Thank you for the folks that have, jumped in. We've still got more people coming into the room, which is great because we've got a little bit of an introduction to get us started. I guess administratively, inside of your webinar interface, you'll see the ability to put anything you want into the chat. There's also a Q and A. If you have any questions for myself or for our presenter panelist, Adrian Harders, just chuck it into either one of those. And we'll probably have five to ten minutes just depending on how interesting and how long our conversation goes. I'll try to make sure we carve out some time. But if we get really into some cool stuff, I might lose track of it. But the goal is to give you guys some time to ask those questions. So just chuck those in as you have them throughout, and we will circle back around and answer as many as we can. So again, that's the chat or the the q and a button. I guess the other thing to mention just from a technical bit, just so that my marketing people are happy with me. We do these webinars every month. So if you want to attend our next one, it might be a customer story like we're doing today. It might be a deep dive on a particular, vendor technology. Like we just did a three part series in Informatica and Snowflake before that and other cool things that we've got planned. Or they might be something from a best practices standpoint, like how to do data governance, data strategy, whatever. Go to interworks dot com slash events and you'll see all of the global webinars as well as a filter for the Australia or Asia Pacific ones. So we certainly look forward to seeing you on future events. So let's get started. So today we're going to be talking to Henning Harders and how they use AI to compete on a global scale. We'll talk a little bit more about who they are and who Adrian is. I'm Robert Curtis. I'm the managing director for Interworks looking after Asia Pacific. I've first started with Interworks I think in two thousand. So I've been with the company for a very long time. And I've gotten to work with many of you on this call. I see a lot of you as familiar faces so it's great to see you again as well. What do we do? We do well simply strategy solutions and support for data. So we help you figure out where you want to go, how to build those things that you need to make yourself successful, then how to support and expand and continue your journey, whether that is supporting applications, your data, or the communities that are leveraging those solutions. A little bit more about us. Unlike other SIs, we've actually been in this business almost thirty years. So we were founded in nineteen ninety six. We are a sort of boutique niche consultancy, but we're global. We've got around three hundred or so Interworks people around the world. I look after our team in Asia Pacific. For a team that size is quite incredible that we've got something like I think seventy seven of the Fortune one hundred now are into works customers. So we get to work with the most complex, most interesting data sets around the world across every vertical that you can imagine. I mentioned it to works dot com already. Have a blog focused on data and analytics and governance and AI. Get somewhere around three point five to four million page views per year. A lot of times when I meet people, they recognize me from the blog. And we have thousands of clients that already mentioned of every industry vertical you can imagine, public sector, private supply chain, health, manufacturing, you name it. One of the we have a lot of things that we've sort of collected on our trophy cabinet over the years. But one of the ones we're the most proud of is, I think in twenty nineteen Forbes made a list globally of twenty five small giants, just smaller companies that punch way above their weight and have a massive impact on the industry that they're a part of. And we were listed into works was listed as a Forbes small giant. So that was a great honor for us, one that we're quite proud of. We get to work with a lot of clients. Obviously, we're going to be talking one today with hitting harder's and we get to work with a lot of great partners. We love Snowflake. That is probably our central partnership. And so we try to figure out how do we leverage all of the great stuff in the Snowflake platform for maximum effect? That might be your data pipelines, your analytics, your data science, your governance, etc. So without further ado, let's get started. So it is my pleasure to introduce you to Adrian Harters. Adrian Harters is a friend and customer for several years. He is the innovations and productivity manager at Hitting Harters. He's got about fifteen years of logistics and shipping experience. He's worked here in Australia. He's gone over to Germany. Wealth of industry experience, and with a key focus on how Henning Harders can best leverage technology and their data and innovative solutions like AI to drive more value so that they can compete with the big global companies in this space, as well as maintain, a real focus on their, core principles and values as a family and business. Welcome Adrian. Adrian, you can I I'll stop screen sharing and we can turn on our video so people can see our faces? Hopefully I'm stopping the screen share. Awesome. So, Adrian, why don't you just give us a little bit of an intro to yourself and maybe an overview of what Hinting Harders does and then we can dig in a little bit deeper from there? Yep, one hundred percent. Really quick synopsis about what, Henning Harders is and who we are. We're a third generation family business, operating