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Many still see AI as futuristic or out of reach—but what does it really take to make it useful in everyday work? We’ll cut through the hype with Florian Douetteau, CEO and co-founder of Dataiku, and discuss what it takes to build real, lasting value with AI. With a $3.7 billion valuation and over 700 customers, we'll unpack how this once Parisian startup has made enterprise AI accessible, practical, and impactful across entire organizations. 

EVERYDAY AI: BEYOND THE BUZZWORD

Conferences

Hello again. AI is still often discussed like it's futuristic or out of reach, but for many companies it's already part of everyday work, helping decision making processes, improving operations, and changing how teams function. To discuss what makes I really useful and where its value truly lies, please welcome co-founder and CEO of Data IQ, Florian Duetta. So Florian, you co-founded Dau in 2013. How long ago was that in AI time? Uh, 100 years, probably 100 years, give or take. Well, again, the reason I, the reason I bring it up is because so much has happened in AI since then. What were those early days of Data I like? In in the early days it was lots of things were similar than than today, meaning uh enterprise were facing new opportunities and technological challenges, and uh the question back then is like, what do you help people? There was enterprise to get value um from AI. And my take back then and until now is that the The roadblocks where I are usually not the one that people think. It's not that much about technology or the quality of technology per se. All of those innovation pouring in. It's about the ability for enterprise to make it theirs. And in particular, back then, what was fascinating to me is that you had the opportunity to create more value with data, of course, but many companies were like, oh my God, in order to make it happen, we need to hire a lot of experts, lots of data scientists, or what else? And this perspective would not work from my perspective because What you really need if you're an enterprise is to transform your business and actually to enable the people in your teams to make more by themselves, which led me to this venture of building a platform to make it easy for the enterprise, for people in the business to create their own AI, their own models to work on their data, to create stuff by themselves, which led to the company I know lead. Well, let's let's name it. What are some of the roadblocks that enterprises often run into as they start to adopt AI? When they start to adopt AI, um, I think the first issue they've got is the This they've got two things. They've got the skill gap, as in like what do we need to have in the business as skills to make it happen, and they've got another one which is just the fear, the fear of failure, the fact that AI is not perfect, AI is not deterministic, and so a business should run the lack a clockwork. So who do you actually reconciliate those two facts? And you're expressly running into a fear of failure. Where do you think that comes from? The fear of failure comes from the fact that indeed AI technology is RO, meaning the RO power. In order to make it work, you need to actually combine AI with your own data. You need to combine AI with things that make sense for your business. You need to put it in control before building it into a process. And it's not just about, for instance, one of our customers started to deploy agents in their shops. They are selling clothes and part of the motivation was to help people in the business to look for inventory so that they could help you faster determining whether this or that piece of item could be available or not. So instead of like going through scanning or whatsoever being To search for it faster. Great, but an agent can help you do that for sure. But in order for the agent to actually be smarter, you also want the agent to be able to suggest if the piece is missing, what else should be provided to the customer. Proactive needs to be proactive. And when you want the agent to be proactive, you don't want the agents to hallucinate. You want it, for instance, to give a recommendation based on good old AI built on models that Helps you recommend one product, one color, one type of jacket versus another, one type of pants versus another, or what else? And so any type of business, would that be in finance, would that be in healthcare, would that be in retail, would that be in manufacturing, they need to combine the power of. Les the power of GAI with the data, their metrics, they are good on models in order to create things that make sense for them, not just for the eye. Well, there's a pretty wide breadth of customers you work with. Give us a sense of the breadth of customers. What are we talking about here? Yeah, so yeah, the business is More than a decade old and we grew into uh having 700 customers, enterprise customers, um, and our business is around 300 million of IR. So our customers are for a lot of them, well 14 2000 companies and names come on, yeah, so some names include, uh, uh, BNP Pariba, Morgan Stanley, um, Fier, uh, Farms, which makes might not resonate with. UK people, because you, you don't chicken, chicken, chicken, a lot of chicken, they make so much chicken and exactly at GE Aviation, they don't make chicken, but they fly definitely not chicken, exactly. And so all of those companies have in common that they actually Generate and can generate lots of data because they are banks because they are healthcare organizations, because