Building Aera Technology: The Future of Decision Intelligence with Fred Laluyaux

Summary

Fred Laluyaux, CEO of Aera Technology, explores the rise of decision intelligence and the concept of the “self-driving enterprise.” Fred breaks down why traditional enterprise systems are no longer equipped to handle the speed, scale, and complexity of modern business—and how AI is evolving from a tool for insights into a system that can make and execute decisions autonomously.

Takeaways

AI is shifting from insights to action
The future is decision-making at scale
Traditional enterprise workflows are too slow and siloed
The “self-driving enterprise” is becoming a reality
Speed is now a competitive advantage
The enterprise software playbook is being rewritten
AI is changing how decisions happen—not just who makes them
New roles like “decision architects” are emerging

Soundbites

“AI shouldn’t just give you insights—it should take action.”
“We’re moving from people making decisions to machines executing them.”
“The real shift is from dashboards to decisions.”

Chapters

01:29 The Birth of Decision Intelligence
05:02 Aera's Unique Approach to AI and Decision Making
05:52 Aero's Unique Approach to AI in Enterprises
08:17 Current Focus and Market Positioning
11:04 Ideal Client Profile and Market Expansion
13:50 Challenges in Growth and Scaling
16:21 Shifting Dynamics in Technology Adoption
17:49 The Acceleration of Deployment and Implementation
20:53 Interdepartmental Collaboration and Agility
22:01 Scaling Challenges and Unique Value Proposition
26:36 Growth Targets and Strategic Focus
31:42 Trends in AI and Decision Intelligence
34:54 Looking Ahead: Success Metrics for the Future

Video

https://youtu.be/Ub9RmvLGToM

Transcript

SPEAKER_00 0:20

Welcome to AI Speed, the show where AI powered companies talk about what actually works in the market right now. Business doesn't move at internet speed anymore, it moves at AI speed. And the people who figure it out how to turn models into money will own the next decade. I'm Evan J. Chelten, the founder of Luxamer and growth partner to high-performing brands. And today I'm thrilled to be joined by Fred Young, the co-founder, president, and CEO of Aero Technology. Fred is a pioneer in enterprise AI and creator of the decision intelligence category in helping global organizations transform how they operate by automating and optimizing decisions at scale. And his work is redefining how business is moving from insight to action in real time. Fred, thanks so much for being here. Thanks for having me event. Glad to be here. Absolutely. So you spent your career building enterprise software companies, including scaling Annaplan to a billion-dollar valuation. What was the pitiful insight that led you to start Air Technology and focus specifically on decision intelligence?

SPEAKER_01 1:29

The story of AR actually in my head started even before Anaplan. Back in 2010 when I was working with ACP, I saw a big problem coming in front of us, and it's pretty simple to understand, right? You think about how companies make and execute thousands of decisions every day in order to operate their business. What do I make? What do I procure? How do I ship? How do I recognize? How do I promote? How do I advertise? Those are, you know, people think about a strategic plan, which is great, but then you have all these decisions that you have to make. And in 2010, I wrote a paper around the fact that, you know, ERPs, transactional systems have allowed the world to go flat, giving large organizations the ability to control their business. But making decisions on top of that, that bedrock of transactional system was still a hustle. It was still very difficult. You have a large pyramid of people organized, you know, 10, 11, uh level deep, uh organized by silos with a bunch of bespoke solutions. And uh and they're scrambling to make and execute decisions. If you're working in one of those enterprises, you know what I'm talking about. You spend your life in email and spreadsheet and collaboration platforms. And the problem that I identified back when, it's almost 15 years, 16 years ago, is that the digitization of our economy was gonna drive a continuous acceleration of business cycles. We're now thinking in quasi-real time, where 10, 15 years ago, you were thinking weeks, in quarters, in months, but not in real time. The second was the digitization was gonna drive a consumerization of our economy, a personalization of offering, driving decisions down to a very fine grain. And the last element was a complexification of our networks. So, in my mind, if you combine volume, complexity, and speed, you result with an explosion in a number of decisions that a company has to make to remain competitive. And when I kind of balance that with that big pyramid of people, I realized that the model wasn't going to work. And every software that we were building was just an iteration, a step better from the previous one. Now it's client-server. Oh, look, now it's internet, now it's cloud. It's great. But it doesn't change the paradigm that everything is based on people working, collaborating, making decisions. So we saw a big problem and we saw a big opportunity to solve that problem by building a technology that would fundamentally allow companies to go from having people making and executing thousands of decisions every day, supported by tools, machines, data systems, and so on and so forth, to a world where machines could actually make and execute those decisions guided by people. So we call that again, June 19, 2017, when we launched, we call that welcome to the self-driving enterprise. We kind of use the analogy with the self-driving car, and that's what we've been building ever since. So tackling that huge problem, and I think the impact was, and now we're realizing it, was is still very important, right? Because if you can remove the human-based inefficiencies, human-based inefficiencies, right? Silos and so on and so forth, from our from the way we we make and we ship and we distribute and we promote our products, but you got a much more efficient model that you know saves on energy, saves on carbon, help reduce waste of raw material, delivers better services to your clients. So that's fundamentally what we were trying to resolve.