in the freight and logistics space. So if you think of us as like a travel agent for freight, we can do it all. So air freight, sea freight, trucking, rail, domestic, customs, quarantine, all those really complicated things about getting goods moved around the world, that's what we do. We have offices in Australia and New Zealand, two warehouses, one in Sydney and one in Melbourne. It was founded by my grandfather Henning in nineteen eighty four. So we pip you a little bit in the number of years that we've been running, but only just but you pip us, with the number of staff we have, we have about one hundred and forty people across Australia and New Zealand. It's a proper family affair. Henning's no longer with us, but it's run by my dad and I work with my brother and my uncle. So it's a full on family venture. And interestingly, we have a non family CEO as well, which kind of keeps the family situation a little bit easier, not having any reporting lines directly to family members. Who I am? Yes, as everyone knows Adrian Hart is my name. My role and venture into the business really started during school holidays. We're very much an inclusive family business, not everyone's like that. So that just meant, you know, every school holidays coming into the business, learning what it's like to be a freight forwarder in business, a family person in business, all of these things. Yeah, we were encouraged all throughout our lives to to pursue our passions. And I deviated from my logistics path, started my science and list science and engineering degree for a year, decided that was not for me. And then went into the family business, worked full time ever since, studied my degree in supply chain and business. Once I finished that all off, I moved to Germany for two years, which was another big part of, what the family is all about getting family members out of the family business, making sure we don't become an echo chamber. We wet our teeth elsewhere. I went to logistics route. So I went to a very large state owned publicly traded logistics company in Germany, learnt how the other side of it all works that corporate life. And that is where I really got my passion for business processes, IT technology data and what the potential is at a scale that is not just incomprehensible for a family business in Australia, but honestly for a country like Australia. The logistics in Germany and in Europe is just unbelievable. So that was fantastic. After my two years in early twenty nineteen, I came home. I started then as the innovations and productivity manager focusing on process design and modernization of workflow and processes. Interestingly enough, one of the catalysts into our data journey was we suffered a cyber attack in twenty nineteen. And that's how IT and cybersecurity ended up being reporting into the innovations channel away from the CFO channel. Since then, the sky has been the limit regarding what we can do with our data and what we can do now. Awesome. I think it's interesting being a third generation family owned company and you being a member of that family, your last name is on the door. How does that Obviously, got a chance to for another company in which you were one of many and probably not as emotionally invested in terms of their long term success. How does being a part of a family company change the way you think about the work that you're doing or the money that you're spending to make these projects work? It must change the calculus in terms of how everything is. One hundred percent. It is a different mentality coming into it all. There's a lot of places to hide in corporate land and there's a lot of places to hide expenses and stuff like that. So we really focus on value investment. So we need to demonstrate that the value that we are creating or the return is actually realized by the end of the project and that we can redeploy that return value into it as well. But we also have a much stronger, I guess, sort of connection to the values about we always question what it is that we're trying to achieve. We don't wanna deviate away from one, the business's large goal, which is to be a you know, provide the best supply chain, personalized supply chain solution to our customers, but also the family's goal, which is to be a multi generational family business, whatever that looks like down the line. We're in a very fluid time at the moment. It's in like the amount of progress it's being made in technology is just unbelievable. But yeah, it really puts it into perspective when you actually hold the fourth generation in your arms for the first time and you see like, okay, we need to make sure that we do things sustainably and we keep going and we're going to be here for the long haul because yeah, just smitten with the next generation coming along and just gives you a lot of excitement and a lot of passion about what we can do. That's awesome. So let's talk a little bit about your journey as the innovations manager. So you came back after working in Germany. What did hitting harder look like from a technology landscape when you came back with that role? So we've always kind of been a maximizer or utilizer of the system that we have, like our main ERP system. And I should just say that's mainly because we as a business don't offshore any of our processes. It's quite prevalent in our industry to offshore processes to the likes of the Philippines and India. We don't think that's the way to go regarding like the value of what can be provided in the industry. It's kind of shortsighted in our opinion. There is already a shortage of freight and logistics