1 00:00:02,800 --> 00:00:05,000 Speaker 1: You're listening to the business of tech power by two 2 00:00:05,040 --> 00:00:08,360 Speaker 1: degrees business. I'm your host, Peter Griffin, and amidst the 3 00:00:08,400 --> 00:00:13,360 Speaker 1: news of business closures, growing unemployment and a puttering economy, 4 00:00:13,760 --> 00:00:15,880 Speaker 1: will take any good news we can get as we 5 00:00:15,920 --> 00:00:19,280 Speaker 1: head into spring, and definitely a big win this week 6 00:00:19,440 --> 00:00:23,480 Speaker 1: is Amazon's launch finally of its New Zealand Data Center region, 7 00:00:23,480 --> 00:00:27,400 Speaker 1: which represents a major injection of dollars into the country. 8 00:00:27,680 --> 00:00:31,280 Speaker 2: Amazon is going to invest seven and a half billion 9 00:00:31,360 --> 00:00:35,480 Speaker 2: New Zealand dollars, and as I mentioned before, this represents 10 00:00:35,560 --> 00:00:39,960 Speaker 2: the largest publicly announced global tech investment in New Zealand ever. 11 00:00:40,440 --> 00:00:44,800 Speaker 2: We expect to support one thousand new jobs and the 12 00:00:44,920 --> 00:00:51,320 Speaker 2: multiplier effect of these investments will affect local businesses, drive skills, 13 00:00:51,360 --> 00:00:55,280 Speaker 2: but most importantly will accelerate the transformation of New Zealand 14 00:00:55,320 --> 00:00:57,160 Speaker 2: into a leading technology hut. 15 00:00:57,640 --> 00:00:59,960 Speaker 1: So what else do we know about these data centers? 16 00:01:00,680 --> 00:01:02,800 Speaker 1: There are three of them in the Auckland region or 17 00:01:02,840 --> 00:01:06,720 Speaker 1: within one hundred kilometers of each other, and co located 18 00:01:06,760 --> 00:01:11,360 Speaker 1: with third party data centers, so AWS hasn't built its 19 00:01:11,400 --> 00:01:15,160 Speaker 1: own one from the ground up. It did have a 20 00:01:15,200 --> 00:01:18,240 Speaker 1: site in West Auckland with that in mind, but after 21 00:01:18,319 --> 00:01:22,360 Speaker 1: issues with drainage there. It's opted instead for three co 22 00:01:22,440 --> 00:01:28,039 Speaker 1: located sites, which is not unusual for AWS overseas. It 23 00:01:28,080 --> 00:01:33,040 Speaker 1: hasn't named who these data center hosts are for security reasons. 24 00:01:33,080 --> 00:01:36,240 Speaker 1: It says there are big players in the Auckland regions 25 00:01:36,280 --> 00:01:41,080 Speaker 1: such as DCI and Canberra Data Center's CDC, so they'd 26 00:01:41,120 --> 00:01:44,280 Speaker 1: be top of the list as potential candidates there as hosts. 27 00:01:45,040 --> 00:01:49,120 Speaker 1: The data centers, according to AWS, are powered one hundred 28 00:01:49,120 --> 00:01:52,400 Speaker 1: percent by renewable energy from day one. That's through a 29 00:01:52,400 --> 00:01:56,360 Speaker 1: long term energy agreement with Mercury. Microsoft did a similar 30 00:01:56,400 --> 00:01:59,880 Speaker 1: deal with Contact Energy for its data centers, which opened 31 00:02:00,160 --> 00:02:04,120 Speaker 1: in December. AWS has pledged to train one hundred thousand 32 00:02:04,160 --> 00:02:08,160 Speaker 1: kiwis in cloud skills by twenty twenty seven. Over half 33 00:02:08,240 --> 00:02:12,120 Speaker 1: of them are already trained according to AWS, so people 34 00:02:12,160 --> 00:02:17,679 Speaker 1: through various partners have done cloud skills or AI courses. 35 00:02:17,880 --> 00:02:22,760 Speaker 1: It's unclear exactly how extensive they are, how advanced those 36 00:02:22,760 --> 00:02:25,960 Speaker 1: skills have got, but I can imagine a lot of 37 00:02:26,000 --> 00:02:31,000 Speaker 1: people in existing companies that use AWS cloud tools have 38 00:02:31,120 --> 00:02:34,840 Speaker 1: been able to upskill and reskill with these three courses. 39 00:02:34,919 --> 00:02:38,840 Speaker 1: That's a good thing. The region is fully operational with 40 00:02:38,960 --> 00:02:44,200 Speaker 1: all required consents and environmental considerations addressed. According to AWS, 41 00:02:44,760 --> 00:02:47,440 Speaker 1: and there are some big names that have signed on 42 00:02:47,760 --> 00:02:53,080 Speaker 1: to be hosted in these data centers, including Kiwibank, Deloitte, 43 00:02:53,440 --> 00:02:58,760 Speaker 1: Vector one, Enz and Datacom smattering off government customers as well. 44 00:03:00,080 --> 00:03:03,480 Speaker 1: Couldn't tell me exactly what proportion of AI workloads will 45 00:03:03,520 --> 00:03:07,600 Speaker 1: be represented by the data center usage at launch, but 46 00:03:07,840 --> 00:03:11,560 Speaker 1: he did say that AWS will bring advanced AI services 47 00:03:11,600 --> 00:03:15,880 Speaker 1: such as Amazon, Bedrock and sage Maker to the region 48 00:03:16,000 --> 00:03:20,079 Speaker 1: later this year, so that'll be good for Kiwi innovation. 49 00:03:20,200 --> 00:03:23,799 Speaker 1: Those tools are currently only available from data centers offshore. 50 00:03:24,200 --> 00:03:28,120 Speaker 1: So yes, this is a decent investment in cloud infrastructure, 51 00:03:28,680 --> 00:03:31,320 Speaker 1: you know, that's critical to the digital economy, a sort 52 00:03:31,360 --> 00:03:34,280 Speaker 1: of benchmark really as to whether we're a developed nation 53 00:03:34,639 --> 00:03:37,960 Speaker 1: actually worth investing in, which is a question that has 54 00:03:37,960 --> 00:03:41,000 Speaker 1: given many companies pause of late when they look at 55 00:03:41,040 --> 00:03:43,840 Speaker 1: New Zealand. But the data center arrives a year late 56 00:03:44,000 --> 00:03:47,640 Speaker 1: and into a pretty soft economy, much softer than when 57 00:03:47,720 --> 00:03:51,960 Speaker 1: that investment was planned out four years ago. Amazon's business 58 00:03:52,000 --> 00:03:56,200 Speaker 1: model depends on New Zealand businesses and government department sending 59 00:03:56,320 --> 00:04:00,560 Speaker 1: increasing amounts of data and applications to the cloud, but 60 00:04:00,640 --> 00:04:05,080 Speaker 1: that requires significant investment for businesses with their own on 61 00:04:05,160 --> 00:04:08,640 Speaker 1: premises or even co located infrastructure. Many of them just 62 00:04:08,680 --> 00:04:11,280 Speaker 1: don't have the money at the moment. They're deferring cloud 63 00:04:11,480 --> 00:04:15,920 Speaker 1: migration and so called digital transformation projects, even if the 64 00:04:15,960 --> 00:04:19,119 Speaker 1: cost equation may work out favorably over the long run. 65 00:04:19,279 --> 00:04:21,839 Speaker 1: But this week's guests on the Business of Tech have 66 00:04:21,920 --> 00:04:25,000 Speaker 1: a different take on the race to the cloud. Seth 67 00:04:25,120 --> 00:04:28,679 Speaker 1: Ravin is the founder of Las Vegas based NASDAQ listed 68 00:04:28,720 --> 00:04:33,240 Speaker 1: IT services firm Remeny Street. Joe Lecandro is the company's 69 00:04:33,279 --> 00:04:38,920 Speaker 1: Australia based group executive vice president and global Chief Information Officer. 