SPEAKER_00 5:02

Yeah, definitely. And so what makes Air's approach unique in the AI and enterprise software space, particularly in how you're connecting data, intelligence, and execution into a single system?

SPEAKER_01 5:15

Well, if you if you well, we we purpose-build this platform from the ground up with that vision in mind. So the question we ask ourselves is how do I digitize decisions? And and you know, starting with what we have, which is a bunch of data, internal and external, structured and unstructured, coming and thrives, you know, you know, in a system. And then you have a decision-making process which is in people's head, right? People know how to decide. Now, companies, especially large companies, have processes, have controls. But at the end of the day, if I decide to increase or rebalance inventory from one place to the other, it's my job as a planner to actually do it.

SPEAKER_00 5:53

So, what makes ERA's approach unique in the AI enterprise software space, particularly in how you're connecting data, intelligence, and execution into a single system?

SPEAKER_01 6:05

Yeah, so if you if you think about digitizing decisions, right, there you need a lot of things to connect together. The first thing that I would say is you need 100% of the information that is required to make a decision digitally to be available in a normalized data model. Now that data is going to be structured, unstructured, internal, external, you're capturing market signals. So the first thing that we had to do is enable that process of bringing continuously cleaning, validating the data into that on ontology. The second thing that you need, just like a human brain, you need all the capabilities to project, to predict, to optimize, to allocate, to do all the math that is required when you're making a decision. And then you need a level of orchestration, which is really the reasoning. What up, why, how do I resolve a specific problem? My forecast shows that there is a risk of stalkout for this specific customer. What can I do? And there you leverage two different technologies. You can use deterministic processes, rules-based approach, which works very well, very fast. Or you can use agentic reasoning and industry content to actually come up deeper into root cause analysis and deep reasoning. And then the next level that you need is a level of engagement. Because you need that system that is not meant to improve the personal productivity of a person, but to improve the performance of the company of an overall process. So you need the system to engage with the users, asking questions. I have a problem here. I need a human input. So I need to engage with that operator and ask the question in a very clear way. I need to engage with your data. I need to engage with your systems to execute the decisions that are made with and by the system. And I need to engage with your agentic environment because you built already some agents that the system needs to leverage as it's processing those decisions. So, you know, the uniqueness is the ability to bring in a single environment that's you know designed for and users to configure easily the data, the intelligence, the automation, the engagement in a single environment.

SPEAKER_00 8:16

Wow, that is really cool. So, where are you focusing most of your energy right now as CEO?

SPEAKER_01 8:23

Uh, we're in a market that's just been recently categorized and defined by Gottner. We're actually the leader in the magic quadrant for decision intelligence platform that's like two months old now. So there is a big boost and growth in the business, which is super exciting within the core industries that we worked in so far: FMCG, life sciences, oil and gas, discrete manufacturing. But we're now seeing an expansion of decision intelligence across industries. And we started also in terms of line of businesses focusing on operations, supply chain procurement. But we're seeing decision intelligence now also being leveraged around demand creation, sales, finance. So we're kind of working with this cube, which had a number of dimensions, and think about it like it's increasing in terms of line of business, in terms of industries. So that's one part is scaling the business. And as a CEO, as I grow the top line, I want to make sure that I identify and leverage my own technology. So we have era on era to really augment and automate most of the decisions that we need to make to operate our business. So, first is really on the offer, making sure that we have the right offer for all those different LOBs and industries. Second is really making sure that we drink our own champagne. I think in the US you like to say we eat your own dog food. I prefer to drink my own champagne. That's the French guide. But we drink our own fair taste. Exactly. Which is really, really exciting because we're leveraging this technology to do things you mentioned kindly before. It's not my first rodeo, but you grow a company from X to 2X, usually you kind of double the size of the team. And here we we don't have to do that. And we get a lot sharper, a lot more intelligent about running our own operations. And I would say the third thing is keeping up with the tech, right? So being a step ahead and two or three chapters of the book ahead. And right now it's the first time in my career that I feel like our engineers are ahead. They're moving faster than marketing, then sales, than enablement, then support. Usually they're ahead and we're waiting for engineering to deliver the next release. And for the last few months, we're seeing a reversal of that process where engineering is ahead, is pushing incredibly fast. We are leveraging all the great technology to write code faster. So we as a company have to adjust to seeing engineering ahead of everything else, right? So I'm not I'm not holding back, I'm not letting the engineers and our co-founder Sharik do his incredible magic with the product, but it's a as I said, it's I've done this for a long time. And it's the first time that we're playing catch up almost with the product.