people. So I came back into the business and there'd been a lot of progress. We were running paperless systems. So a lot of data was going into our ERP where it would be reported on. But it was ultimately trapped in a a lot of ways into a very regimented structured way that, you know, we couldn't get the full value out of it. We could provide basic reporting and and things like that too. But it just we weren't maximizing our ability to it as well. I guess the other side of it is my main remit when I first came on board was to look at the like how our staff interact with system itself and the processes. So it was quite, know, narrow the scope when I first returned. And from there, we we could immediately get some productivity gains by like, you know, removing some spurious tasks that could be done by the system itself. But, yeah, it was only really when the cyber attack happened in twenty nineteen and and IT started reporting into me during the recovery that we could, you know, move on to what the future looked like for our hosting environment. We moved away from like, you know, co located servers to private cloud instances and that initially gave us a big bump in capability in what we can do and now this is just the next iteration which is Snowflake data warehousing and all the fantastic world of AI which again is just mind boggling at the moment the capacity of that. That's great. So let's talk about when you made the decision or when you were making the decision on the next data platform and obviously Snowflake, huge name, massive IPO captured the mindshare of the global business community as well as Australia. What was your decision making process? Why Snowflake? What was it that sort of led you in that direction? We were evaluating quite a few platforms at the time. We'd been engaged with you. We'd already discussed it. We ran through quite a number of the other possibilities out there and you kind of pointed us being not quite mature on our data journey. The simplicity of Snowflake made it a lot easier and the accessibility having prior SQL experience within the business made it enticing to move in that direction. But then we actually funnily enough to lead into choosing Snowflake kind of backwards. Do you wanna talk about the Document AI journey, Robert? Or do Yeah. Go for it. Yeah. We went into the Snowflake offices, you know, to run through what it looks like and what it would look like for us to be a customer of like a data warehouse customer of Snowflakes. And this was right around summit time and Document AI was in private preview and all this stuff. And they they had like one slide in their slide deck around like what their future, AI offerings would be like. And that really piqued our interests because we actually do or we did quite a lot of robotic process automation of documentation. So taking unstructured data out of documents, feeding it into the system through robotic process automation. And we just come up against like this decision inflection point whether we were going to be able to scale the RPA processes to what we wanted to achieve in that way and would it become too you know administratively burdensome to continue to build and develop these RPA pipelines. So yeah, just so happened that Document AI was in private preview. We ended up talking seventy five percent eighty five percent of the meeting about Document AI and the potential of that in so that was that initial meeting was in April twenty twenty four. In May twenty twenty four, the Document AI entered public preview. So we were able to get our hands on it and that's when we got our hands on it and we said this is the direction we wanna go in. Yeah, we engaged you to help us do the Snowflake startup or the quick start so that we didn't have to start from a blank canvas. We had everything administered because one of the biggest, I guess, scary moments around these sorts of platforms as a service is how much the cost is gonna be and cost administration and cost, you know, making sure that we don't go ballistic. Because you obviously hear massive stories about my first month I spent, you know, huge amounts of money because I forgot to turn a warehouse off or something like that. If you can do that, if you can have your platform pre configured so that, you know, the overflows aren't so bad, then it's a no brainer. So yeah, in May we did the quick start and in June, July we started processing documents through Snowflake Document AI. Yet to be confirmed by my account manager, but I believe we are one of the first, if not the first to put a Document AI pipeline in production. And yeah, we've gone from three thousand no touch document imports via RPA now up to ten thousand plus a month, no touch documents being processed through Snowflake and it's just fantastic. So let me just wind back a look because I remember talking to you about this problem that you had, all these cargo manifests and everything coming in and you you had actually tried, correct me if I'm wrong, a couple other sort of image to data scanning solutions. And so when I mentioned, when we were talking about Document AI, I think there was a little bit of cynicism like, well, we've actually tried three or four of these and none of them can you kind of without mentioning names, kind of walk through what your experience was in terms of experimenting and not finding success? Yeah, absolutely. So were some industry specific software platforms that had come out directly related to the sort of extraction of unstructured data from documents and pushing it into our system everything like that in two way feeds so you