70 00:04:39,520 --> 00:04:43,800 Speaker 1: Remeny Street provide third party support for big on premises 71 00:04:44,200 --> 00:04:48,839 Speaker 1: enterprise IT systems from the likes of Oracle, PeopleSoft, SAP, 72 00:04:49,200 --> 00:04:52,440 Speaker 1: and VMware. Their pitch is that they can save customers 73 00:04:52,520 --> 00:04:56,039 Speaker 1: up to fifty percent on support fees for those systems, 74 00:04:56,600 --> 00:04:59,920 Speaker 1: below what they typically be charged by the software vend 75 00:05:00,279 --> 00:05:04,880 Speaker 1: annual support programs. Not only that, Ravin's big pitch is 76 00:05:04,920 --> 00:05:08,200 Speaker 1: that you can stay on those legacy systems for another 77 00:05:08,279 --> 00:05:11,919 Speaker 1: fifteen years. They'll support them out to twenty forty In 78 00:05:11,960 --> 00:05:15,160 Speaker 1: many cases, don't get caught up in the race to 79 00:05:15,240 --> 00:05:19,120 Speaker 1: the cloud. They say, sweat your perfectly good existing assets 80 00:05:19,720 --> 00:05:23,880 Speaker 1: and save significantly on support fees. But what about new 81 00:05:23,920 --> 00:05:27,800 Speaker 1: features like AI? AI agents are all the buzz at 82 00:05:27,800 --> 00:05:30,719 Speaker 1: the moment. Remeny Street say they've come up with a 83 00:05:30,760 --> 00:05:34,960 Speaker 1: way to run AI tools and agency even over the 84 00:05:34,960 --> 00:05:38,960 Speaker 1: top of those legacy platforms, which Ravenc's is basically becoming 85 00:05:39,520 --> 00:05:43,599 Speaker 1: large databases of information that you use AI to extract 86 00:05:43,880 --> 00:05:48,760 Speaker 1: information and insights from. You don't actually need to upgrade 87 00:05:48,800 --> 00:05:52,360 Speaker 1: to the cloud version to get that added functionality. It's 88 00:05:52,360 --> 00:05:55,120 Speaker 1: a bit of a controversial approach that has seen remeny 89 00:05:55,160 --> 00:05:58,000 Speaker 1: Street tied up for years in legal action with Oracle, 90 00:05:58,520 --> 00:06:01,880 Speaker 1: which are just this year's set, but the cost saving 91 00:06:01,960 --> 00:06:06,240 Speaker 1: narrative certainly has widespread appeal. Remeny Street had revenue off 92 00:06:06,240 --> 00:06:09,839 Speaker 1: around four hundred and twenty nine million dollars US last 93 00:06:09,920 --> 00:06:13,200 Speaker 1: year and has a growing slate of customers in New Zealand. 94 00:06:13,760 --> 00:06:17,600 Speaker 1: So here's remeny Street founder Seth raven and global CIO 95 00:06:17,880 --> 00:06:21,360 Speaker 1: Joe Lecandro on how to find new life in your 96 00:06:21,440 --> 00:06:31,640 Speaker 1: legacy tech Seth and Joe, Welcome to the business of tech. 97 00:06:31,680 --> 00:06:32,240 Speaker 1: How are you doing? 98 00:06:32,680 --> 00:06:36,280 Speaker 3: Great? Good, good good to be back in the Australia, 99 00:06:36,360 --> 00:06:40,440 Speaker 3: New Zealand market and looking forward to having a trip 100 00:06:40,480 --> 00:06:41,960 Speaker 3: to New Zealand in a couple of days. 101 00:06:42,240 --> 00:06:44,760 Speaker 1: Yeah, yeah, that's great. You're coming over to see customers 102 00:06:44,800 --> 00:06:49,200 Speaker 1: and talk to enterprise IT people here, and quite a 103 00:06:49,360 --> 00:06:52,279 Speaker 1: compelling proposition that you'll be giving them, and we're going 104 00:06:52,320 --> 00:06:55,159 Speaker 1: to get into that shortly. But big milestone for you, 105 00:06:55,200 --> 00:06:58,479 Speaker 1: seth the company is as we record this, a couple 106 00:06:58,520 --> 00:07:02,200 Speaker 1: of weeks away from being twenty years old two thousand 107 00:07:02,200 --> 00:07:05,640 Speaker 1: and five. You set up this company after very senior 108 00:07:05,720 --> 00:07:10,000 Speaker 1: roles at vice prison of SAP for instance, PeopleSoft. You're 109 00:07:10,000 --> 00:07:13,200 Speaker 1: at enterprise IT guy through and through. Tell us about 110 00:07:13,240 --> 00:07:16,960 Speaker 1: the genesis of the company. What inspired you doing really 111 00:07:17,000 --> 00:07:21,560 Speaker 1: well in these highly established companies? What inspired you to 112 00:07:21,560 --> 00:07:23,560 Speaker 1: go out on your own and sit up Reminy Street. 113 00:07:23,920 --> 00:07:26,400 Speaker 3: You know, Peter, I was actually in the business of 114 00:07:26,920 --> 00:07:32,480 Speaker 3: the maintenance and seeing the customer value at PeopleSoft. We 115 00:07:32,520 --> 00:07:36,240 Speaker 3: built the company from the early team up very successfully, 116 00:07:37,160 --> 00:07:40,400 Speaker 3: and we built a maintenance team, and I watched how 117 00:07:40,400 --> 00:07:43,640 Speaker 3: we continued to raise the rates or we used to 118 00:07:43,800 --> 00:07:47,679 Speaker 3: charge them fifteen percent of their of what the license 119 00:07:47,720 --> 00:07:51,040 Speaker 3: fees were, then seventeen, then eighteen, then twenty, then twenty 120 00:07:51,080 --> 00:07:55,720 Speaker 3: one and twenty two percent, and the profit margins continued 121 00:07:55,760 --> 00:08:01,000 Speaker 3: to rise up to in the ninety percentage points. I'm 122 00:08:01,040 --> 00:08:03,960 Speaker 3: sure many of your listeners would love the idea of 123 00:08:04,000 --> 00:08:07,720 Speaker 3: a ninety percent profit margin, but the reality is there's 124 00:08:07,800 --> 00:08:11,960 Speaker 3: few companies in the world that achieved that kind of number. 125 00:08:12,520 --> 00:08:14,960 Speaker 3: And so I went off and I looked at a 126 00:08:15,000 --> 00:08:19,120 Speaker 3: bunch of things, and when I left SAP, I looked 127 00:08:19,120 --> 00:08:24,280 Speaker 3: at this opportunity. And in every other part of the economy, 128 00:08:24,680 --> 00:08:28,000 Speaker 3: there's choice. You can take your car to the dealer 129 00:08:28,160 --> 00:08:31,080 Speaker 3: that you bought it from and have the mechanics work 130 00:08:31,120 --> 00:08:33,480 Speaker 3: on it, but you can also take it to the 131 00:08:33,520 --> 00:08:36,320 Speaker 3: local mechanic down the street if you like them better. 132 00:08:36,920 --> 00:08:40,440 Speaker 3: And so every part of our world had alternatives. But 133 00:08:40,559 --> 00:08:44,480 Speaker 3: in the world of enterprise software, there was an assumption 134 00:08:44,640 --> 00:08:48,760 Speaker 3: that only the software vendor could fix the system, could 135 00:08:48,840 --> 00:08:52,600 Speaker 3: run the system, and therefore you had to pay these 136 00:08:52,679 --> 00:08:57,080 Speaker 3: exorbitant amounts of money for in many cases, low value, 137 00:08:57,800 --> 00:09:01,400 Speaker 3: and that's the only choice. So there was this attached 138 00:09:01,480 --> 00:09:04,040 Speaker 3: rate of over ninety nine percent. I looked at that 139 00:09:04,160 --> 00:09:06,120 Speaker 3: and said, you know what, I'm going to take my 140 00:09:06,280 --> 00:09:08,360 Speaker 3: experience and I'm going to come in and offer an 141 00:09:08,360 --> 00:09:12,360 Speaker 3: alternative in that space. At half off and better service. 