SPEAKER_00 11:04

That's incredible, too.

SPEAKER_01 11:05

Yeah, it's kind of fun.

SPEAKER_00 11:07

Yeah, definitely. So who do you serve best? What's the ideal enterprise profile that gets the most value from Aerosplatform?

SPEAKER_01 11:16

So, you know, I've done this a few times, building new categories. It's always the same process, but this time it's accelerating. By what I mean by process is you go after uh the tip of the spear, the companies who have the means to innovate. Well, the technology might not be fully ready. And that was the case with us. We pioneered this technology, working with great companies, very large organizations who saw the need. My vision as a CEO when we started the company is let's go after the best in class, the most advanced companies in their domain. Think about supply chain, you're gonna go after life sciences, you're gonna go after a CPG. So we pioneered this technology with them. Very complex, very large organization, vast amount of data, vast amount of decisions. We've digitized more than 50 million decisions so far. And then you start the market matures, the category gets defined, and then you start going, as I explained, across industries. We signed our first utility or first mining, first uh public sector and um universities. So expanding across industries, but you're still kind of working with the largest companies. And right now we're seeing now smaller companies, you know, 500 million in revenue, a billion in revenue, that are now embracing this. And what's super interesting about them is that they want to leapfrog the traditional model, which is you know, a three-tier architecture with the system of records, your ERPs. Then you have a bunch of systems of differentiations, your planning tool, your transportation management tool, your warehouse management tool. They have all these tools, and then they put a layer of intelligence on top, usually analytics. And those newer, fast-growing companies, they're already thinking about collapsing that stack. They want a smarter system of record and a single system of intelligence on top to do the work. They're already thinking with decision intelligence in mind. They're already thinking about how to not build that pyramid. This is so deep that I explained before, but a more nimble and flatter organization. So we're seeing that momentum right now picking up, which is super exciting because those are the things we've been thinking and talking about for many, many years. Technology was not necessarily ready. The mindsets were not necessarily ready, but there's been clearly a shift in mindsets, in technology readiness, and in appetite to move by a much broader and deeper set of technology comp uh tech companies thanks to the technology. And that's really kind of in the last the last six to twelve months. Yeah, yeah, that's moving really fast.

SPEAKER_00 13:52

So, what would what would you say has been your biggest challenge growing era this past year?