can see it all. Although ultimately they all kind of fell over because it was a lot of the times software engineers or machine learning or data engineers telling us how we should be doing the jobs which is kind of a little bit backwards. We really required some of the information that was on those documents. It was a high priority to us and they just wouldn't get around to doing it because it wasn't something that was in importance to the product so to speak. So having it in a platform where we could be the masters of our own destiny in a lot of ways was really that's what took us to the next level. Now we can say that the sky's the limit if we can think of it, we can basically do it. So the other side of moving away from robotic process automation I should say as well is that didn't we didn't end up with a nice clean data set to run our analytics on at the tail end of RPA. Yeah, the document would end up in the system and the workflows would run off that document But we never, you know, went into diet like deep diving into the contents of the document in a structured way. So having Document AI then place everything really nicely and neatly into a table that we can now query and run analytics on has has just been a tertiary benefit out of this as well. I wanna go broader into some of the other things you've discovered about Snowflake, but let's finish this Document AI. So how much time do you think you guys were spending manually looking after these documents? So if three thousand were making it through and there's thousands that weren't, how much time were you guys spending per day per week, whatever the number is, getting those documents in manually? Yeah. We conservatively, we budgeted for like a dollar a minute a document, sorry. So you calculate that up into like seven thousand minutes a month in in that gap of where where we are, that's a huge amount of time saved where a staff member doesn't need to search for that document anymore. It just appears in the job. They can just, you know, click send that document to a trucker or a shipping line or to the customer. Once everything has been verified, there are still manual checks. So it's like a it is very much like an AI assistant in in that way. But we're just getting started because we're just using it quite simply to place the document into our system. We're extracting all this information, preparing it, getting it ready so that we can then place the actual information into the fields and start to build a little bit more logic upon that too. Something that wouldn't have been possible with robotic process automation is now the sky's the limit once again. That's awesome. So there's obviously some efficiency gains in that we have these people doing a task that's now been automated, but not only are you now saving time and money reducing that effort, but because the data is more useful and more accessible and more extensible, you're actually able to use the solution to go and drive further innovation and then look for further opportunities for efficiency and gains. And something that we hadn't considered or that we were concerned about initially when when it comes about the framing of automating processes within a within a company is all about how you frame it up to staff members and stuff like that too. It's actually interesting that these were processes that our staff came to us about asking like, hey, can we automate this process? Because no one likes living in an inbox, dragging and dropping documents in, you know, double clicking everything, confirming details. That's that's not something that people like to do. It's not fulfilling. They're incredibly busy with their with their other work like booking freight and making sure that, you know, we don't like, also very important to remember that we are in a strict regulatory framework industry too. So if we miss a document and something doesn't get quarantined, for example, that's that's one, a penalty on us. But two, also the risk to Australian agricultural is is incredibly high and we take that responsibility high too. So our compliance has increased, staff happiness is increased because they don't need to live in this, you know, inbox world anymore. They can just get back to to doing their actual job. It also probably means you have less dependency on people personally manning or observing these processes because, you know, like, if you've got thousands of documents that come in that are time sensitive, somebody always has to be there to make sure so that might limit some ability for people to do other things, take PTO, do whatever. A hundred percent and the timeliness of it. Mean, like the that process is running twenty four seven. Like, you can't expect a person to run twenty four seven. You can't we don't run shifts. We run, you your standard nine to five. Anything that deviates out as outside of those times, and I should say nine to five across all of the time zones as well. So, you know, we have extended trading hours from Wellington all the way to Perth, but still you have a very large gap of about, you know, twelve hours at least where there's no one manning those keyboards and this is doing it and it's it's able to produce alerts. It's it's been really, really good. So your your reporting is stronger. The ideas that come from having better data, is creating, more innovation. Obviously, you've got efficiency gains. In terms of actually standing up Snowflake and then getting Document AI going, how long did that take? That took less than a month to get all of that going. That was very much in part of having the administration of the kickstart