From Small Town to Technology Leader with Sumandeep Kaur, SVP of Product Management at Odessa

(Intro Narrator at 00:00:01) Today, we're talking to Sumandeep from Odessa about the latest data trends and her journey from a humble town in India to becoming a prominent technology leader. You're listening to Joel Beasley, Modern CTO.

(Joel Beasley at 00:00:19) One of the things that stood out to me when I was researching you and your experience is that you were the first person in your hometown to get a degree in IT. I was hoping you could tell me about that.

(Sumandeep at 00:00:29) Yes, definitely. I think there's a little bit of a backstory behind it. So I'm from a small town, but everybody there is really focused on education and making sure their kids go to college and they are able to go out in the world and make a name for themselves. But the two key professions at the time when I was growing up were you can be a doctor or you can be an engineer. Right? So there was a joke that if you throw a stone, it's going to really hit a house where there is either a doctor or an engineer. So I was all set to pursue medicine and be a doctor like everybody else. But then one day, I got introduced to somebody who told me about computers and the vast possibilities of what the future can hold, and that really changed my direction. So I was just coming out of high school, going into college, and did my undergrad then and then my master's in computer applications.

(Sumandeep at 00:01:26) And these are in the nineties, late eighties, where computers were not mainstream, definitely not in India, in the area that I was living. So it was a big deal. Right? It wasn't just me as a girl going and getting that degree, but just the first person to be doing that.

(Joel Beasley at 00:01:46) That is so cool. So were you in a rural area or a city area?

(Sumandeep at 00:01:50) It is a city, but again, it's a small town in the state of Rajasthan named Sri Ganganagar. And now it has grown, like, triple the population compared to when I was there growing up in those times. Yeah. So not really rural rural, but definitely it's a city, but not a metropolitan city.

(Joel Beasley at 00:02:12) I get what you're describing because I grew up in an area that was in the middle as well. It wasn't a big city, but it also was bigger than a small town. So yeah. I'm curious, how did you go from that city in India to the United States? How did you get over to the US?

(Sumandeep at 00:02:31) So my journey really started after I finished my college. I went into doing my own thing, which again was something which was different, which normally everybody was going and taking up a job. And I actually started my own company, not a big company, but doing freelancing in terms of building software, building products. And three years I did that. I was doing that for a company dealing with car rentals. So very new. Computers were new. So they bought a computer but didn't have enough software to really run their business. So the only thing they were using it for was Microsoft Office and the tools there. So I started there. And three years later, I saw that really I'm not learning anything new because I was only applying whatever I knew at the time. So then I took up a job and then got married. And my husband actually transferred over here on his job, and then I came over. And actually, the same company hired me, and that's how I ended up here, which was like twenty-six years ago.

(Joel Beasley at 00:03:44) Did you know your husband before you came to the States?

(Sumandeep at 00:03:46) Yes. It was after one year of our marriage that we came over.

(Joel Beasley at 00:03:50) Oh, very cool. And so what is it about you that caused you to go achieve this, getting your degree, doing something great, and going to the US? Obviously, not everyone in the town does that. Why are you different?

(Sumandeep at 00:04:06) So I think I would give the credit to my parents where they always encouraged us to follow our dreams, and really nothing was off limits. So I have an older sister and a younger brother, and all of us were given the same opportunities. And they were always pushing us to go beyond the norm, do something that nobody's done in the town. Right? So explore opportunities which others have not, and which is what really is now ingrained in me to really always challenge the status quo, even challenging gender biases. So that's where it started, where when I was younger, I used to play all the games that boys would play normally. Right? And I was really good at it. So I was, again, the first girl who was riding a motorbike at that time in our hometown.

(Sumandeep at 00:04:58) So which I know that a lot of girls at that time would look up to me and they would be like, okay, I want to be like that. You know? So I think that's what really started with, nothing was off limits, and you could do whatever you wanted. So which that mindset really opened up the opportunity to see what else is out there, what else you can do. So that's that's, I think, so I'm truly grateful for my upbringing because that is what set the foundation for who I am today.