SPEAKER_01 13:57

It's hard to pinpoint to a single challenge, Evan, when you're doing what I do. There's many challenges. Um look, we're we're doing well right now. So I think the challenges were in the past when the market was not necessarily ready, when our tech was not necessarily ready, when you were working with pioneers and the big challenges in very large organizations. You start working with a small group of leaders who get your vision and are willing to bet the ranch and their career on making it, and then people move on, and then you get to another team that were not invented there, and you have to resell and re-explain, especially if those changes happen during the implementation or the early adoption phase. Once it's anchored, it doesn't move. But but it's been a challenge to kind of re-explain and resell to existing accounts that we were working with. But this is kind of like in the past now, because you see IT now really starts to understand decision intelligence and and its impact. I think for us right now, the challenge is scaling and scaling intelligently. As I said before, how do we leverage our technology to enable the company to become so smart that I don't need to become bloated and fat when I can be super agile and smart, right? So that's what excites me right now about the business, keeping up with, as I mentioned to you before, keeping up with innovation and making sure that all the parts of the companies are kind of following and driving in unison. And right now I've got one part of the company playing drums a little faster than everybody else. So everybody has to kind of catch up and make sure that we are providing a coherent story with, and there's there's things that are evolving in our industry quite well, right? Technology is evolving so fast that thinking that you, as the vendor of the technology and the vision, you know everything and you all hold the content and you wisely distribute it, this is over, right? Today you provide the technology, there is viral adoption, you need to bring that community of users talking to one another, exchanging. So our job is changing to become more of an enabler of that exchange. Of course, we continue to provide new ideas, content, experience, you know, agentic libraries and all those good stuff. But if you really want to move as fast as the technology is moving, you got to bring the network effect with your customers, your partners. So shifting from we know it all and we distribute and the knowledge to we are enabling the change with our technology, but we're also enabling that community to work together, which is super exciting. We're also building, for example, a new academy because decision intelligence creates new roles in a company, right? You're gonna find new jobs like a decision architect, a decision analyst. These are new jobs. No one five years ago could say, I am a decision architect at Company X. It is the case today. Back to the point I was making, learning from our clients, and then with our clients, as I should say, and with our partner, and then we're releasing classes, a new academy on how to become a decision architect, how to become a decision analyst. What is the job? And so there's a lot of creation of content and you know, bringing bringing that together with our ecosystem, which is super exciting. Technology is still a giant part of what we do, but but you have to surround it with everything that that is required for a company to be successful fast. Because look, I've worked for you know in the different eras of enterprise software, and I remember, you know, oh, it's a year-long implement. Today, if you go and you tell a client that it's going to take a year, you're out before you even got a foot in. Right? We're talking weeks now to deploy an enterprise software solution that autonomously can make and execute decisions at scale. And when you say weeks, customers will say, can you make it in days? So this acceleration is everywhere. People know the immense power of LLMs. They use it every day. They're using it as a personal productivity. Now, to deploy that intelligence at scale at the enterprise process level, decision-making process level across the value chain, that requires a new set of thinking and technology, which is much more complex than allowing you or I to be more efficient with my emails or retrieving data more effectively or getting access to answers that I wouldn't have access before.

SPEAKER_00 18:21

Yeah, definitely. I'm really interested. You mentioned, you know, keeping up with engineering, um, you know, the different departments. Um, I'm curious how that affects you know departments like, say, marketing, for example. Like how do they keep up? You know, what what impact does that have and keeping up being able to even talk about what you're doing and spread the word? That to me is fascinating.

SPEAKER_01 18:46

It's a it's a it's a massive acceleration of the cycles, right? Normally in a company like this, you know, enterprise software, you have your yearly conference to bring all your users and you release your innovation, and you think, okay, maybe I'll do another release six months later, and you have time to plan. And of course, you're always clambering, you're always behind, you finish the night before, but you have time. Here, this cycle is shrinking. And it goes back to what I was saying in the introduction, right? The acceleration of business cycles. Well, we as a tech we as providers of technology have been professing that in the market for years, and now it's impacting us. So we have to bring the same tools that we're selling to our clients, so to speak, in terms of content creation alignment. We have to be a lot more agile and nimble. So a solution is you have to have a great team. Uh, we're lucky at ERA to have a fantastic team and folks that I've worked with for many, many years that know each other and that trust each other. When you have wings in your cell, everybody's aligned. So that helps a lot. But then it's it's you know, leveraging tools and technology internally to create content faster, to analyze things faster. And you just have to be smart. I mean, you have to be really, really sharp. And look, the days are long, um, but it's so super exciting. And and yes, I think we are we are now uh meeting more and often, like you know, literally, we're doing our product reviews much more frequently. We bring marketing in there, we decide faster. We just don't have the same amount of time that we had before. It's kind of at the end of the day, it's down to us. We were driving a car. Look, I had the the the the massive opportunity to build uh a SaaS software company in the heydays of uh of SaaS when it became a thing and cloud, when it became a thing with Anaplan. And we were we pushed really hard and we moved really fast. But this is ten times faster. You as the the pilot or you know the co-pilot, you have to be sharper and uh and have the experience and the trust and the confidence that that you know what you're doing. Because if you're left behind, you just I don't think you can catch up right now.

SPEAKER_00 20:52

Yeah, definitely. And and you also mentioned you're talking about being.