142 00:09:12,720 --> 00:09:14,840 Speaker 1: Well, look, that's that's the pitch, isn't it. You know, 143 00:09:14,880 --> 00:09:18,880 Speaker 1: remeny Street says it can help organizations dramatically cut their 144 00:09:18,960 --> 00:09:23,200 Speaker 1: support costs on platforms like SAP and Oracle. You know, 145 00:09:23,400 --> 00:09:26,880 Speaker 1: big customers here using both of those. What's at the 146 00:09:26,880 --> 00:09:29,240 Speaker 1: core of the savings. Where do you find the sort 147 00:09:29,280 --> 00:09:32,760 Speaker 1: of efficiencies that Oracle or SAP don't. 148 00:09:33,200 --> 00:09:37,840 Speaker 3: It's not just about the efficiencies. If you if you're 149 00:09:37,880 --> 00:09:41,440 Speaker 3: willing to accept a lower profit margin, you're in a 150 00:09:41,520 --> 00:09:44,640 Speaker 3: position where you can say, Okay, we're going to accept 151 00:09:44,640 --> 00:09:47,880 Speaker 3: a reasonable profit margin and we're actually going to spend 152 00:09:47,960 --> 00:09:52,760 Speaker 3: more money to service the client. Because if you're driving 153 00:09:53,120 --> 00:09:57,800 Speaker 3: a ninety percent plus profit margin, just do the math, 154 00:09:58,440 --> 00:10:03,200 Speaker 3: you cannot offer much service. You can't. The money's not there. 155 00:10:03,320 --> 00:10:05,960 Speaker 3: You have to say no to just about everything. And 156 00:10:06,000 --> 00:10:09,720 Speaker 3: so in that environment, we said, we're gonna we're gonna 157 00:10:09,760 --> 00:10:13,480 Speaker 3: spend more on the customer, give them more service. We're 158 00:10:13,480 --> 00:10:17,640 Speaker 3: gonna cut the price in half, accept a much lower 159 00:10:17,720 --> 00:10:22,200 Speaker 3: profit margin. That's reasonable, and that's how we're going to 160 00:10:22,240 --> 00:10:24,359 Speaker 3: do this. We're gonna make it better for the customer, 161 00:10:24,440 --> 00:10:27,480 Speaker 3: and we're going to have a good business, a solid business. 162 00:10:27,280 --> 00:10:32,000 Speaker 1: And Joe, look, you're also enterprise it guy, through and through, 163 00:10:32,120 --> 00:10:36,800 Speaker 1: you know, senior roles, Emirates, Cathay Pacific and many Australian companies, 164 00:10:36,840 --> 00:10:40,840 Speaker 1: and then over the ditch here at at Fletcher's for 165 00:10:40,840 --> 00:10:44,120 Speaker 1: a while as as CIO, and that is a big 166 00:10:44,320 --> 00:10:48,199 Speaker 1: sap shop, you know, Fletcher's, So give us your perspective 167 00:10:48,360 --> 00:10:53,360 Speaker 1: being a CIO, I guess frustration at exactly what Seth 168 00:10:54,000 --> 00:10:57,760 Speaker 1: was talking about in those roles, seeing these high maintenance 169 00:10:57,800 --> 00:11:02,320 Speaker 1: and support charges and then being inspired to actually join 170 00:11:02,400 --> 00:11:04,800 Speaker 1: Seth and cutting those for customers. 171 00:11:04,920 --> 00:11:09,120 Speaker 4: I've been a practicing CIO globally for over twenty five 172 00:11:09,240 --> 00:11:14,839 Speaker 4: thirty years, and for me, like most other CIOs, you're 173 00:11:14,880 --> 00:11:18,800 Speaker 4: on the treadmill, you're on the upgrade path, and in 174 00:11:18,880 --> 00:11:23,000 Speaker 4: most cases the cost to move is a barrier, even 175 00:11:23,040 --> 00:11:27,760 Speaker 4: if you were getting a huge price increase, and vendors 176 00:11:28,120 --> 00:11:32,200 Speaker 4: typically know that that even if they rip up the 177 00:11:32,240 --> 00:11:36,800 Speaker 4: price year on year, the cost to exit is greater 178 00:11:36,880 --> 00:11:41,320 Speaker 4: than the price of the increase. But for me, the 179 00:11:41,520 --> 00:11:46,200 Speaker 4: value proposition of Rhymney and It was that we had 180 00:11:46,960 --> 00:11:53,280 Speaker 4: some tech debt and everybody wants to modernize and until 181 00:11:53,440 --> 00:11:56,000 Speaker 4: you know the advent of AI and things like that. 182 00:11:56,880 --> 00:12:02,640 Speaker 4: There wasn't many alternatives. Most CIO and most executives got 183 00:12:02,679 --> 00:12:08,439 Speaker 4: their world best practice through upgrades or supposedly through your 184 00:12:08,480 --> 00:12:13,840 Speaker 4: maintenance fee. The problem is sometimes you used all the functionality, 185 00:12:13,920 --> 00:12:16,760 Speaker 4: sometimes you didn't, but you're still stuck with the cost 186 00:12:16,800 --> 00:12:21,120 Speaker 4: of upgrading. And that's the real hidden cost. It's not 187 00:12:21,160 --> 00:12:26,040 Speaker 4: necessarily the license cost. It's the cost of upgrading because 188 00:12:26,080 --> 00:12:32,679 Speaker 4: sometimes and I did an upgrade from ECC six S 189 00:12:32,760 --> 00:12:36,880 Speaker 4: for Hannah, and the most common bit of feedback I 190 00:12:36,920 --> 00:12:40,920 Speaker 4: was getting is that this runs totally different. It's not 191 00:12:41,000 --> 00:12:45,840 Speaker 4: an upgrade, it's a new implementation and the change management 192 00:12:45,920 --> 00:12:49,480 Speaker 4: and all everything that's associated with it, and all that 193 00:12:49,679 --> 00:12:52,560 Speaker 4: is for the sake of I'm going to get more 194 00:12:52,559 --> 00:12:57,360 Speaker 4: functionality because I have to modernize. But now there are alternatives. 195 00:12:57,400 --> 00:13:02,920 Speaker 4: And when I joinedney Street and I'd seen firsthand as 196 00:13:02,920 --> 00:13:06,240 Speaker 4: a customer, and I think that's the proof in the putting. 197 00:13:06,280 --> 00:13:09,319 Speaker 4: When you're a customer and you've got all the cost 198 00:13:09,360 --> 00:13:13,200 Speaker 4: pressures and you've got all the board pressures and compliance pressures, 199 00:13:13,240 --> 00:13:16,840 Speaker 4: and you know that doesn't go away. And rymney Street 200 00:13:16,960 --> 00:13:21,479 Speaker 4: offered me, in my role in New Zealand, an alternative 201 00:13:21,600 --> 00:13:26,240 Speaker 4: that I was able to keep those systems running more 202 00:13:26,320 --> 00:13:27,200 Speaker 4: cost effectively. 203 00:13:27,559 --> 00:13:30,680 Speaker 1: Yeah, and look the exactly as you say that upgrade 204 00:13:30,720 --> 00:13:36,560 Speaker 1: treadmill that you know most New Zealand Australian organizations are on. 205 00:13:36,720 --> 00:13:39,680 Speaker 1: You know, I've been hearing a lot from SAP, you know, 206 00:13:39,840 --> 00:13:43,079 Speaker 1: putting out this message support is ending for our legacy 207 00:13:43,120 --> 00:13:46,040 Speaker 1: systems in twenty twenty seven. You need to move to 208 00:13:46,120 --> 00:13:49,400 Speaker 1: the cloud to is for Hannah, don't be left behind. 209 00:13:50,520 --> 00:13:52,920 Speaker 1: So that is very much from all the vendors, whether 210 00:13:52,960 --> 00:13:56,560 Speaker 1: it be Microsoft, Oracle or any of them, you'll fall 211 00:13:56,600 --> 00:14:00,640 Speaker 1: behind on security, compliance and integration. And if you don't 212 00:14:00,720 --> 00:14:04,679 Speaker 1: go on this pathway. What is quite refreshing and different 213 00:14:04,840 --> 00:14:07,920 Speaker 1: is this opposite you view that you take that legacy 214 00:14:07,960 --> 00:14:12,680 Speaker 1: platforms can continue running safely and reliably. 