(Joel Beasley at 00:05:29) And what did your siblings end up doing?

(Sumandeep at 00:05:31) So my brother, he works for McKinsey. He's a partner. And my sister, she runs her own business. So she has a bakery business back in our hometown, which, again, it started as a small business and now growing into the surrounding areas where they are actually distributing to other businesses. So it's which is pretty cool.

(Joel Beasley at 00:05:57) So clearly, your parenting style is a good one. Have you or your siblings applied that parenting style with your kids?

(Sumandeep at 00:06:05) Yes. Absolutely. I think one of the learnings that I carry from what my parents taught me is, again, passing on the values, never forgetting the roots, where we come from. So if you notice, I am a Sikh by faith. So I keep that very dearly in my heart to make sure I'm passing on those values to my kids. And then, again, every child is different. So letting them understand what their strengths are and what they really like, enjoy, what career they want to pursue. So passing those on and having that same style with my son has been very helpful. I can see how that encourages and giving them an environment to flourish and grow based on their terms.

(Joel Beasley at 00:06:57) And did you find is there a big community of your religion in the States, or is it small? How does that work?

(Sumandeep at 00:07:04) Oh, it is. There is a big community here. And, of course, depending on the state that you're in across the US, you might find a small or large community. But we have communities, Sikh communities, which are surrounding the our Gurdwaras, which is the house of worship. So we actually are associated with the Gurdwaras here, which is close to my house, about ten minutes away. And then as part of that, every Sunday, we make sure that we're focusing on kids' education, giving them an environment to learn and grow while they connect with their roots. But they also are finding role models to follow, to know that, you know, it's not one or the other. You can follow your faith, and you can still have the same opportunities out in the world and be able to have any career that you desire. And so yeah. So Gurmat Academy, if you've seen all my profiles, so I volunteered there, and that was the organization that I was part of when we founded it and still continue to be associated with.

(Joel Beasley at 00:08:11) Well, I love that you're promoting faith to your kids. It seems that every day there's that pool tends to get smaller and less popular in culture. So it's definitely like an uphill battle to feel free to share your faith and discuss it openly. So I love that you're promoting that within your kids. And does that come up at work at all?

(Sumandeep at 00:08:36) I would say I've been fortunate that I've always worked in companies and worked around people who really value diversity and what everybody brings to the table in learning about them, accepting them, that I haven't personally faced any challenges there. So I would say has not been a challenge for me, but definitely, I've seen that others share their stories where it has been challenging. So I really, really support accepting and embracing equity and having equal opportunity for everybody regardless of what their beliefs are, whatever their faiths are, where they come from. So I think I feel very strongly about that and keep it at the center of my interactions with everybody who works with me within the organization or even as we work with customers and partners.

(Joel Beasley at 00:09:33) Yeah. I did a series on faith in the workplace about a year ago, I believe. And because I wasn't sure how faith expressed itself in the workplace. And so I had on different people, different tech leaders, some were pastors, some were just practitioners, things like that. And I asked the same question over and over, like, how does faith express itself in the workplace? And what I got back after all of my interviewing was it essentially drives who they are as a person. And so when they're enacting the values that they believe, then they're impacting everybody. It's not necessarily, as some would imagine, you standing up and preaching at work. Right? It's more of like you just living out the values that you believe in and others being interested in, like, why is this person so happy?

(Sumandeep at 00:10:23) Well, I would say 100%, I truly believe you are the sum of your experiences, but more importantly, the values that you learned in your childhood and in your upbringing. And faith plays a really key role in that because whatever your parents are doing, you're learning from that and your surrounding community, what they're doing and what they believe in. And I think that that value system stays with you, even if it's not prominently, we call it out. But how you value every person and you see the good in every person and you value their opinions. And more and more we see that it applies to our work. Every day we are building products and solutions for our end users. Right? And our end users really represent our communities, which is a sum of all of this diversity that is there. So if we don't understand all the different viewpoints, we are not going to be designing solutions which are centered on our customers and the users and really solving for the full solution and giving them the best experience that we can. So definitely, I think it plays a key part in your day to day.

