is that competition can push Innovation but the real winners are customers who Force Integrations like this if the Department of Defense one of the most data critical institutions in the world demanded data bricks and paler work together that tells you everything the future isn't about siloed platforms it's about seamless interoperability why fight over the pie when you can bake a bigger one llms and the uh revolution of llms I'm assuming pounds had the stance that the large language models will be commoditized the integration of them is what matters I would imagine you you feel the same yeah I mean I think uh I think that's probably already out there I think that the LMS are going to there's going to be a ton of value that those companies can still create around l M and we'll see what that looks like I think you know uh anthropic open AI they're still going to like they're just not going to make LMS they're going to expand off from there but I think the general purpose that we're looking at them today is has been commoditized I think you can build a $10 million llm that's pretty good or you can use llama or something like that and right why would you uh why would you pay more for something you don't have to right um and you know data rcks is unique because we can kind of look at those models and run them against the same analytic simultaneously right and then say well at this cost this performance the quality of this answer and compare them all and then allow a customer to decide okay I want to use this one or I want to use that one for this unique workload it's it's it's I think that will help also drive down prices which you know good for everybody that's right yeah uh Rory thank you for taking the time to do this last question for you 10 years from now where do you see the data AI Revolution kind of taking place in the context of data bricks oh that's a great question we're GNA have robots and Terminators getting ready I mean I I I it's interesting I always am I'm an optimist so I think that in the future there will be robots and I think you know the Gen Revolution will actually accelerate the leverage of robots autonomous everything because they're going to be able to somewhat educate themselves about the next step right um but yeah I I think the best outcome for everyone is finding the really smart things that we can use this apply this to healthcare yes let's find cures F robots let's manufacture in a way for hum there's a lot of things that we do that are super dangerous let's build some robots that do those things let's uh you know travel further go faster those things are all in our future and I think data is a big part of that hopefully data bricks will be underpinning most of that in the future I love it Rory thank you for the time appreciate it data bricks and paler now working together if llms are becoming commoditized then what truly sets a apart in AI it's not just about having a model it's about how you use it datab Brick's ability to compare different models in real time optimizing for cost performance and accuracy is a game Cher but here's where it gets even more interesting palente ontology can take that AI output and turn it into something actionable it's not enough to just generate insights you need to operationalize them apply them and turn them into real world advantages that's why this partnership is so significant it's the perfect combination of AI infrastructure and decision-making intelligence with this companies don't just get AI they get AI that actually delivers value where it matters most