215 00:14:13,440 --> 00:14:16,800 Speaker 3: So how do you do this? Again, You start with 216 00:14:17,520 --> 00:14:22,560 Speaker 3: excellent engineers. We have nearly one thousand engineers across twenty 217 00:14:22,600 --> 00:14:26,800 Speaker 3: three different countries, and you start with the quality of 218 00:14:26,840 --> 00:14:32,080 Speaker 3: that engineering talent, and then you build a system of 219 00:14:32,360 --> 00:14:37,280 Speaker 3: processes that allow you to respond in things like two 220 00:14:37,320 --> 00:14:41,160 Speaker 3: minutes or less twenty four by seven, which again we 221 00:14:41,600 --> 00:14:45,720 Speaker 3: support all the way up to military and then of 222 00:14:45,760 --> 00:14:50,560 Speaker 3: course things like nuclear power very very high security operations 223 00:14:50,600 --> 00:14:54,840 Speaker 3: that we help manage. And so when you see all 224 00:14:54,840 --> 00:14:58,040 Speaker 3: that and you put all those pieces together, you have 225 00:14:58,120 --> 00:15:02,600 Speaker 3: a program that can right what the vendors offer. It's 226 00:15:02,640 --> 00:15:06,800 Speaker 3: actually more robust. We cover things that the vendors don't uh. 227 00:15:06,960 --> 00:15:09,080 Speaker 3: And it really is a function of what is it 228 00:15:09,120 --> 00:15:11,760 Speaker 3: you're willing to do, what is it you're willing to 229 00:15:11,840 --> 00:15:15,800 Speaker 3: spend in order to service the customer, and what profit 230 00:15:15,840 --> 00:15:18,200 Speaker 3: margin you're willing to take. And I think we've come 231 00:15:18,280 --> 00:15:21,920 Speaker 3: up with a great balance that allows for a strong company. 232 00:15:22,080 --> 00:15:25,360 Speaker 3: You know, we're grown over four hundred million US a 233 00:15:25,440 --> 00:15:30,200 Speaker 3: year as a stock exchange a traded company in the US, 234 00:15:30,960 --> 00:15:34,040 Speaker 3: and we've been able to build a company with thousands 235 00:15:34,120 --> 00:15:37,720 Speaker 3: of clients, including hundreds of the world's largest companies and 236 00:15:37,760 --> 00:15:41,840 Speaker 3: government agencies. And so it's it's been a really exciting 237 00:15:41,960 --> 00:15:45,560 Speaker 3: thing to come into a market and change the dynamic 238 00:15:46,400 --> 00:15:49,360 Speaker 3: where customers are like, wow, I mean I actually have 239 00:15:49,440 --> 00:15:54,520 Speaker 3: an alternative and it's and it's a very pragmatic alternative 240 00:15:54,920 --> 00:15:57,640 Speaker 3: because they're used to this in their common life. You 241 00:15:57,640 --> 00:16:00,400 Speaker 3: you know, if you're washer and dry or break down home, 242 00:16:00,840 --> 00:16:04,360 Speaker 3: you can call the manufacturer, you can call Joe's repair shop. 243 00:16:04,480 --> 00:16:07,440 Speaker 3: Down the street and you have those rights. I mean, 244 00:16:07,480 --> 00:16:10,320 Speaker 3: this is in many ways we're just bringing the same 245 00:16:10,400 --> 00:16:14,680 Speaker 3: kind of choice that consumers have in their daily lives. 246 00:16:14,840 --> 00:16:18,440 Speaker 1: And that speaks to really the disconnect I see and 247 00:16:18,800 --> 00:16:23,560 Speaker 1: here when I talk to cio CTOs and boards of companies, 248 00:16:23,760 --> 00:16:26,680 Speaker 1: there's a disconnect between the speed at which the vendors 249 00:16:26,720 --> 00:16:29,600 Speaker 1: want to move, particularly in the cloud era where it 250 00:16:29,720 --> 00:16:33,280 Speaker 1: is moving very very quickly, and their ability to move 251 00:16:34,080 --> 00:16:38,360 Speaker 1: their legacy systems. And particularly it's hard times in New Zealand. 252 00:16:38,360 --> 00:16:40,960 Speaker 1: We're in a recessionary environment at the moment. A lot 253 00:16:41,000 --> 00:16:45,840 Speaker 1: of budgets have been cut, so they're being told we're 254 00:16:45,840 --> 00:16:49,960 Speaker 1: going to have to defer these upgrades. So your pitch, 255 00:16:50,000 --> 00:16:53,000 Speaker 1: I think is very attractive. But is there a danger 256 00:16:53,160 --> 00:16:57,200 Speaker 1: that companies that sort of sit on their legacy stuff 257 00:16:57,960 --> 00:17:01,080 Speaker 1: defer upgrades, that they're just pushing cost into the future, 258 00:17:01,120 --> 00:17:02,440 Speaker 1: or are they going to end up with sort of 259 00:17:02,440 --> 00:17:06,160 Speaker 1: brittle systems that limit their ability to innovate. 260 00:17:06,480 --> 00:17:08,920 Speaker 3: But you know, Peter, there's two things. You can save 261 00:17:09,040 --> 00:17:13,120 Speaker 3: money and you can invest money. And what we do 262 00:17:13,280 --> 00:17:18,280 Speaker 3: is by lowering the daily cost of operations, we allow 263 00:17:18,680 --> 00:17:22,359 Speaker 3: organizations to make decisions. You know, if you're really in 264 00:17:22,400 --> 00:17:26,680 Speaker 3: a tight financial position, you can drop all the savings 265 00:17:26,720 --> 00:17:30,080 Speaker 3: to the bottom line. You can do that if you 266 00:17:30,119 --> 00:17:32,439 Speaker 3: are in a middle ground where you're saying, look, I 267 00:17:32,520 --> 00:17:36,080 Speaker 3: need to save something, but I also need to innovate. 268 00:17:36,119 --> 00:17:39,440 Speaker 3: Because the truth is, Peter, you can never cut your 269 00:17:39,480 --> 00:17:42,879 Speaker 3: way to growth. And if you're in a position, and 270 00:17:42,880 --> 00:17:45,240 Speaker 3: it always depends on where you are in the economic 271 00:17:45,359 --> 00:17:49,199 Speaker 3: cycle of both an organization as well as the economy. 272 00:17:49,840 --> 00:17:52,680 Speaker 3: If you're in a defensive position again where it's throw 273 00:17:52,800 --> 00:17:55,679 Speaker 3: everything overboard and we just need to we need to 274 00:17:55,720 --> 00:17:57,960 Speaker 3: cut costs, we need to get that cost down. Great, 275 00:17:58,359 --> 00:18:01,239 Speaker 3: we can help with that if you want it and 276 00:18:01,280 --> 00:18:05,840 Speaker 3: make an investment. You must invest in innovation in order 277 00:18:05,880 --> 00:18:10,560 Speaker 3: to accelerate growth and maintain and grow competitive advantage. And 278 00:18:10,560 --> 00:18:13,480 Speaker 3: that's why most of our customers, instead of saving the 279 00:18:13,520 --> 00:18:16,720 Speaker 3: full amount, they'll save some of the money that we 280 00:18:17,000 --> 00:18:20,399 Speaker 3: help cut in costs, and then they'll invest some of 281 00:18:20,440 --> 00:18:23,480 Speaker 3: that money. Some do fifty to fifty. We'll drop for 282 00:18:23,560 --> 00:18:26,960 Speaker 3: every you know, for every dollar that we say, we're 283 00:18:27,000 --> 00:18:30,400 Speaker 3: going to put half of that on the savings line 284 00:18:30,440 --> 00:18:32,160 Speaker 3: and we're going to put half of it into innovation, 285 00:18:32,880 --> 00:18:38,520 Speaker 3: and we allow innovation to continue forward by reallocating that 286 00:18:38,680 --> 00:18:43,880 Speaker 3: part of the savings into new technology, so they don't 287 00:18:43,960 --> 00:18:45,879 Speaker 3: have to sit on their hands and knees, and they 288 00:18:45,880 --> 00:18:49,160 Speaker 3: don't have to just wait and do nothing. And because 289 00:18:49,280 --> 00:18:53,360 Speaker 3: we've now got an innovation model investment that says we 290 00:18:53,400 --> 00:18:57,320 Speaker 3: can do small pieces at a time, they don't need 291 00:18:57,359 --> 00:19:00,520 Speaker 3: to do some massive project that nobody is going to 292 00:19:00,560 --> 00:19:04,000 Speaker 3: approve from a risk and cost perspective. But we can 293 00:19:04,040 --> 00:19:07,760 Speaker 3: do a piece at a time and move a customer forward. 