their manufacturing processes are very complicated and generate lots of data, and they also have in common the fact that they can derive lots of value in AI because you have lots of processes you can optimize and you can optimize them because in the manufacturing line you've got someone that may spend one hour a day going through some logs in order to write a log report of the day. And this person is paid a good amount of money just to do something in the very same thing every day, and AI can automate that and those are the type of things that our customers are building with our platform. Um, it is uh something that is valuable for them because healthcare companies, they manage lots of data with patients in order to understand what you, what kind of drug they could actually um. Uh, they could actually work on the market in order to understand what the actual use of the drug already on the market that they could better understand and that they do lots of surveys, lots of texts, and a good amount of their workforce is working on analyzing patient interview and patient data in order to trans that into something they can then use in order to make some determination, and this can be automated with AI. And so those things are small, each of those, but like those are the hours and hours that AI will actually automate, and I think that is the concrete version of AI that would transform the enterprise. Well, one of the things I find really interesting about all of these different use cases is pharmaceuticals are very different from aviation applications, which is very different from chicken, right? So what is the thing that binds them all together? What is true in every case, if anything? What is true in every case is that the people that actually in order to actually create a good AI project, you need first to understand the context because many of those companies are building fairly sophisticated products. Why? Because they exist for decades and decades. There is a way actually to do chicken, a way to build an airplane engine. There is a way to do finance. There is a way to actually push a drag on the market and They actually have lots of knowledge and they need to translate this knowledge and so you need the context of the business in order for the EI implication to make sense. And so for that you need to enable people that are those domain experts. The second thing they've got in common is that they've got large operations that do work, so you don't want actually AI to break things up. So the main risk of AI is that you flip the switch, you build a model, you let it run something, you build an agent and so forth, and if it's not good enough. Uh, best case just distract people, which is never good. No one loves distraction. I do love distraction, but not when I work. Or actually I love distraction when I work, but I should not. Whatever. You want the right amount of distraction at the right time. Exactly. So worst case is just distraction and Best case is discussion and worst case they actually break something. They make a customer service poor. They actually create an issue that you wouldn't have before. And so consequences which yeah, which should have practical consequences. And so the the the thing that is key for them is that. When they run AI systems and when they get more and more sophisticated, they actually need to just build more and more tests, essentially speaking to focus a lot on the quality of those systems and the issue when using generative AI at scale or using agents in the enterprise is today not so much the relative quality between 1 and 03 or whatever else. Of course it matters, but it's. And from my perspective and not just that is the fact that in order to use them for real, you need to build them, test them, connect them to your actual data and so forth in a way that is. That require some work. Now, one of the things that is talked about a lot is AI being hyped or overhyped. How do you help customers differentiate between what will really work and what's noise? I think that the perspective from our customer is winning. The, the, um, well, a couple of months ago, um, we gathered some of our customers and that would be mostly chief data officer for instance of various, um, large organizations, um. And one of their concerns was that essentially speaking in their company, lots of people were talking about AI. The management team of the company was talking about AI. The board of the company was talking about AI, and so they were like, OK, we actually have to do more AI. Everyone's talking about it, so we have to do it or not, blah blah, to manage it. And so one of our next step is that. In order to understand better, we actually try to survey CEOs themselves again from various organizations across Europe and US and various sides of the company, but like, OK, what do they actually think about AI? And indeed part of the eye and part of the thing that we learned from the survey is that many CEOs realize that they have to do things about the eye and are almost to some extent fearful of losing their job or their position. Because of AI, because of not doing enough, like 80% were actually fearful of that. And at the same time they were conscious about like regulation and the impact of regulation, and we're aware that for 30% of them that some projects of AI were canceling the company because of regulations. And so what I, what I think is that part of the hype is because there is this realization that it's a moment, it's a moment where a lot of organizations will actually transform their