(Joel Beasley at 00:11:40) That brings up creativity. I was talking about this earlier, and I'm just curious what your thoughts are. I was having a conversation with Adam Feinchman. He owns like a digital agency. So he works with designers. He works with engineers. All stuff you and I are familiar with. But he told me that he's noticed a trend where technologists would say that they're not creative, but they're very creative people, but they would say, oh, no. I'm not creative, but then they would go do creative things. Have you seen that happening in the engineering field?

(Sumandeep at 00:12:08) Yes. I think where I see it is the merging of an engineer who's in the back room taking the requirements from somebody who's facing off with the business or the customer to say, okay, what is the requirement and how I need to translate it back to the engineers to go build things, where now it is all about your thought process and how you design solutions is changing. Right? Where you are all of the design thinking principles, all of the customer-first mindset, where you're really sitting down with the customers, understanding the business problems. And in that, you have all of the teams involved. Right? So the visibility that the engineers have to the actual business problem is making it the creative solution. So I don't think inherently they think we are creative because they're looking at and seeing people who do the cool UX design of the applications, and they're really the creative ones. But ultimately, it is powered by the engineering and the tech behind it. So the more they understand what problems they're trying to solve and they incorporate that in their solutions from day one, I think that's where the creativity in the engineers is showing up.

(Joel Beasley at 00:13:22) And what type of problems is Odessa solving? I don't know a whole lot. I was hoping you could tell me about it.

(Sumandeep at 00:13:27) Yes. Yes. Absolutely. So we are primarily in the asset financing industry. So we cater to all of our customers, of course, small businesses to all the way to global companies who are around the world. So the complexity of the problem is very varied, but the way we see ourselves is a platform that helps that spectrum of customers to be able to run their business. So we want to see ourselves as the platform, which is the operating system for running their business. And in doing so, we are always continuously on the watch for how those organizations or our customers are transforming. What's changing in their landscape in terms of what type of experiences, what type of business solutions that they're offering to their customers and how they are working within the ecosystem of their partners as they build these solutions and taking that into account as we are building out our roadmap. So how are we going to enable our customers to be able to unlock that additional value because we are enabling those capabilities to really drive that best customer experience they are looking to offer to their own customers.

(Joel Beasley at 00:14:44) And so it makes a lot of sense for you because you're in it every day. But when you say asset financing, is that, like, I need to buy a million-dollar machine for my business, or is that, like, for I have a product and my end consumers, like, in Affirm or something, they're financing the purchase of something that I'm selling. Could you tell me, like, more detailed what the asset financing is?

(Sumandeep at 00:15:06) Right. So when we talk about asset financing, if you know, in a traditional sense, if you think about you go into a hospital and you see one of those CAT scan machines. Or now when you go in, you have those cool tech on wheels, the little trolley comes in with all of the diagnostic equipment, and they take your vitals. So those machines are all leased. Right? Nobody really owns them. So these are all on lease. And then from a leasing industry, so I know leasing is looked at from a traditional standpoint, but this is the space which is changing very, very drastically and very rapidly in terms of nobody wants to own or lease anymore. And we are shifting to more around subscription economy and how I can have flexibility in how I pay for things. I want to just use it as I go. So that is the industry where Odessa plays in. Right? Providing the capabilities to the lessors to be able to lease the equipment. And, again, we are talking about a variety of industries. Right? We could be talking about IT equipment. It could be in health care. It could be in agriculture. So you see a big agriculture machine that, again, is not owned by anybody, so it's leased. So behind it, the companies that are really running those businesses is where we come in.