294 00:19:08,280 --> 00:19:12,959 Speaker 3: So progress is possible even within a cut budget if 295 00:19:12,960 --> 00:19:14,480 Speaker 3: they're willing to allocate for it. 296 00:19:14,600 --> 00:19:19,840 Speaker 1: Joe Remenie Street often talks about you know, layering artificial intelligence, 297 00:19:20,040 --> 00:19:23,120 Speaker 1: data analytics and the like on top of these stable 298 00:19:23,200 --> 00:19:27,240 Speaker 1: but you know, legacy systems to extract new value from 299 00:19:27,280 --> 00:19:30,440 Speaker 1: those older systems. So how does that work in practice? 300 00:19:30,480 --> 00:19:33,320 Speaker 1: Particularly again the message from the vendors, if you want 301 00:19:33,680 --> 00:19:37,320 Speaker 1: to get the best out of AI agents, for instance, 302 00:19:37,359 --> 00:19:40,879 Speaker 1: on SAP or Salesforce or Oracle, you really need to 303 00:19:40,880 --> 00:19:43,639 Speaker 1: be on our cloud. But you're saying no, you can 304 00:19:43,720 --> 00:19:46,199 Speaker 1: run AI over the top of all of that off 305 00:19:46,280 --> 00:19:47,280 Speaker 1: those older systems. 306 00:19:47,520 --> 00:19:50,439 Speaker 4: Yeah. Correct, And I think this is the this is 307 00:19:50,480 --> 00:19:54,200 Speaker 4: the paradigm shift. This is the choice as a CIO 308 00:19:54,320 --> 00:19:57,639 Speaker 4: did not have two years ago. If I wanted innovation 309 00:19:57,840 --> 00:20:02,880 Speaker 4: or increased functionality, I had to upgrade because the older 310 00:20:02,920 --> 00:20:07,560 Speaker 4: system was seen as a blocker to innovation. AI wasn't 311 00:20:07,600 --> 00:20:11,399 Speaker 4: around two years ago in the sphere, little one agentic 312 00:20:11,520 --> 00:20:16,880 Speaker 4: the term. So the difference now is those systems of record, 313 00:20:17,040 --> 00:20:22,640 Speaker 4: those ERPs, financial systems or whatever run well. They've got 314 00:20:22,680 --> 00:20:28,320 Speaker 4: their customizations where they're giving value, you're really sweating the asset. 315 00:20:28,920 --> 00:20:33,680 Speaker 4: But they're compliant, they're auditable, etc. So therefore the premise 316 00:20:33,920 --> 00:20:38,560 Speaker 4: is, is there an alternative path to give me functionality, give 317 00:20:38,600 --> 00:20:42,960 Speaker 4: me innovation without having to rip out and replace the core. 318 00:20:43,920 --> 00:20:47,800 Speaker 4: And this is where agentic AI comes in. Now, agentic 319 00:20:47,880 --> 00:20:51,560 Speaker 4: AI and generative AI. Most people are familiar with generative 320 00:20:51,600 --> 00:20:56,240 Speaker 4: AI through co pilot and chat GPT, and it does 321 00:20:56,280 --> 00:20:59,920 Speaker 4: a bit of predictability based on some sample sets prior. 322 00:21:00,920 --> 00:21:06,240 Speaker 4: Agentic AI is a workflow and when you combine predictive 323 00:21:06,560 --> 00:21:13,600 Speaker 4: analytics and generative AI together with workflow, you can put 324 00:21:13,600 --> 00:21:16,879 Speaker 4: that on the top of the ERPs. And that's the 325 00:21:16,920 --> 00:21:19,959 Speaker 4: big difference. In the old days, you would have to 326 00:21:20,160 --> 00:21:24,120 Speaker 4: customize your old ERP to a new workflow and new 327 00:21:24,240 --> 00:21:29,240 Speaker 4: job type, but speed to market is what is important 328 00:21:29,280 --> 00:21:33,359 Speaker 4: now because an ERP upgrade or a functionality one would 329 00:21:33,400 --> 00:21:39,560 Speaker 4: take several years and significant cost to build. On Seth's point, 330 00:21:39,880 --> 00:21:44,360 Speaker 4: the agents that are roaming across the top go through 331 00:21:44,400 --> 00:21:48,600 Speaker 4: what we call a data fabric layer, and those are 332 00:21:48,760 --> 00:21:53,960 Speaker 4: like self determining data dictionaries. If the agent is looking 333 00:21:54,040 --> 00:21:58,440 Speaker 4: for financial information, it will recognize that when it goes 334 00:21:58,520 --> 00:22:05,000 Speaker 4: into a financial system, there's numbers, and there's customer attributes, 335 00:22:05,400 --> 00:22:08,280 Speaker 4: and it knows it's a financial system. It's building up 336 00:22:08,320 --> 00:22:11,720 Speaker 4: that on the fly. If it goes into a CRM 337 00:22:11,840 --> 00:22:16,120 Speaker 4: system like a salesforce, etc. It's seeing customer notes, it's 338 00:22:16,119 --> 00:22:21,000 Speaker 4: seeing all those things. So the intelligence is now being 339 00:22:21,040 --> 00:22:25,840 Speaker 4: in the layer above, just as the intelligence in routers, etc. 340 00:22:26,760 --> 00:22:30,480 Speaker 4: Is now in the software above. This is a trend 341 00:22:30,920 --> 00:22:34,800 Speaker 4: that you see where the intelligence gets taken out of 342 00:22:34,840 --> 00:22:39,439 Speaker 4: the core hardware or firmware into that next layer above. 343 00:22:40,000 --> 00:22:43,800 Speaker 4: So what that means is for companies and CIOs is 344 00:22:43,840 --> 00:22:47,359 Speaker 4: that they can mix and match processes, they can mix 345 00:22:47,440 --> 00:22:51,879 Speaker 4: and match data and analytics, and they only have to 346 00:22:51,960 --> 00:22:55,639 Speaker 4: go into the source system for the information it needs. 347 00:22:56,600 --> 00:23:00,719 Speaker 4: And a good example is if you're in inventory, you 348 00:23:00,760 --> 00:23:02,919 Speaker 4: have to go through two or three systems to do 349 00:23:03,040 --> 00:23:06,840 Speaker 4: your job, and you do about twenty clicks. If you 350 00:23:07,040 --> 00:23:09,879 Speaker 4: had an agent, it could go and check the inventory 351 00:23:09,960 --> 00:23:13,439 Speaker 4: through the inventory system. It could predict that through the 352 00:23:13,480 --> 00:23:15,960 Speaker 4: sales that you're going to run out within four months. 353 00:23:16,560 --> 00:23:20,040 Speaker 4: It can create a process where it automatically creates a 354 00:23:20,080 --> 00:23:24,080 Speaker 4: purchase order, looks at the vendor file, and automates all 355 00:23:24,160 --> 00:23:29,400 Speaker 4: that from twenty clicks to one click, from twenty minutes 356 00:23:29,600 --> 00:23:33,840 Speaker 4: to two minutes, with all the recommendations and automation. And 357 00:23:33,920 --> 00:23:38,160 Speaker 4: that is quick, cheap and easy to do on top 358 00:23:38,240 --> 00:23:41,560 Speaker 4: of the ERP and you can keep doing that many 359 00:23:41,640 --> 00:23:45,359 Speaker 4: many times over. You don't have to wait for the 360 00:23:45,400 --> 00:23:49,080 Speaker 4: next upgrade, which is like I say, a reinstall in 361 00:23:49,119 --> 00:23:49,840 Speaker 4: most cases. 