productivity. Where the one that will go faster to AI will actually potentially be a big winner, but also where people that go too fast and actually create a risk in their business could actually also be the first losers because they would just essentially open themselves to the critique coming either from their customers or shareholders or whatsoever to the risks and consequences of AI. So from the perspective of leadership in the organization, depending on. The way you look at life, it could actually be either a win-win type of situation or a lose-lose type of situation because you might lose on both and if you go too fast, you lose because people will yell at you that you're a responsible user of AI or if you go too slowly, well, exactly. And then, well, you could be replaced as as a leader by the next generation of CEOs that would be AI first, whatever that means. Now, I'm gonna come to you all for questions in a moment, but Florian, the IU has reached quite a bit of scale and has long been rumored as an IPO candidate. Anything I need to know? In front of all these people. Oh yeah, of course, that's the type of place where you make revelation about IPO. Yeah, I guess it's been the question all day. Yeah, yeah, meaning we built as many companies, we, we, we've built ourselves to our public readiness and we brought together in the last few, um, in the last few quarters, actually, um, quite a few seasoned people in the next, uh, uh, a CFO, a CRO, a chief people officer, a GC coming from uh Twitter, Zoom. Cisco and so forth, and which is I think what you need in order to scale and grow a business. Uh, a related question uh can be uh in which country and those kind of things that you haven't asked, but I can see you please continue, but indeed as a company we, um, as a company and I think for many companies of our generation, we decided fairly early on to, um. Uh, essentially get, uh, US investors and uh focus our business in the US even if, uh, as a company we are very nuanced because we, uh, operate our product from Paris. I'm based in London and the company investor based in the US. Any questions for Florian? It's not, I can keep going in the back. Oh, hello there. I think then, co-founder and CEO of Nana where we do home-based digital diagnostics using AI and applied machine learning. Lauren, I have a question because you guys are kind of horizontal across the enterprises like an AI developer of different project needs. So I imagine. Your success with your enterprise customers actually comes down to their data sets and what the project they want to develop. How do you take those learnings from one enterprise and one sort of industry vertical to others, because obviously you can't take that data with you for your next project. Oh yeah, of course not. And because our product enable our customers to differentiate by building their own models, their own AI and so forth, it's not desirable. And actually many of our customers operate their IT in a very nuanced way with things on the cloud, but they're on VPCs, things on Prem, and parts of our value proposition must be actually to be very agnostic to that, and then keep the data where it is, whatever cloud, whatever data platform, like, yeah, keep it, keep it, we don't want it and uh. So what we, what we do though is uh focus on the ease of use so that people in the business can actually use the platform and actually build the solution and accelerators so that the most common business needs can actually be done faster on the platform, uh, for instance, um. Well, marketing mix modeling, that's something that every company needs to do, that every pharma company needs to do, every retail company needs to do, uh, and in the grand scheme of things, no one really cares to differentiate that much because of that, because it's a bit of plundering. Um, if you're honest, so, well, very smart, but like still, and so yeah, they are very happy to take something that is off the shelves if they can adapt it to their own data because many of the situation, the issue of like of the shelf solution from the perspective of the enterprise and especially the larger one is that it does not really work for the mix of their data, their constraints, the code increase the operate in, and that's kind of like something they can do with our platform and the way we think about it. Any other questions for Florian? I can keep going. What do you think Is the most misunderstood thing about enterprise AI right now. Hm. I think that's the If I, if I reflect about the AI in the last 10 to 15 years, one thing that has been constant is change, as in if you're the, if you're an enterprise, um, you can look at all of the technology popping in and lots of these core tech technology is actually coming from the, from the Bay Area. And in fact this technology keeps changing, meaning the best database, the best models, the best, I don't know, open source, whatever that can be useful, you've got something new every 2 or 3 years. And so the issue for the enterprise is that an enterprise is also something that is stable and needs to accommodate change in a very specific way. So something that is misunderstood is that the The reason why entropy succeed in AI and so forth will not be that much based of that technology, but whether they build a culture, they build a framework, they build a way to think or integrate those technology so that they get it slightly faster than the other and slightly better for their own business. And that relates to a little bit of framework or platform like ourselves perhaps, but