done. So it was like very much a templated. We've done this before. That's from the interwork side. But now like we managed to do all of the development for our Document AI initial use case I should say like that was our first data pipeline, document pipeline within the thirty day trial of our enterprise account. So like we still had Snowflake credits left over at the end of that process. It's we've also I should say we're incredibly fortunate. We had the Azure environment already set up. So we had our blog storage ready to go. We understood the administration of, you know, granting access to Snowflake to the stages, the external stages in Azure for the staging of the documents and the administration around that. But yeah, it's it's the barrier is incredibly low for this sort of technology, I feel. Yeah, I mean, that's amazing. Four weeks to set up a platform, then drop in a containerized AI production ready solution that then opens up the door to save hundreds of hours of years in terms of man hours. That's amazing. This is a little bit less technical, but I think it's super relevant. You mentioned at the start of this family organization, very cost sensitive because again, you guys are competing with very large players and so you have to be super, efficient on how you invest the money that you've got to build these solutions. How did you go about convincing, your leadership, dad in a way, and your other the other stakeholders to invest in something that probably is a bit on the uncomfortable side. Okay, AI data, what is this thing? How is it actually going to help us? How did you get that stakeholder engagement and buy in? It was a very we went a very circumvented way around that as well. So it was actually part of our robotic process automation initially where that was our first real dip of the toe into a technical solution for for a business process. We're like the development for that the the company didn't want to field that investment. So in a discussion between Julian and I, my brother, we believe that there was a lot of credence and a lot of credibility to this idea, and we were willing to, you know, put our hands in our own pockets in a lot of ways. Like, not in a lot of ways. We did exactly that. We paid for the development of this product out of pocket and then we offered it as a service to Henning Harders initially. Now that it is demonstrated, it it hindsight's always twenty twenty. It could have been money that we've we've thrown away. But now it meant that we got those runs on the boards and, you know, I guess there's always this perception as the next generation coming along that you're always gonna be that little boy to to your dad or to your mom or something like that. You're gonna be that baby in their eyes. So like, what would they know? But now now once we've proved the the veracity and the concepts of this and we can demonstrate it and show other use cases from Snowflake to senior leadership, they're on board now because people are now you know, they're begging for more processes to be automated in a lot of ways and to make their lives easier. Because again, it's a lot of digging for information when they just wanna service their shipments as well as possible. So, yeah, a little bit it's definitely not the use case or the way to get most investment going, but you could almost think of it as like we went into a little startup startup mode, did it really lean, learnt all about it, and then sold into the business that way around. No, that's great. It's just a testament in terms of the vision that you and Julian what's Julian's role just for everyone listening? He is the commercial manager. So he looks after a lot of the finance side whereas I went into the industry straight out of school. Julian went into the finance world and went that way around, you know, worked through KPMG, became a chartered accountant, you know, not as interesting as I am, hence why I'm doing the webinar. And I got to have a little jab in front of all these people now too. So that's immortalized. Let me just see if Julian's on here. Okay. He's gonna get the recording then. Yeah. Exactly. He's gonna sniff it. Julian does look like the finance guy. You do look like the IT guy. I'll just throw that out there. But what what I see a lot of times, because I get to work with organizations as they're making these decisions quite a bit, there is a push pull dynamic that you guys perfectly sort of sit on. There's a data breach in twenty nineteen, which is we cannot stay where we are because there's risks. So that's the push of towards a solution. And then you guys doing this POC is the pool. There's value over here. Come here. So most of the time when you have those dynamics, that's the best way to get executive leadership to do it. We can't stay here, but if we go over here, there's more value. So you guys you guys did that perfectly. So anyone that's on board, selling value with the the solving risk is the best way to get executive buy in. I guess the other side is sorry, just add one second that we now identify data as a key enabler to just about everything that the business wants to achieve. Like that that proved that technology and data is is a pillar upon which to build the capacity for the rest of the team. You can't look at it as like we wanna achieve our strategic goals and data be a separate strategic goal. It is central to what it is that we need to achieve going forward to hit our long term goals. I think it's a perfect segue into the next thing I wanna talk about. As a logistics supply chain freight shipping, I'm not gonna say it exactly how you said