362 00:23:50,000 --> 00:23:53,040 Speaker 1: It's really quite a challenging concept to the model we've 363 00:23:53,080 --> 00:23:56,920 Speaker 1: been sold. I mean, what's the future of these big 364 00:23:57,160 --> 00:24:00,199 Speaker 1: ERP systems. Are they essentially just going to become like 365 00:24:00,280 --> 00:24:05,359 Speaker 1: databases where you use your own AI agents and interfaces 366 00:24:05,400 --> 00:24:09,520 Speaker 1: to interrogate those systems and get the reporting and the 367 00:24:09,560 --> 00:24:10,880 Speaker 1: information you need out of them. 368 00:24:10,920 --> 00:24:13,840 Speaker 3: Well, Peter, I believe in five to ten years our 369 00:24:13,880 --> 00:24:18,480 Speaker 3: position is there's no ERP software. We are now in 370 00:24:18,600 --> 00:24:23,679 Speaker 3: the process of converting. If you look at ERP software, 371 00:24:24,560 --> 00:24:29,760 Speaker 3: these big monolithic systems, they were designed to run most 372 00:24:29,760 --> 00:24:33,760 Speaker 3: of the key processes of a business or an organization. 373 00:24:34,520 --> 00:24:38,520 Speaker 3: And we always had these defined processes like order to cash, 374 00:24:39,080 --> 00:24:40,240 Speaker 3: procure to pay. 375 00:24:40,760 --> 00:24:42,040 Speaker 4: They haven't really changed. 376 00:24:42,480 --> 00:24:45,399 Speaker 3: We've been doing We've been counting the beans as accountants 377 00:24:45,480 --> 00:24:48,680 Speaker 3: for years. You know, we have to send out invoices, 378 00:24:48,720 --> 00:24:52,040 Speaker 3: we have to pay employees. None of that has changed really, 379 00:24:53,000 --> 00:24:57,000 Speaker 3: you know, in fifty years, we just have improved the systems. 380 00:24:57,040 --> 00:25:00,200 Speaker 3: They've got prettier screens and things along the line, but 381 00:25:00,560 --> 00:25:03,080 Speaker 3: it makes it a little bit easier. But we're still 382 00:25:03,119 --> 00:25:06,520 Speaker 3: doing the same functions. And what we're doing now is 383 00:25:06,560 --> 00:25:11,720 Speaker 3: we're taking these processes and we're turning them into aegentic 384 00:25:12,240 --> 00:25:17,119 Speaker 3: ERP processes that live above where the ERP system is. 385 00:25:17,680 --> 00:25:21,240 Speaker 3: And as we build these out, connecting up a whole 386 00:25:21,280 --> 00:25:26,400 Speaker 3: bunch of different services with a workflow system like service 387 00:25:26,520 --> 00:25:30,560 Speaker 3: now and then we're using intelligent agents to run those 388 00:25:30,600 --> 00:25:34,600 Speaker 3: processes instead of human beings. And so when all that 389 00:25:34,680 --> 00:25:38,840 Speaker 3: comes into play, there's no need for the underlying EARP 390 00:25:39,119 --> 00:25:42,720 Speaker 3: software anymore. It goes away. And so you can imagine 391 00:25:42,720 --> 00:25:47,120 Speaker 3: how terrifying This is for the ERP software vendors, and 392 00:25:47,640 --> 00:25:49,800 Speaker 3: this is the vision we're out there. In fact, we're 393 00:25:49,840 --> 00:25:53,880 Speaker 3: installing this already. We just put in in a company 394 00:25:53,920 --> 00:25:59,920 Speaker 3: called Absent Pharmaceuticals in Brazil. We took their existing SAP system, 395 00:26:00,320 --> 00:26:04,200 Speaker 3: their ECC system, and instead of doing the big migration 396 00:26:04,359 --> 00:26:07,760 Speaker 3: that SAP wants them to do, we put the service 397 00:26:07,840 --> 00:26:13,560 Speaker 3: now over the top. We've now automated almost seventy percent 398 00:26:13,800 --> 00:26:17,480 Speaker 3: of all the manufacturing processes where they had human intervention, 399 00:26:18,119 --> 00:26:21,320 Speaker 3: and they're loving it. They went from an experiment to 400 00:26:21,400 --> 00:26:25,560 Speaker 3: the company's full position, and this is the direction they're going. 401 00:26:25,640 --> 00:26:28,719 Speaker 3: Instead of the big upgrade migration, which really wasn't going 402 00:26:28,760 --> 00:26:31,520 Speaker 3: to provide any value. It wasn't going to change the game. 403 00:26:32,119 --> 00:26:36,480 Speaker 3: We're changing the game with this new agentic AI across 404 00:26:36,520 --> 00:26:38,520 Speaker 3: the top. It's really exciting you are. 405 00:26:38,840 --> 00:26:41,800 Speaker 1: But as the world goes sort of cloud night, of 406 00:26:41,840 --> 00:26:44,800 Speaker 1: which most companies will end up there, what does that 407 00:26:44,840 --> 00:26:45,720 Speaker 1: mean for you guys. 408 00:26:45,880 --> 00:26:49,399 Speaker 3: It was interesting in our panel sessions yesterday with a 409 00:26:49,400 --> 00:26:53,640 Speaker 3: lot of the biggest companies that you can imagine across 410 00:26:53,720 --> 00:26:58,280 Speaker 3: the ANZ market, it really came out that SAS is 411 00:26:58,359 --> 00:27:03,160 Speaker 3: dead and that was you know, it's shocking. It's we're saying, well, 412 00:27:03,240 --> 00:27:06,040 Speaker 3: the underlying ERP is dead, and they think SaaS is 413 00:27:06,080 --> 00:27:10,560 Speaker 3: dead because the whole model of software is changing. Everything 414 00:27:10,640 --> 00:27:14,119 Speaker 3: is about data. Now. Data is the gold, and so 415 00:27:14,760 --> 00:27:17,879 Speaker 3: it's not about the number of users, it's not about 416 00:27:17,880 --> 00:27:20,080 Speaker 3: how you know, Oh, let's see the turnover of your 417 00:27:20,240 --> 00:27:24,480 Speaker 3: organization and price it that way. Everybody wants to meter 418 00:27:24,640 --> 00:27:27,480 Speaker 3: the data. The data is moving from point A to 419 00:27:27,560 --> 00:27:30,800 Speaker 3: point B, to point C to point D. Everyone wants 420 00:27:30,880 --> 00:27:33,320 Speaker 3: to get in on figuring out how do I get 421 00:27:33,359 --> 00:27:36,000 Speaker 3: a piece of the action. So everyone wants to set 422 00:27:36,080 --> 00:27:39,560 Speaker 3: up tall boots so that they can collect a toll 423 00:27:39,920 --> 00:27:44,480 Speaker 3: as data moves from place to place. It's a fascinating change, 424 00:27:44,560 --> 00:27:48,320 Speaker 3: and we don't even understand how to cost. What's this 425 00:27:48,400 --> 00:27:51,000 Speaker 3: going to look like If everyone's putting a toll booth 426 00:27:51,880 --> 00:27:54,520 Speaker 3: and it's my data, but you want you want to 427 00:27:54,600 --> 00:27:57,400 Speaker 3: charge me for pulling my own data from from here 428 00:27:57,440 --> 00:27:57,800 Speaker 3: to there. 429 00:27:58,640 --> 00:28:00,200 Speaker 4: We don't really even understand that. 430 00:28:00,320 --> 00:28:01,840 Speaker 3: Yeah, but it's a whole new world. 431 00:28:01,960 --> 00:28:05,280 Speaker 1: Already we're getting bill shock in the cloud for data 432 00:28:05,280 --> 00:28:07,680 Speaker 1: egress and all of that. So that is a concern. 