also to the culture of the company, and I think that's what's potentially misunderstood about this. ultimately, the success will be cultural. Well, and sort of in this vein, what does every single person who's an executive at a company need to know about enterprise AI in 2025? Um, I think that's what they. What they need to know is um hm. I think they need to understand what's magic versus not. They need to try it for themselves. I think they need to understand who is in the business doing it versus not. Uh, in the survey we did, I think that more than again 80% of the CU had the perspective they had a good grasp of what was happening in AI in their company, but I'm sure, I'm not sure I believe it. The same CEO were also saying that. So they're reporting to you, they have a good grasp. You're sort of sitting here saying what is a good gras just they've got the perspective of like the things that were coming to them. And they also have the perspective funnily enough that uh and I think it was a very high number like 90% of them plus were considering that AI could do a better job as at least one of the above member. Yeah, well, well, I don't know, maybe they all have like very, very big board, so law of the statistics say that in a very big group you always have a stupid person. I don't know. Yeah, say that sentence did not. I thought it was going to end. I'm not sure if they understood what the answer to this question because they also participate with the board, so it could be applied to. But so I think that it's also understanding what what we actually delegate or not we are having a good understanding of the limit of this technology and how to, how to think about it is probably something they should do and by getting a eye to their business, not just using it casually through the GPT in order to prep their next interview or their next meeting. Now we're gonna end somewhere that I know is central to JI2. Everyday AI. What does it mean and why does it matter to the future of AI as a whole. Yeah, we, we focused uh uh quite a bit of messaging or even build events around the topic of everyday AI as in the moment where AI and then we started that back like 7 years ago, back to. This idea that at some point AI would be so pervasive in our day to day lives that we should stop talking about it because today we talk a lot about it because it's new, but like ideally at some point we stop talking about AI because it would be an everyday thing. I think that with the advent of a generative AI and so GPT and so forth, we made a step toward this because indeed uh 12 years ago AI was a funny word of mad scientists, so. I was very, very careful before saying AI today like everyone probably in this room has done some. GPT today we got a we got a full room of hands earlier on. So a lot, a lot has changed and you've watched that trajectory. Thank you so much for taking the time, Florian.

Wemimo Abbey, Co-founder and Co-CEO Esusu
Laureen Meroueh, Founder and CEO, Hertha Metals; Breakthrough Energy Innovator Fellow 
Vivek Sharma, Chief Executive Officer, InStride
In conversation with: Alyson Shontell, Editor-in-Chief, FORTUNE; Co-chair, Fortune CEO Initiative

CEO Initiative 2022 - Creative Capitalism: Using Ingenuity To Make An Impact

Wemimo Abbey, Co-founder and Co-CEO Esusu
Laureen Meroueh, Founder and CEO, Hertha Metals
Vivek Sharma, Chief Executive Officer, InStride

Creative Capitalism: Using Ingenuity To Make An Impact

Wemimo Abbey, Co-founder and Co-CEO Esusu
Laureen Meroueh, Founder and CEO, Hertha Metals
Vivek Sharma, Chief Executive Officer, InStride
In conversation with: Alyson Shontell, Editor-in-Chief, FORTUNE; Co-chair, Fortune CEO Initiative

Wemimo Abbey, Co-founder and Co-CEO Esusu
Laureen Meroueh, Founder and CEO, Hertha Metals
Vivek Sharma, Chief Executive Officer, InStride
In conversation with: Alyson Shontell, EIC, FORTUNE

In our leadership roundtable discussions and mainstage conversations. We've been examining the themes and interlocking mechanisms that are helping create capitalism. 2.0, an essential driver of transformation across business sectors is innovations in this evening's program, we're going to hear from three business leaders about how innovation can catalyze and accelerate social impact. Please welcome to the C E O I stage Lauren merry way Ceo and founder of Hertha medals and breakthrough energy innovator fellow Vivek Sharma chief executive officer at in stride and joining us momentarily will be with me Mo Abbey co founder and co Ceo at Suzu joining the conversation is fortune editor in chief Allison Chantelle. All right, good evening everyone. Uh welcome to Fortune Ceo. I in our evening this we have incredible guests started the varying stages here with us who think that doing good is also good for doing business. And so um beck you started in stride a few years ago um, maybe could just open up with saying what your vision for inside is actually the walt Disney company to do this. You've been with corporate America for a long time. Why this vision by this company? So first of all, thanks for hosting us um in stride was launched with my basic belief that businesses have a social impact obligation as well. And around the time I was working at the walt Disney company, I was also the adjunct professor of data science at USC. So one thing I could see was look at corporations as a professor and universities as an executive and I found that, you know, it's hard to imagine two ecosystems that have moved to offer to each other than universities and corporations, but they don't work