(Joel Beasley at 00:16:28) And how do you use data? Because you're doing a banking type product, you know, leasing. But how are you using all the data to help figure out that this is the trend people are headed in?

(Sumandeep at 00:16:41) Yes. So if you think about data, I see that as really data is the energy that is driving the engine. Right? That's what your business is running on. So even though our customers are businesses and then their customers are also businesses, but a lot of things are now taught with the lens of consumer tech. So very quickly, the gap and the expectations of consumer tech and business tech is reducing. Right? Because at the end of the day, we are really on a day to day basis dealing with individuals who we are selling the products to or who are using our products. So when we think about data, right, so there are, of course, there's consumer tech when you think about Meta and how they are monetizing the data that they collect on a daily basis. That's really what their business model is.

(Sumandeep at 00:17:36) But still, every organization is capturing a lot of data and a lot of times don't know what insights are sitting in that data. Right? So in order for them to make better business decisions, in order for them to know more about their customers as a 360 view of the customer, what's going on throughout the journey of the customers that they have within their engagement. Plus, now that there's so much data available even in the public domain to which you can consume and mash up with your data to drive even further insights to understand your customers better, to see how you can improve the customer experience, or you can come up with new offerings for your customers. Right?

(Sumandeep at 00:18:20) So if you think customer first and you then work backwards from there, you need the data to be able to really change the game there, making sure you're giving them the best experience. You're coming up with innovative offerings which are helping those customers unlock additional value or be able to position them to service their own customers better. Right? So that's where, at Odessa, what we're looking at is what is the data that our customers are collecting today within our environment and how we can, as part of our platform offerings, give them some insights which are readily available. Because not every customer has access to data analytics teams who can actually build those for them.

(Sumandeep at 00:19:05) So giving them a head start to be able to then build on our platform, extend the platform that we have is how we look at the capabilities we are building around data at Odessa.

(Joel Beasley at 00:19:17) Let's try to give a real world example. So I live out on a farm, a little five-acre farm, and let's say that I had a business and maybe a couple tractors or a couple different things, tools that I would need, fairly expensive ones. Let's say that I'm a small business farm, and I would lease the tractor through Odessa. Is that correct?

(Sumandeep at 00:19:42) No. So you would actually be going to a leasing company or companies who are in the financing business for agriculture equipment. But for that company to be able to manage those assets, those equipment that they have purchased or they have leased and manage the life cycle of that and be able to help their end customers with whether it is the invoicing, giving them notification, understand if there is maybe there's servicing involved with that equipment, ensuring that it's running. And so it's very similar to how you think about car leasing. Right?

(Sumandeep at 00:20:19) But it is different. Right? In every industry, there are other nuances depending on the type of equipment you're leasing. So Odessa really provides the software for those leasing companies who are catering to that scenario that you just mentioned.

(Joel Beasley at 00:20:35) That makes a whole lot more sense. Okay. I have a good idea. Yeah. You build lender software. Right? But that's a very simplified version of it. Yeah. That is cool. So everything from payments, processing, probably credit score stuff to, like you said, equipment life cycle, value, all of that. That is pretty cool. So really, that's a good business to be in because the lender or your customer is highly dependent on your product.

(Sumandeep at 00:21:03) That is correct. And but what I would also say is that, again, depending on our customer base, in some customers, we are a small part of their business. And in other customers, we see that we are the big rock in their landscape. So majority of their business is running on our platform. So we always have to ensure that there is capability to extend our platform to integrate better within the customer ecosystem. Right? So ensuring whether it is around data exchange, whether it is around connecting with their external processes that are not running on our platform and also having the ability to connect directly with their customers and partners. So that is where the real thinking of how do we cater to that variety of those customers while giving them the base key capabilities that every leasing company really needs?