it, company, you are very, very data rich. And so data is obviously going to be a key asset that you've got. So you've had success with Document AI and some of that automation. What are some of the other big initiatives that you're sort of thinking about over the next two to three years is more AI solutions make it into Snowflake, Cortex, Cortex search, you know, sort of the SQL copilot. What are some of the other things that you're thinking about might be big winners for you? The issue is that it is progressing so incredibly quickly that we're just trying to keep up with the new enhancements that are coming out. So it's wild to me that we're only talking about a year ago, we did this Document AI thing and it was novel and it was a brand new thing. And a year later, we're now talking about if anyone is technical, check out Cortex AI SQL. It just came out at Snowflake Summit. Mind blowing incredible things coming out of Snowflake at the moment. And it's just where we need to remain at the moment as a family business is we need to keep our agility and like our ability to be nimble and adopt these technologies as they come along. I shouldn't say adopt, I should say evaluate. Because just like the blockchain of years past, not every technology is going to totally revolutionize the world. But you always need to evaluate and understand what it is. Blockchain absolutely had the like has and had the potential to revolutionize a lot of processes. But this AI, systems running at the moment, it just seems like everything that is touched is is turning to gold at the moment. And it comes from a good data structure and it like understanding how we can utilize the data that we've generated over thirty eight years of operating and what insights we can gain out of that. That's where we're going now. But yeah, long term is five years. I'm just trying to keep hold of the fact that we're applying these new tools that just got released a couple of months ago. So when you are looking at the use cases that's either you guys as the IT folks come up with or members of your business, so like it'd be great if we could solve this. What's your calculus, your methodology and saying, okay, that's one that we can solve that's going to have high value. Or maybe this one's going to take a lot of effort, but maybe not as much value. What's your decisioning process on selecting a use case? A lot of the times, it comes down to one, is it a customer desire? And is it something that we can offer to other customers? That's something novel that hasn't been done before. Then it comes down to understanding, like, what business processes and how much time is spent on these business processes to get the most amount of return on actual, you know, finger time on keyboards. Because, yeah, like having the one hundred and forty staff in Australia and New Zealand and having that choice not to, you know, offshore to the Philippines and to India and the like, It was a benefit to ours during COVID, you know, not having to deal with the lockdowns or anything like that that happened over there that slowed a lot of businesses down. But it's also like these are incredibly intelligent people that we have working here. We need to make sure that we can utilize their intelligence or they will get bored and and move on to other things. So we need to give people space to grow. And technology is an enabler. It's not a replacer in my view. And at least that's the view that we're going into it going forward to. I love that you said that. I've been doing a fair bit of research and writing articles and presenting about AI readiness. And it is strategy, data governance and people. And you just touched on the point there about how AI intersects with people. One, it is empowering them to understand how best to use AI solutions and giving them the skills prompt engineering, etcetera, etcetera. Two, there's the ethical part of it. So we are augmenting these roles so that they can do more and we can get to the things we've always dreamed about, but manual processes slow it down. Let me ask you some broader questions and sort of just let you see, give you a chance to sort of philosophize a little bit. In thinking about your journey to now, and obviously big things that you want to accomplish on the horizon, what sort of advice would you give to other folks that are maybe standing at the threshold of taking a big step into AI, or maybe getting into, you know, moving into cloud based data onto a platform like Snowflake. What advice would you give them? What warnings would you give in terms of think about these things before you get started? I think upon reflection of my own journey, into this kind of unknown realm, it was you can spend so much time analyzing everything to the nth degree. And I guess I'm in a very fortunate position where I am given quite a bit of freedom around where I can go and where I can investigate. And we obviously have to keep our regulatory frameworks in mind. So like our data sovereignty and everything like that. So that was a non negotiable. The data must remain in Australia, all that sort of stuff too. But you can try a lot of these tools and not provide them the full data and not provide them everything relatively easily and simply. So if you can just, know, get your hands on these sorts of tools, start up a free account, go through some of the worksheets, just in engross yourself into what the capacity of some of these products are. And then ultimately find what you are passionate about. And I I don't know if you can hear it, but this is like this is my passion. When I go home, it's sad, but