well at scale. And we looked around and we saw corporate America spend $28 billion on workforce education but not a single ceo C. H. R. O. Was happy. So we started in stride with like minded co founders, which is the TPG Rice fund and the Arizona State University with the goal of helping large organizations provide workforce education to their employees in a way that they also achieve business goals. And the central thesis here is by doing that they're achieving business and social impact and the manifestation of that is to think about learners and employees as the same thing. They are good fiduciaries, but also good citizens And they do well and do good. So we've been around for close to four years now. We serve over 42 large organizations about 20 Fortune 500 and I'm proud to say that as a result of a platform, the employees in our partners have avoided over $630 million of student debt. So that's what we do. Well done in a short time to just a few years Laurie and I want to jump to you, you're innovating in a very different space. You're in climate tech. This is actually your second climate tech startup and attracted the likes of Bill Gates as an investor. Um, you don't have a product yet because this kind of innovation takes time a few years out. So this is a long term play. Can you just tell everybody what you're doing in steel production, how that creates um CO two emissions and what you're doing to curb it. Yes, thank you and thank you all for the opportunity to be here. This is incredibly exciting to be in a room filled with the decision makers and the people with the power to have an impact that we're striving for. So at Hertha metals, we are d carbon izing iron and steel production at the core of what we do is driving impact. The global climate change worsens global inequities. And so if we can solve climate change, we can do our part and many don't know that steel is actually one of the biggest industrial emitters out their steel production. It results in more than 10% of global CO two emissions. And we're not getting rid of steel. Right? Steel is the backbone to modern industry, it's material we need that supports our infrastructure. Uh, so we're addressing this by being able to make our iron and steel thing we use every day everywhere, It will be the same product. But instead of using coal, which is how we make primary steel today, we use hydrogen and renewable electricity. So 95% less co two emissions than what we're used to and how have you found um raising money for a venture? That sounds game changing, but it's also takes time, a lot of effort. Um, I assume some tinkering, maybe some failures. Um, as long as success is to get to the product stage, not every investor would wait for that. Yes, it definitely takes patient capital. But our investors understand with high risk and long time periods come this enormous reward. Uh, and at Hertha metals, we truly believe that we have the game changing process to, to pay up that reward. So it takes a special kind of investor and you're seeing more of them in the climate tech space where this isn't a software uh, play right. This isn't a typical Silicon Valley startup. You need that 10 year plus. Uh, fund life and investors like Bill Gates who have founded breakthrough energy uh, understand that mindset and have proven it to be a successful mindset in how they invest as it has already resulted in returns, but patient capital needed. So this gets a little bit into the es de conversation in which that's become a little bit of a charged word. You told me I'm not allowed to ask you if woke, but here I am asking um, is it woke? Yeah, No. Yes, she's not work. So I'll go on record saying that the, the, I'll come back to the central thesis of why we started our company as also the principle behind how yes, she should be done. Well, see I run my company, I have a board, I have an obligation to my shareholders. I'm on a public board. I'm also in a private board. I expect the ceos to deliver on shareholder returns. The whole idea behind you know, in stride and the right way to do E. S. G. Is to recognize that this is not our this is ad you can achieve all that you are charged to do by your shareholders in a way that you also deliver on E. S. G. Right? So I'll give you a few examples from some of the customers we serve. We have retail customers who are really struggling with attrition in retail industry. A good year is when you have a tradition of 30% a bad year is 50%. Now, what would happen if you did not take that attrition as a given, you said, I will invest in your career aspirations, your re skilling your up, skilling and as a result of my investment in your career, I build an equity with you that you want to stay with the company longer. It helps the employee, it helps the learner as well. Um, so the right way to do it is to think about, as I said business and E. S. G. Goals not in contradiction with each other. It's when you think about this in the context of our, that's when you get the phrases like the one you said, but in and adding anything to and at the end of the company mission is really hard to do. Doing one thing. Well, it's hard enough been doing too. Is that really reasonable to expect executives? Actually, that's what C E O S do. We manage short term and long term goals. We serve the interests of customers, employees and shareholders. We we do a lot of ants across geography across different time frames. What this is saying is it is not as simple as picking up an E. S. G. Goal, figuring out KPI s and not linking with your business priorities