SPEAKER_01 20:58

I have one more thought, if I may. Sorry, just because I think it's important for everyone. The ability that we have to work super tightly with customers and partners. I mentioned that before, but it's more important than ever, right? Traditional product managers would meet with clients and have those sessions. Now it's everyday. Now it's like real-time feedback. And we learn something, it makes it to the product, we we we communicate around it. So that loop as well can only be viable if if it's inclusive of your ecosystem and not as a happy check, go to the conference, talk to some customers, and you know, now it's and the customers are a lot more involved themselves.

SPEAKER_00 21:43

Well, you were talking a bit about uh before about scaling, uh you know, being a challenge, obviously, and you know, looking to scale. Um maybe you could talk a little bit more about that. I'm interested in you know that side of the thing of what What you're talking about.

SPEAKER_01 22:01

Yeah, the challenges of scaling today's you I mean uh uh uh inside era but outside era in general is that the technology is moving very, very fast, right? You feel like you can be disrupted the next day. So you have to be very confident about your unique value proposition, about what it is that you do that is truly unique, that enables a level of transformation and execution in an enterprise like you know our giant customers. So you have to make sure that you truly understand that as the core to get the confidence to invest in your growth. Otherwise, you're kind of feeling frozen. And I meet a lot of entrepreneurs and younger companies and explain to me their business model. And every other time, not to say every time, I end up saying, uh, I wouldn't do that because this technology is gonna come in and disrupt you within a time that won't allow you to establish your value proposition in the market. You build your brand, build your customers, especially in our domain, which is large enterprise. Um, and um, so you got to really be very solid about what it is that you do that that's unique. For us, the recognition by Gottner as an example, it got lots of accolades, but the leader position in the magic quadrant, after a thorough process, is incredibly valuable and it defines our leadership in decision science, in decision engineering. So the market now understands what we're doing. When you've got this kind of validation and you understand your technology and you've got an incredible set of customers, then you can invest in your growth and be working with your board, with your investors, uh to put the right scale in front of the business. The challenge and the opportunity, which is incredibly exciting, is what the latest agentic and AI technology can provide to hypergrowth without hyper bloating your organizations. The models that have been working with for 20 years, the traditional SaaS model, with all the ratios. If you had a salesperson, you need to have a third of a pre-sales and you need to have a BDR, and you need to have this and you need to have that. So think about it as a pyramid. That pyramid is collapsing completely, right? We can digitize a massive amount of work. You have an RFP, you have large companies sending us those 50 pages documents. It used to be a job to really literally fill up that RFP. Now it's done in minutes, and soon you'll be able to do it on your own online. And of course, human supervision can be added if needed. You want to deploy the technology. It used to be that it's months and months of discussion and negotiation and tries, and we're going to get to a point pretty soon where you just go online and try. And we're talking about a hyper-scalable and a pride technology, customized. The whole customization will happen on its own. Pricing is super important as you scale, we're providing transparency, putting the consumption-based models in the hands of your clients. Scaling in 2026 is so different than scaling in 2012. I've got, as I said, I can write the playbook of scaling an enterprise software company in the cloud and even before the cloud. And that playbook is completely rewritten. And we have to write it. So it's the constant push internally for making sure that we think about this in the perspective of three years from now and not three years ago. If you allow me a minute, we had our kickoff a few weeks back, and uh I started my presentation, and we've been working on this for nine years, and I said, we're all fired, literally all fired. Yeah, like, oh, well, that's uh not very nice. And I said, now you think about why do I want to take this job at era today? Because things that we've tried three years ago that didn't work the way we want, the feedback we got from customer prospects, XYZ were not always positive because the market wasn't ready, because the technology wasn't ready. So you're fired. You have to re-y have to really re-hire yourself and think very deeply about I'm taking this now. I don't care about the history. What am I building now? How am I leveraging everything that's available to me in terms of access to data, to digital intelligence, to information, to networks, to communities to actually build a very intelligent and and hopefully profitable business, right? Because I think if you if you get that and you see it today with some of the companies that are leading the you know the AI market, the level of profitability is quite remarkable.

SPEAKER_00 26:36

So, what are your main growth targets for this year for era?