I think about data and what we can do as a family business to, you know, remain relevant and utilize the data. We acknowledge that we are a very small cog in a very, very large supply chain machine like that encompasses the whole world. So whatever we can do to accelerate digital uptake in the industry is ultimately going to be good for the industry. It's going to be good for us. That's our vision. That's the passion. If you can harness a little bit of passion into what you want to achieve, then honestly, the sky's the limit and you'll have so much fun doing it too. The the user groups get involved in user groups as well. If you ever do take up Snowflake as a as a platform, the Snowflake technical user groups, It's a it's a daunting name, technical user group. I'm not that technical. Like, I can hold my own a little bit, but you can go there. They're incredibly welcoming. They're nice people. Just go out and meet, you know, other passionate data people too, and you'll end up having massive chats and just meeting great, great friends now, throughout the entire process. So I guess just make the most of the situation that you have, which is, yeah, we're at the precipice of this whole new technological evolution. This stuff didn't exist a year, two years ago. Data warehousing did absolutely, but where we are right now in the data journey and the AI journey, it didn't exist. So everyone's kind of learning on their own feet too and everyone's happy to share, would say. Not everyone, most people. Yeah. We've got a couple of snowflake people on the chat and I'm sure they're really happy with you making the endorsement for the user groups. I think the other thing that's really useful yes, you can go there and learn about technical stuff and you can road maps and talk to snow, Snowflake people, get ideas on on solutions and how to best manage your credits and consumption. But to your point, Adrian, this is such a new thing that this is honestly, I think one of the best things about these user groups is just the ideation share. We tried this. This is what happened. This is what we would have done differently. We tried this. It was amazing. It just gives you a community of like minded data leaders to sort of pitch ideas off of and learn from so that you don't have to go and do everything hands on and just get experiential knowledge. You can get referential knowledge, which is super powerful. And I'll just quickly add that the and I won't say his name because I don't know how confident how happy he would be about it. But one of the presentations at the most recent stud was about building a business use case or like a business proposal to like, about a data project, which is not something you think of as like a Snowflake technical user group, but it was fantastic because it just explained like how the business needs to think about this sort of thing, how data users, data engineers and architects and technical people need to think about framing it to the business. Yeah. Was really, really, really good. Oh, that's awesome. I'm going to tie all of this up into one more question, and then I'll give you sort of an open ended moment to sort of state your final thoughts. My last question for you before giving you the floor for any final thoughts is with everything that we've talked about in terms of big steps forward in adding security and governance to your data, adding Snowflake to solve a specific document AI, use case, but then looking at oh, now we can expand to do more things. And obviously, within the focus of in Australia, smallish style business compared to the big global players, what is it, that you've learned that really allows you to compete on the global scale? I mean, said you were a minor cog in the sort of global supply chain network. What do you think are the key things that have really helped you guys stand out and differentiate on a global scale, sort of the thesis of this whole webinar? I guess acknowledging what our historical key point of difference was throughout the process and trying to continue on that vein which is historically our point of difference was like our single point of contact which was your key account manager role, heavy reliance on data in the system in a timely way. So if you had a question, you can call up your key account manager. They will talk to you through, you know, your customs requirements or your quarantine requirements or anything throughout your entire supply chain. You just spoke to that one person. And now we wanna stick to that, but we also recognize that what was our key point of difference may not be our key point of difference in the present or in the future. So just enabling them with technology so that we can be that thing. Who knows that key account manager might become an agentic endpoint so that another AI chatbot or something like that or another AI agent can communicate with the hardest agent. We don't know what's going to come, but we just need to be ready for whatever does come. And I guess what's amazing is that while we are a small piece in the logistics machine, every other freight forwarder, every other customs broker with a small piece in this big machine too. Because you then have like, you know, you have your suppliers, you have the shipping lines, you have the airlines, like it's it's actually quite beautiful watching how, you know, hundreds of people, thousands of people can communicate across the world and the flow of goods just kind of continues. And it is, you know, you know, quite a beautiful thing to watch when it all works well. And, yes, it is almost like watching a car crash like in