433 00:28:08,359 --> 00:28:12,800 Speaker 1: You've You've had lengthy court battles with Oracle over how 434 00:28:12,800 --> 00:28:16,280 Speaker 1: you deliver support. So this is challenging to that vendor 435 00:28:16,320 --> 00:28:18,959 Speaker 1: in particular. So I think you've resolved a lot of 436 00:28:19,000 --> 00:28:23,080 Speaker 1: that now, but how do you reassure prospective clients here 437 00:28:23,119 --> 00:28:25,639 Speaker 1: in New Zealand who might be worried about sort of 438 00:28:25,680 --> 00:28:29,159 Speaker 1: being caught in the crossfire between Remeny Street and and 439 00:28:29,160 --> 00:28:30,320 Speaker 1: and Oracle or SAP. 440 00:28:30,640 --> 00:28:33,639 Speaker 3: The only vendor we ever went to court with was 441 00:28:33,760 --> 00:28:40,080 Speaker 3: Oracle for many years. We just settled the Oracle litigation. Uh, 442 00:28:40,240 --> 00:28:43,040 Speaker 3: you know, terms are seen and available, but there was 443 00:28:43,080 --> 00:28:47,240 Speaker 3: no findings of infringement, there was no no admissions of 444 00:28:47,280 --> 00:28:51,920 Speaker 3: any wrongdoing. It's done, uh, and we've moved forward. And 445 00:28:52,320 --> 00:28:55,640 Speaker 3: this was a you know, again, these were related to 446 00:28:55,760 --> 00:28:59,920 Speaker 3: third party support on very specific Oracle platforms. But the 447 00:29:00,160 --> 00:29:04,160 Speaker 3: reality is third party support is legal. There is no 448 00:29:04,280 --> 00:29:06,920 Speaker 3: other challenges that have ever been raised in the near 449 00:29:07,000 --> 00:29:10,440 Speaker 3: twenty years and we've been doing this, so obviously we're 450 00:29:10,520 --> 00:29:14,040 Speaker 3: very confident. When you've got governments and you've got people, 451 00:29:14,160 --> 00:29:17,560 Speaker 3: again thousands of customers around the world that have done this, 452 00:29:18,320 --> 00:29:22,280 Speaker 3: from your Hyundais in one hundred countries to the largest 453 00:29:22,360 --> 00:29:26,240 Speaker 3: of organizations. So this is not a new concept. This 454 00:29:26,360 --> 00:29:30,960 Speaker 3: is a proven concept, proven savings, proven value. And this 455 00:29:31,160 --> 00:29:34,280 Speaker 3: is just a really exciting time when you're talking about 456 00:29:34,280 --> 00:29:39,160 Speaker 3: putting AI over the top of existing systems, and you know, 457 00:29:39,320 --> 00:29:42,000 Speaker 3: obviously a little scary in the labor markets, and you know, 458 00:29:42,040 --> 00:29:45,640 Speaker 3: what's this mean for people's jobs that were these agents 459 00:29:45,680 --> 00:29:49,520 Speaker 3: are getting so smart and they're able to make decisions, 460 00:29:50,360 --> 00:29:53,600 Speaker 3: and really it's really something to watch. It's almost science 461 00:29:53,640 --> 00:29:55,280 Speaker 3: fiction in so many ways. 462 00:29:55,520 --> 00:29:59,120 Speaker 1: So, Joe, what's the pitch when you come across here? 463 00:29:59,120 --> 00:30:03,440 Speaker 1: For instance, as talked about government clients, We've got a 464 00:30:03,480 --> 00:30:07,240 Speaker 1: government here that has a cloud first policy, so it's 465 00:30:07,280 --> 00:30:11,360 Speaker 1: pushing everything to the cloud, which here effectively means sending 466 00:30:11,360 --> 00:30:13,400 Speaker 1: it to Azure with a little bit of a WS 467 00:30:13,400 --> 00:30:16,560 Speaker 1: and Google Cloud maybe and a little bit in private 468 00:30:16,600 --> 00:30:20,480 Speaker 1: cloud if it's really sensitive for data sovereignty and military 469 00:30:20,480 --> 00:30:26,000 Speaker 1: applications and that sort of thing. So is government prospective 470 00:30:26,520 --> 00:30:30,560 Speaker 1: client for you here, because they're all struggling with cut 471 00:30:30,600 --> 00:30:36,240 Speaker 1: budgets and legacy systems that they will need to upgrade. 472 00:30:36,280 --> 00:30:39,280 Speaker 1: But essentially, the pitch is the same to a government 473 00:30:39,320 --> 00:30:42,080 Speaker 1: agency is you can sweat that asset for a bit 474 00:30:42,120 --> 00:30:44,120 Speaker 1: longer and run AI over the top of it. 475 00:30:44,360 --> 00:30:47,800 Speaker 4: And that's true and I'm seeing that, you know in 476 00:30:48,280 --> 00:30:52,840 Speaker 4: Auckland City Council where they've been trying to manage the budgets. 477 00:30:52,840 --> 00:30:56,760 Speaker 4: I'm seeing it in Wellington where you know the current 478 00:30:56,880 --> 00:31:00,440 Speaker 4: government is trying to optimize its cost structures. And to 479 00:31:00,480 --> 00:31:03,360 Speaker 4: be fair, there is just not enough money to go 480 00:31:03,560 --> 00:31:08,000 Speaker 4: round in all the government departments and to follow that 481 00:31:08,120 --> 00:31:13,000 Speaker 4: traditional path. And the real question for the ministers and 482 00:31:13,040 --> 00:31:16,760 Speaker 4: the governments there is can I do and give a 483 00:31:16,840 --> 00:31:24,640 Speaker 4: customer or a citizen a better facility and service at 484 00:31:24,640 --> 00:31:29,440 Speaker 4: a cheaper cost that doesn't put too much pressure on 485 00:31:29,480 --> 00:31:32,680 Speaker 4: the budget. And we know that New Zealand's been in 486 00:31:32,720 --> 00:31:35,240 Speaker 4: a bit of pain and continues to be in the 487 00:31:35,320 --> 00:31:38,720 Speaker 4: pain and in the interest rates, and you're seeing the 488 00:31:38,800 --> 00:31:45,280 Speaker 4: consents are still low, etc. And given that scenario one, 489 00:31:46,000 --> 00:31:48,840 Speaker 4: you've got to minimize the cost of just running the 490 00:31:48,880 --> 00:31:52,280 Speaker 4: business as it is or running the technology. And that's 491 00:31:52,360 --> 00:31:58,240 Speaker 4: where Rymney is really good at supporting the existing at 492 00:31:58,280 --> 00:32:02,280 Speaker 4: a far better rate than going through an OEM. Then 493 00:32:02,360 --> 00:32:06,960 Speaker 4: the ability to optimize all the systems and get them 494 00:32:07,360 --> 00:32:12,480 Speaker 4: supported in a better fashion is another tenet of Rimney Street. 495 00:32:12,960 --> 00:32:17,760 Speaker 4: And then finally, after you've consolidated and supported and optimized 496 00:32:17,840 --> 00:32:22,400 Speaker 4: freeing up the budget to either allocate towards other goods 497 00:32:22,480 --> 00:32:26,959 Speaker 4: or services or to reinvest in what I call agentic 498 00:32:27,560 --> 00:32:33,080 Speaker 4: AI and building on gives you a speed and cost 499 00:32:33,120 --> 00:32:38,040 Speaker 4: efficiency that is far more superior than the traditional approach. 500 00:32:38,640 --> 00:32:42,000 Speaker 4: And that's why I'm saying that you're not really kicking 501 00:32:42,040 --> 00:32:45,600 Speaker 4: the can down the road on innovation if you stay 502 00:32:45,760 --> 00:32:50,400 Speaker 4: on your traditional ERP. What you're doing is taking an 503 00:32:50,400 --> 00:32:55,600 Speaker 4: alternative path to innovation such that you quarantine and quarterize 504 00:32:55,720 --> 00:32:59,520 Speaker 4: and make that the most efficient databases it can be, 505 00:33:00,120 --> 00:33:04,680 Speaker 4: and redeploy the funds to a smarter, quicker way of 506 00:33:04,720 --> 00:33:09,400 Speaker 4: deploying innovation than the traditional path. And that's that's the 507 00:33:09,400 --> 00:33:10,120 Speaker 4: big difference. 