SPEAKER_01 26:43

Well, there's there's multiple dimensions. Obviously, you know, we're doubling the top line. That's quite simple. Um simple conceptually, it's always hard to do. Um we're doing it, yeah, yeah. Look at this arrogant guy. We're doubling. No, it's it's very difficult to do, but we're doing it by providing also new routes to market. Gonna, you know, introducing new ways, flexible, faster way for customers to get on the platform and and try it and work with it and expand. That's one you know vector for growth. And the other one I touched on before, which is really now taking decision intelligence, this self-driving enterprise and expanding across the value chain. Just if I if I stop on this for a second, if you think about the decisions that a company makes, there a lot of them are still inspired by the old world, right? So I'll give you a very simple example. You if you're selling consumer packaged goods until not that long ago to promote your product, you used advertising and coupons and point-of-sell flash cells and all this kind of good stuff. Today, the vast majority of your media spent is digital. That means you can activate and deactivate it on one click. You couldn't do that before. You would launch a process, put some ads on the freeway and whatever you want, and then measure after whether it had an impact or not. Today I can see if a digital media ad for that specific SKU, right, product on Twitch in East Cleveland within a square mile is performing. The next question: do I have inventory in the store? Do I have inventory in the warehouse? And if I predict that inventory is not going to be there, then stop spending. The point I'm trying to make is new decisions today are born in digital. They were not even conceivable uh 10 years ago. So you have to have a digital solution to answer. And what it allows you to do is connect dots that were not connected before. The media planning tool was doing its job, the supply chain team was doing its job, and they would not meet. Now it's a single process. So the growth from ERA comes from the ability to enable that end-to-end value orchestration. That sounds very fancy, but it means connecting dots logically that were not connectable before.

SPEAKER_00 29:07

Yeah, definitely. And so which areas of the business are you most focused on scaling new industries, deeper deployments within existing clients, or expanding globally? Are you thinking about each of these in different ways? Big focus.

SPEAKER_01 29:23

I mean, we have it, we have the the geographical footprint that we need right now, and business has gone flat. So I don't think we need to put many more offices. A bit more probably in uh in Asia. Um we have presence in Australia and Singapore. I think there are a couple of offices that we may want to open in in other countries. No, I think look, the and the land and expand model is kind of working on its own. So always focusing on customer adoption. These are new technology and new approaches. So we've got to be there with our partners to help our clients be successful. But it's, you know, the flywheel is starting to happen. I think for me, right now, the biggest opportunity is to take our brand. And look, historically, we've been selling a lot to the chief operating officer, to the business side of an enterprise, to the chief supply chain officer, to CFOs. Now we're pushing a little bit more to the CIOs and to the digital part. They were not necessarily ready, and I think they are now. So a big addition to what we do, not replacement, is focusing more on the IT side. We're going to be doing some of the big events, you know, IT symposiums and stuff like that, which we didn't do before. So opening to IT with an objective to really help now scale decision intelligence across the enterprise, right? Going beyond the line of business that we've been serving initially. And as I said to you before, opening other industries. There is so much that we do. We got an incredible customer, which is the largest online university in the United States called the Western Governor University. They're deploying decision intelligence for a magnificent use case that helps them reduce students' dropout, and they've got incredible results. How do I take that success that is theirs, not ours, but with our technology, and help you know bring that to other universities as an example? We've got a lot of successes in one industry. How do we expand? That's the next challenge. But that's something that we've done before in past lives that's super exciting, requires some rigor, requires some hard work. But the access to the information today, the access to everything is so easy that we have a shot to try to gobble a lot more than we were able to do in the in the past few years.

SPEAKER_00 31:36

Absolutely. So what trends are you seeing in AI and decision intelligence that excite you the most right now?

SPEAKER_01 31:42

Well, in AI, DI is a category of AI, right? So decision intelligence is a category of AI. In AI in general, I think the the power of, I'm going to open an open door or push an open door here. Everybody knows that. But I think the the amount of power and the quality of the LLMs that we can leverage today is incredible. That level of intelligence for what we do is actually reached a level of performance that I don't need it to be better. We have what we need for the reasoning that is required to run decision intelligence. We can get to uh, you know, cloud version 10 and Chat GPT version 11. I don't really care. We have enough intelligence today, and it moved really fast over the last three years. So I think what those technologies can do and will continue to do is absolutely remarkable. The level of autonomy you can get is phenomenal. As far as DI is concerned, I think it's the speed at which it can now be deployed. Uh, that's absolutely remarkable. We're we're releasing technology that allows you to basically prompt the configuration process for what we call a skill, which is a set of decisions that you want to digitize, and it's cutting the implementation time. It's truly, you know, I've I've got a few pet peeves in my career. One is, you know, you've heard about self-service analytics. It's never really been the case because a normal business user doesn't really know which field to look at. There's always, and and despite 25, 30 years of effort to try to bring that analytics layer and making consumable by normal business people, it's never really worked. Now it does. Now, with the technology that we built, we can literally interact with uh ERA and get access to all the intelligence because ERA has that memory of which field means what. So we resolve a very simple problem. The technology is very sophisticated, but the problem was simple. So this level of self-service analytics, modeling, recommendation is there. I don't need a lot more. The challenge was always to deploy that at enterprise scales and the time it takes. And again, the technology is coming to the rescue here and pre-configuring the systems. And in the course of this year, we'll be we'll be moving very fast in that direction. So the next level of thinking, once the technology issue is addressed, is organizational designs. It's the impact of these technologies on people, on organizations, on the future of work. This is a very big topic. And I think people don't realize how quickly this is coming until just a few months ago. There was enough barriers and enough complexity to go slow, and therefore the impact of the organizations was not really felt at scale. The minute the technology is basically self-deployed, and I'm exaggerating a little bit, but we're gonna get there, then there's no more reasons not to use it, and the impact on the organizations is gonna be quite, quite critical.