(Joel Beasley at 00:21:59) And now that I have a better understanding of the product, let's continue with the agriculture example. What type of insights are you providing to the lender across their customers? Would you say this is more popular machine? What type of metrics are you looking at that are useful to the lender?

(Sumandeep at 00:22:19) Yeah. So I think, and this is where depending on the industry and the type of equipment, I think the needs are very different. Right? Because when you look at the agricultural equipment, there's big machines with high value, but there are not a lot of them. Right? And if you contrast that with IT equipment, you have a lot of assets, lot of different machines that are being deployed in the customer landscape, but the value per machine might be lower. Right? So in terms of what is the life of the equipment in terms of how long it's going to be on a lease, and especially some of the big ones can be on a really long lease cycles. So there is activity around the data and the interaction with the customer is a little bit lower compared to the ones which are getting refreshed every three years. Right?

(Sumandeep at 00:23:12) So that's one difference in terms of the type of data that they will be needing. If you have a lease which is just set and really nothing is changing, then there's not a lot of interaction during the life of the lease. It's only at the end of it you decide whether you want to send it back, you want to renew it with a better machine, and how you want to do your business going forward. Right? So those are the conversations and giving them the tools to know who's coming on in terms of the end of term, what we think the customer behavior is going to be, and how you want to enable that customer transaction.

(Sumandeep at 00:23:45) But on the IT sector, it's a whole different ballgame. Right? Because there is so much data out there that you want to not only know what's happening at any point in time of the whole asset portfolio, but you also want to derive insights in terms of what type of products and what type of assets really are best suited for leasing in terms of the long terms or they are more short-term deals and then the equipment is coming back and how you're going to monetize that if it comes back early. So those insights is where we would be focusing on.

(Joel Beasley at 00:24:21) That is pretty unique. How are you using any cool tools to structure this data in these learnings? Have you gotten into AI or machine learning or GPT, anything like that to help you come up with these insights?

(Sumandeep at 00:24:35) Yeah. So when we look at our industry, majority, I would say, of our data is structured. Right? So we are dealing with structured data which comes to us through our system, through integrations. In terms of unstructured data, it is around we would get emails and documents. Right? So as the deal is being negotiated and processed or during the life of the deal. So because majority of our data is structured, we are working within our platform to transform that data, restructure it because we know that data that is collected is really geared towards transaction processing. Right? So we are running the business. We are making sure the processes are run on that data. But when it comes to consumption of that data to really drive insights, you need to optimize it for reporting and analytics. So that's the restructuring that we are doing as part of our platform. But there are some use cases where we are starting to dip into the machine learning to really understand the data and build some predictive modeling around knowing what the customer behaviors are going to be. So whether we think about credit scoring or delinquency or what we think they're going to do at the end of the term. Right? What is the next action they're going to take and just be able to predict that and better manage our business.

(Joel Beasley at 00:26:03) That is actually really cool. And are you using GPT at all? Have you played with this technology?

(Sumandeep at 00:26:09) I've played with it on a personal basis, and I see it is exciting and scary at the same time. Right? And then you see the next version coming out, and it's not just text, and you can do audio, video, and it's able to just how quickly it's learning. So now I think it is for everybody to look at and say there is definitely use cases that you can think of and apply in your day-to-day and see how they systematically get integrated into your business solutions. Right? So right now, it's an early stage of everybody trying out and seeing the value in it, but there's still the last mile that you want to have that human touch. Right? So you want to let GPT do its thing, give you the first draft of it, and then you want to look at it and see how you want to consume it. So I think there'll be a lot of POCs and trials that'll happen before we see exactly where it's going to land in terms of the use case.