508 00:33:10,320 --> 00:33:12,400 Speaker 1: Well, I think that's something that's going to resonate with 509 00:33:12,520 --> 00:33:16,280 Speaker 1: you know, Judith Collins, our Minister for digitizing Government here 510 00:33:16,280 --> 00:33:19,400 Speaker 1: in New Zealand, who is tasked with you know, they're 511 00:33:19,400 --> 00:33:22,000 Speaker 1: going to introduce a digital driver's license for instance, and 512 00:33:23,200 --> 00:33:26,480 Speaker 1: all of the stuff is great and needed, but initially 513 00:33:26,800 --> 00:33:28,520 Speaker 1: you're thinking how much is this going to cost us? 514 00:33:28,520 --> 00:33:30,960 Speaker 1: If they can you know, we have a database of 515 00:33:31,040 --> 00:33:33,760 Speaker 1: driver licensed data. If we can use AI agents or 516 00:33:33,840 --> 00:33:37,080 Speaker 1: something to interrogate that database, that's going to save money, 517 00:33:37,160 --> 00:33:39,640 Speaker 1: but just finally seth for you. Where do you see 518 00:33:39,760 --> 00:33:43,920 Speaker 1: Reminy Street in a decade at its thirtieth birthday, Is 519 00:33:43,960 --> 00:33:46,800 Speaker 1: it still going to be fighting the support cost battle, 520 00:33:46,880 --> 00:33:49,520 Speaker 1: or do you see the company moving more deeply into 521 00:33:50,120 --> 00:33:54,800 Speaker 1: this AI driven IT architecture, becoming the company that specializes 522 00:33:54,840 --> 00:33:57,320 Speaker 1: in the sorts of agents and technology you can use 523 00:33:57,400 --> 00:33:59,480 Speaker 1: to get get the best out of those systems. 524 00:33:59,680 --> 00:34:04,520 Speaker 3: Well, I think our smartpath methodology, which is cut the cost, 525 00:34:04,600 --> 00:34:07,720 Speaker 3: stop doing things you don't need to do. It's very pragmatic. 526 00:34:08,320 --> 00:34:11,480 Speaker 3: That's what creates the people time and money freed up 527 00:34:11,800 --> 00:34:14,759 Speaker 3: to either again drop to the bottom line in savings 528 00:34:15,400 --> 00:34:18,200 Speaker 3: or drop some to the bottom line and invest some 529 00:34:18,320 --> 00:34:21,160 Speaker 3: in innovation. And by the way, you know, we do 530 00:34:21,239 --> 00:34:23,520 Speaker 3: governments all over the world. We've got a whole of 531 00:34:23,560 --> 00:34:27,720 Speaker 3: government agreement in Australia where we're supporting I think nearly 532 00:34:27,760 --> 00:34:31,440 Speaker 3: a dozen different agencies already. We've got an agreement with 533 00:34:31,520 --> 00:34:34,359 Speaker 3: the government in New Zealand, and I believe we have 534 00:34:34,400 --> 00:34:39,520 Speaker 3: two agencies already in New Zealand that are using Ramini services, 535 00:34:39,800 --> 00:34:43,120 Speaker 3: as well as many in the private sector. And so 536 00:34:43,719 --> 00:34:47,680 Speaker 3: it really is popular for governments and governments are coming 537 00:34:47,719 --> 00:34:50,920 Speaker 3: on board is what Joe said. They're looking for ways 538 00:34:50,960 --> 00:34:54,200 Speaker 3: to deliver more value to constituents. This is a really 539 00:34:54,239 --> 00:34:58,640 Speaker 3: tough thing. It's always tough to cut budgets, especially in government. 540 00:34:58,719 --> 00:35:01,160 Speaker 3: People don't like to give up what they have. But 541 00:35:01,200 --> 00:35:04,359 Speaker 3: when we can take the current spend and make it 542 00:35:04,400 --> 00:35:07,160 Speaker 3: more efficient, where we can drive, we can pay for 543 00:35:07,239 --> 00:35:10,600 Speaker 3: innovation out of the existing spend and so we can 544 00:35:10,719 --> 00:35:14,360 Speaker 3: make it a much better experience and we can deliver more. 545 00:35:14,719 --> 00:35:18,080 Speaker 3: And when we get to thirty years, I think we're 546 00:35:18,120 --> 00:35:19,760 Speaker 3: going to be an innovation leader. 547 00:35:20,440 --> 00:35:20,920 Speaker 1: We are the. 548 00:35:20,880 --> 00:35:23,600 Speaker 3: Guys who figure out how to pay for it, not 549 00:35:23,800 --> 00:35:27,160 Speaker 3: come in and say, oh, give us a billion dollars 550 00:35:27,239 --> 00:35:29,359 Speaker 3: and we'll see what happens in a few years. Those 551 00:35:29,400 --> 00:35:33,239 Speaker 3: projects are dead. Nobody wants to do that, not in 552 00:35:33,280 --> 00:35:36,480 Speaker 3: the government, not in the private sector. The way that 553 00:35:36,520 --> 00:35:39,359 Speaker 3: we're approaching this is saying, look, we're going to pay 554 00:35:39,400 --> 00:35:42,320 Speaker 3: for that innovation because we're going to get smart about 555 00:35:42,360 --> 00:35:46,120 Speaker 3: how we're spending today. That budget money is in there, 556 00:35:46,520 --> 00:35:50,000 Speaker 3: It is in the existing budget. We just have to 557 00:35:50,080 --> 00:35:53,960 Speaker 3: spend it better and then we can reallocate that spend 558 00:35:54,040 --> 00:35:57,799 Speaker 3: and do both. We can deliver savings and we can 559 00:35:57,920 --> 00:35:58,880 Speaker 3: deliver innovation. 560 00:35:59,200 --> 00:36:02,640 Speaker 1: Yeah, well a compelling proposition. You're on your way to 561 00:36:02,640 --> 00:36:05,759 Speaker 1: New Zealand, so hopefully it resonates with some of our 562 00:36:06,000 --> 00:36:11,120 Speaker 1: IT decision makers here. Happy birthday, congratulations on your twentieth anniversary, 563 00:36:11,239 --> 00:36:14,239 Speaker 1: and thanks both of you for coming onto Business of Tech. 564 00:36:14,320 --> 00:36:16,040 Speaker 3: Our pleasure, thanks for having us. 565 00:36:22,080 --> 00:36:26,320 Speaker 1: So thanks to Seth Ravin and Joe Lecandro from Remeny Street. 566 00:36:26,320 --> 00:36:30,080 Speaker 1: A really interesting point of differentiation from most of the 567 00:36:30,120 --> 00:36:32,799 Speaker 1: tech vendors I talk to, who really want to get 568 00:36:32,840 --> 00:36:36,200 Speaker 1: you to the cloud as quickly as possible, basically so 569 00:36:36,239 --> 00:36:38,920 Speaker 1: they can lock in your business. Remeny Streets approach is 570 00:36:38,960 --> 00:36:41,840 Speaker 1: actually quite refreshing. You know, what is the future of 571 00:36:41,920 --> 00:36:45,920 Speaker 1: these big, monolithic enterprise resource planning systems in the world 572 00:36:46,040 --> 00:36:50,120 Speaker 1: of AI is software as a service, something that New 573 00:36:50,239 --> 00:36:52,840 Speaker 1: Zealand companies have done very well out of on the 574 00:36:52,880 --> 00:36:55,839 Speaker 1: way out as well. Let me know what you think. 575 00:36:55,920 --> 00:36:59,080 Speaker 1: Get in touch with me on Peter at Petergriffin dot 576 00:36:59,120 --> 00:37:02,440 Speaker 1: Co dot MX, or you'll find me working on LinkedIn, 577 00:37:03,120 --> 00:37:06,280 Speaker 1: stream the Business of Tech on iHeartRadio or your favorite 578 00:37:06,280 --> 00:37:09,919 Speaker 1: podcast app, and find the show notes at Businessdesk dot 579 00:37:09,920 --> 00:37:13,359 Speaker 1: co dot NZ. Just look in the tech section next 580 00:37:13,360 --> 00:37:17,200 Speaker 1: week Australia's former Chief Science Advisor and the big bets 581 00:37:17,320 --> 00:37:20,799 Speaker 1: Ozzie has made on advanced technologies in recent years and 582 00:37:20,840 --> 00:37:23,840 Speaker 1: the potential for us to be smart in doing exactly 583 00:37:23,880 --> 00:37:26,799 Speaker 1: the same. That drops next Thursday. I'll catch you in