SPEAKER_00 34:54

Absolutely. So if we were to have this conversation again in 12 months, what would make you feel it's been a successful year for Aero Technology?

SPEAKER_01 35:03

I'm thinking about my team listening to this answer and thinking Fred will never be happy anyway. So uh always push for more. It's funny you asked that question because for many, many years I've used this exercise that I call prospective hindsight, which is exactly what you ask, right? We are that's the way we plan. We are a year from now, we've been incredibly successful, and then we reflect on what we did now that enable that success. I think for me, number one is the uh the well, I just not gonna repeat the technology part, but it's literally cutting the uh the time to deploy the technologies to days. We have a program that is gonna enable that. So you can try ERA and deploy it in a matter of days. We went from a year to six months to average right now, two, three months, it has to come to days. If we do that, bingo, I think we're done. So I think that's a very, very big point from the product standpoint. The second is that I mentioned the community, right? We we're launching that community. It's gonna be having a large number and a very active community so that content can be and advice and experience can be shared, and we're not just in the middle. We're enabling, but we're not, you know, the center point for everything. That's what's gonna enable the hyperscale. We've got an incredible team, incredibly stable, incredibly talented. My goal is that a year from now we've we've grown that team, but we kept our core intact with the amazing people that have been enabling the era vision and dream for the last many years. I mean, our tenure is remarkable in this company, and uh the culture is really strong. So a year from now, I want the top top line growth, I want the velocity on the deployment, I want the community, but I want the culture to remain what it is today um and and not lose that. So I'm quite obsessed with that and making sure that we stay true to ourselves, to what we are, to our values. We're in a cutthroat industry with a lot of people behaving in, and there's always a lot of money at the end for the winner. So you see behaviors that no, we're not gonna do that. Um, I think a big part is the uh ecosystem as well. We have very strong partners that are working and believing in us. So I would love them to be super successful with our technology, have built practices and see the flywheel, it's happening. But a year from now, we've got objectives to really make them successful. If I can make my clients successful, if I can make my partner successful, if I can make my team successful, then you know we're we're achieving our goal. So, you know, it's probably in no specific order, but nothing makes me more happy than to hear our clients talk on stage at our conferences and talk about the success that they're getting, because this is not just yet another technology. This is not a replacement for an existing tech. This is the true transformation. I always say we are the innovators, but our customers are the disruptors. They're disrupting their business. We're here to help them and enable that. So having more and more customers having fantastic success stories is always like the the goal for us. It's not a single dimension. When you do what I do in the market that that we operate in, you cannot think about a single dimension. So it's the product, it's people, it's customers, it's partner, it's bringing that success. Um, and I think we have um we're we're doing it, and I think we have a great shot. So the next 12 months are going to be super exciting, and hopefully we'll be talking again before that.

SPEAKER_00 38:33

Absolutely. Well, that's it for today's episode of AI Speed. A huge thank you to Fred for sharing his invaluable insights into how Aero Technology is helping enterprises turn AI into real operational decisions at scale and for navigating the future of decision intelligence. If you're building or leading an AI native company or service business that uses AI under the hood and you care about revenue adoption and market share, make sure to subscribe to AI Speed. Learn how the best AI operators ship faster, sell smarter, and stay ahead. Thanks for listening. Until next time, keep building, keep selling, and keep moving at AI speed. Thank you. Thank you.