once you do them. Well, this is just one more and you have to work with, but we have V. S. C E. O. S. I hope all CeoS will agree here have done that forever. And how do you both align um, your employees, your boards, um, your executive team with all the right KPI Well, the starting point for that if done the right way is you have to clearly articulate the purpose of the organization. So when I started in stride, uh, we were in a ford f, we work, I was all by myself, which was a bit of a transition from running a multi billion dollar business at Disney. And so the first thing I did was I wrote what I call as the founders memo and we said, what's the purpose? What's the vision? What are our values and what is it that I can articulate to customers to shareholders, investors to our partners in a way that it makes sense to them. I think that that definition is important. Uh and and every time I go to my customers, I recruit a new employee. I tell them very clearly, look, we are in stride is about helping organizations drive life changing benefits to their employees in a way that it also benefits the organization. I have not had anybody had any problem with that. And Lori and how about you? I would agree with what said, you definitely should be starting with the mission. What is the mission of your company and what do you do? And note that it's not too late for you to change your mission, right? You might be an established company and you're saying well for so long we've advertised ourselves in this way, times are changing and if you're successful, you should change with the times correct, Which means your mission should also transform accordingly. Uh and we also, um thankfully a lot of people believe in the same thing. We believe it hurt the metals, which is, you can drive profitability while also creating a better planet uh and securing the longevity of humanity, right? Um, so mission alignment and I believe that it doesn't need to be uh either profitability and some of our shareholders being um appeased versus the other of us doing what we want to do in terms of our impact, but there is alignment and you just need to really be thoughtful and considerate in thinking about how to align uh your stakeholders towards one vision and value and in fact you're a tech investor yourself um you sit on boards, you've obviously been a Disney um how are you seeing large companies um succeed in their E. S. G. Initiatives in doing good is also being good for business well. Uh So in addition to that, I also teach a course at USC called the Digital Foundation for Business Innovation. And I always tell my students that remember innovation in large organizations is idea meeting commercialization. You should not forget that and there's a little bit of that with PSG goals as well. Right, so once again I'm going to repeat my previous answer but basically it is figure out the purpose of the organization walk back from that and and design a mechanism in which we achieve both goals. Let's take a few examples. So imagine being in the conversation with the Ceo for health care system and articulating and a program to invest in their employees in a way that you can reduce their tradition of nurses. We, as a country are short of half a million nurses, every time a nurse leaves a leading healthcare system just to backfill cost is $60,000. Right, imagine you're in conversation with the financial services ceo or industrial ceo. All of them are worried about what it would mean when technology becomes the core of the business and the employees do not have basic digital literacy. So a conversation with them around upscaling the employees on basic digital literacy that gets frankly good resonance across the entire ecosystem. The challenges when we try to take the short path, when we don't do the hard consultative top down work and try to understand what business is trying to achieve and come up with KPI is that may or may not make sense. So it's basically working bachelor business goal and then designing the KPI and how do you get the employees to buy in The once again, it starts with an education like workplace education. A lot of companies offer that, but not everybody takes them up on it. Like how do you get them involved? So let's start with why it is not working in the way it is done today. So typically when corporate America spends $28 billion, why is it not successful? Well, the reason it's not successful is number one, it is not linked to the strategic goals. No two. As a result of that, there is not real support behind those programs, tuition reimbursement is more talked about than actually adopted. Less than 2% people adopted and those who adopt do not find this changes their career trajectory in a meaningful way. So what we try to do is to say, look number one, we will always position this investment in employee education with the goals of the organization. Two is we will provide education opportunities that drive real outcomes. The employees are not entrusted in enrollments. The employees are entrusted in changing their career trajectory outcomes are important. You have to really articulate how it will help. And in our case we also try to make sure that the platform, which in our case is a technology enabled platform, creates a seamless experience to the learners so that they don't have a problem. Um, welcome. We're so glad you're here. You're here depressed. Apologies. Been traveling since one PM today, but hopefully the dedication, we appreciate it. Now you're in sunny florida. Just relax and have some wine and ask you