COVID or when you see a ship wedged in the Suez Canal, that always makes for a very interesting thing. And, you know, oh, well, it's gonna be crazy and data's not gonna help me here, but it's just how you react to those situations. And it's a super dynamic industry and I I love it. So yeah. Let's say the way you the way you describe it, it almost sounds like an anthill where at a at a high level, it looks like chaos. But when you go down to the ground, these ants all have systems and tax and it all sort of chaotically beautifully works together to a net result. Yep. And we shouldn't touch on politics because that's gonna be a spicy topic. Next webinar, how about that? Sure. Well, listen, Adrian, thank you so much for for for coming on this webinar. We've gotten to work with you for several years. It's been an absolute delight working with you. Adrian is exactly like this in all of our meetings. She's very earnest and and, helpful and as, engaging and looking for the best ideas possible. From our side, it's been amazing. I'll give you the final comment and then just encouraging any the folks that are, in the, in the attendee list. If you've got any questions, please put those in now. Otherwise, Adrian, the floor is yours for some final thoughts. Thank you. Yeah, I just think that the journey that we are on as in like the whole world, every business is going to be touched by data and AI in some way, shape or form. So you best get on that wave now because it's just so much potential for not just the big businesses, but also small medium sized enterprises like us and other family businesses, there's just so much potential out there for AI and data to be the great equalizer. I touched a lot of the time on on, you know, what Snowflake offers. And Snowflake in a lot of ways offers a level playing field. Like, yes, you'll always come up get up against bigger competitors and everything like that. But we don't need to develop these super bespoke, very expensive tools. We don't need to, you know, develop our own LLMs. We can use other people's. We can have a federated platform for relatively low cost, you know, in comparison to what other data projects used to cost. It's going to be the great equalizer and there's no reason why and I'm passionate about family business too, but there's no reason why Australian and New Zealand family businesses or family businesses all around the world can't absolutely capitalize on this situation and yet grow and just be a force of good in a lot of ways in something that's quite can be framed if you read the news quite negatively too. And I do want to say thank you very much to the Interworks team. We wouldn't be on this journey to the level that we are without them. They've absolutely enabled us to get to our point where we are. We didn't touch on the Tableau journey, which is how we first met into works. But every step of the way, we always had someone I could talk to, to spitball the ideas off. If you want people that are passionate about data and AI, they're happy to help whenever. And obviously they get something out of it, we get something out of it too. But it's just, it's really, it's been a fantastic relationship and I look forward to many more years. Oh, thanks, Adrian. That was very nice. I'll give the folks just a little bit more time to put some more chats in there. There is a couple little slides I want to go through just at the end here. So for those folks that are looking to take another step forward in their data or AI journey, we can help. And we'd like to give you guys a bit of a fast start in it. One of these ones is is something that we did for Henning Harders, which was the AI exploratory workshop for executives. That's us sort of ideating with your leadership team on how AI could help. One of the other ones that we're offering for free for you guys that are attending is what we call a DART assessment or data and analytics review and tactics. Quick, short, sharp assessment on the things that you're doing across five maturity frameworks. That's data, people, governance, platforms, and governance, and how all of those things equate to AI readiness. It is again, it is a three sixty look short and sharp and tactical. So if you've got any interest in those, this is a little bit more detail on each of those. Ping us. We're certainly happy to help. And if you want to contact Interworks, all you have to do is scan this code. And if you have any, any need to to see Adrian, I'm sure he'd, say hi to you at the Sydney user group for Snowflake. There are probably other ways to stalk him, but, we'd certainly love to chat to anybody that's got an interest in sort of exploring this further. Let me take a look and see what we have in terms of questions. I just got to find my Zoom controls that jumped on me. Where did it go? Not there. Oh, there it is. I knew we had one comment, so I'll read that. I don't know if it's a question, but it's worth sharing. From, I think, Bridey. Thank you so much, Adrian. It was great to hear your story. Makes me think of Jim Collins' built to last and building a company that the world would miss if it didn't exist. Thanks for being such a great supporter of Snowflake. It's very good. Yeah, very nice. Otherwise it doesn't look like there are any other questions. If you do have questions after the fact, please email us. We're certainly happy to share them with Adrian and see if there's any answers that we can offer. Otherwise, Thank you so much for joining. Thank you again, Adrian and the entire Henning Harders team. We look forward to seeing everybody next time. Thanks Rob. Thank you everyone.