some questions. It's gonna be great. Um, so welcome. So for those of you who don't know a memo is the founder of a billion dollar startup called Isuzu. Um, he is trying to help correct the racial wealth gap here in this country And I was wondering if you could tell them a little bit about how you're doing that and also how your upbringing um led you to this mission. Absolutely. So it's just really stemmed from a personal experience. I grew up in the slums of Lagos Nigeria. I lost my father at the age of two and I was raised by my mother and to verify the sisters. One thing my mother fundamentally believed in was just the importance of education she afforded my school fees to one of the finest high schools in the land. And that's what led me to this magical place called America. I immigrated from 80 degree weather in Lagos to negative 22 degrees in Minnesota. It was, it was a really cast a building experience. And when I told my New York and L. A friends, I go deer huntin and ice fishing. Um, you know, they always confused. Um, but during that transition, something important happened, my mother and I did not have a credit score. We walked into one of the largest financial institutions to borrow money and were turned away and had to go borrow money from a predatory lender at over 400% interest rate. My mother upon my father's wedding ring. We borrowed money from church members and that's how we got started in the United States. So really inspired by that experience, We started Susan on three core premises no matter where you come from, the color of your skin and particularly your financial identity shouldn't determine where you end up in the wealthiest nation the world has ever seen And the way we make that up and it's really simple when you pay your mortgage today. That data is reflected in your credit profile when you pay your rent. Unfortunately it isn't reflected. So we are the plumbers that essentially created the technology that capture your rental payments data and reporting to the consumer rating agencies. We walk with 60% of the largest owners and operators of real estate in the United States, Uh, to capture this data across, you know, all 50 states in the Union. And what was seen is really simple. The biggest driver of wealth in this country, right is home ownership. And what we are doing now is helping people establish their credit score and then giving them access to other quality financial product. It's essentially unlock them getting a home one day, affordable credit card, the card notes to be able to go to a good school. Um, and you know, was a 30 person shop 18 months ago. Now, it's 200 people valued at a billion. And we're just getting started amazing. Um, and an incredible mission. Um, there's obviously a racial wealth gap in startups as well, which, you know, well, um, could you tell us, given that backdrop, how has your experience been scaling to this level and um, how would you see it changing? Is it getting better? Yeah. Just to level set on the statistic out there, less than 2% of capital go to black and minority and women founders for black women or women. That's .0002%. you know, we always talk about thinking outside the box, but the folks that get to play and manage capital are inside the box. If you're interested in solving the world's toughest challenges, we need to consider folks that outside, I'm an outsider, have nothing to lose. And I'm really, really incentivized to think about our folks from where I come from, I realize the true american potential and that's what I'm squarely focused on. So, you know, my own experience of capital, My co founder and I spoke to 326 investors have said, no, you know, I used to walk out Goldman Sachs Pricewaterhousecoopers. It was one of the cosponsors here. Um, and you know, before I left PWc done $32 billion in deal value. You know, m and a walking with the biggest institutions, but that resume and that pedigree didn't mean anything when I was raising capital. Um, and one of the funniest story was when we started a su su and we were, we just won a $20,000 contract, the first ever one. Um, my co founder, and because credit cards were maxed out at over $100,000. 1 of our favorite places was Dennis. So the idea was, you know, we couldn't afford a hotel room and we decided to go to a Dennis got the Grand Slam. Uh uh, it's that night. And unfortunately, um, you know, we're not perpetual motion machines, so we dozed off and we were kicked out of it, Dennis. Um, and I say that story, um, just make it very real that are sending from zero to a billion dollars isn't just this fad, right? It took a lot of hard work. And for those coming behind us, my job is to outperform um not with rhetoric, but the record um that when you invest in black and other minority founders, um your capital is going to be put to good use, but above all, change the narrative, which I think this forum is all about each and every one of you are here because I think your justice capitalist, you believe on the premise that you can do good and do well and there might know means mutually exclusive. And that's the narrative I want to tell. I'm sick and tired of the 2% of the .002%, I can care less about that. I want to create a narrative whereby when you invest in folks like me, you create $10,100 billion dollar firms and companies like there will be a force to reckon with while doing good and doing well alright. Um and that's where we will leave it. Thank you all for all the hard work you're doing and innovating in your field

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