(Joel Beasley at 00:27:07) I found it somewhat fascinating how certain people are entirely dismissive of the concept simply because it's not perfect. They'll say, oh, yeah. That's not ready. And I'll say, you know, have you tried it? Most people are like, no. I haven't tried it. I just saw this meme. And so for me, the way it played out is, you know, I saw it. I kind of, you know, I was like, whatever. And then I saw somebody give a tutorial of using it as an assistant to write code and help them debug some of their errors. And once I saw that YouTube video, I was like, oh, wow. I really got to go check this out. So I did, and we ended up using it at the company, at our business to help write prep, different questions, interesting questions based off of topics because we not only do this show, but we do like 15, 20 other shows. So we manage shows for other businesses. So we do a lot of this prep, and what we found out is that we can train it. We can show it a bunch of good preps, and then we can then give it more information, put your bio in, put topics that we're interested in talking to, and then it can output a prep. And that to me as an engineer is fascinating because I just fed it unstructured data, text, and then it learned what I wanted and gave me something back that is not perfect. Yeah. But we were talking about creativity. There's a certain amount of creativity hours that we all have in a day. Right? And so now that you have this technology that can help you generate creativity, well, you just made your time more efficient. And so it's not like we got rid of people or anything like that, but we made our producers far more efficient. Now they can allocate that time to making even better prep with this new tool, or they can allocate that time to doing other things that push the business forward.

(Sumandeep at 00:28:55) Absolutely. I think for anybody who hasn't tried it, one thing I would say is in our household, the first person who went and tried it is my father-in-law. And I was amazed. Like, he's the one who was like, have you tried it? And again, he was looking at it as a better tool from instead of just doing a pure search engine search on something and getting all these different links and then having to go find where really the answer is that I'm looking for. So he used it for whatever his questions were, but he was very, very excited about it. So I think definitely everybody should try it. And you're right. It's not going to be perfect in the beginning. And as you use more and you see and learn about the different scenarios as everybody's trying out and what where it's really helping, I think it starts to stem other ideas. So we just need to continue testing it.

(Joel Beasley at 00:29:47) I saw over the weekend, Zillow, the property search app, they implemented a variation of it. So now, you know, we were looking at different property recently, and so, you know, there's 100 filters with real estate property. Right? And you have to go configure them all, search, and so on. But now they have a text box up top where you can just say, I want five acres within an hour of Nashville that is ready to build, and it'll do its, it does a really good job of getting you there. And for at least the first version, right, I was blown away. Obviously, there's always improvements you can make, but I tried a whole lot of different prompts for the text input, and, man, it got all of the ones I tried.

(Sumandeep at 00:30:33) That's awesome. That's awesome. And, again, anything that is data that's available in the public domain, right, it's going to perfect reading that. And then once it comes into you're able to open up the data that you have within the enterprise and be able to mash up both sides, it's going to be incredible.

(Joel Beasley at 00:30:53) I have noticed that trend, like, to what you said, where I've seen the consumer experience. That's the first area, and then usually the business experiences are lagging to that. So Apple will do something cool, all the consumers experience it, and we instantly say, why isn't the software at work like that? Right?

(Sumandeep at 00:31:10) That is so true. That is so true. That's why I was saying it's not just the gap is reducing. It's just the expectation is changing so drastically. And which is why, right, even we as product managers, as we are thinking about products, we have to take that user input and their, we have to think about the user first, right, in terms of what their experiences in their day-to-day life and how they're expecting the same in the business world and then building solutions according to that. Of course, in the business, there are other things that we have to comply by their compliance, regulatory rules. There is data privacy. There's so many other things that we have to truly think about, but I think it's a good accelerator for us to keep in mind.

(Joel Beasley at 00:31:57) Yeah. I've crazy ideas about what I think is going to happen, but I do see this technology improving to the point where, essentially, the services we know of today, they have a data store and an interface. Right? And we interact with the product like that. I think there's going to be a new layer on top, which will be this assistive AI that we'll engage with on a verbal type of basis. Right? Like a prompt text, ask questions, get results basis that'll sit on top of that. And then I think some of the old school people will still use the visual UI of the softwares. Think about Facebook's interface. Right? Or a business software's interface. But then I think in the long term, it'll end up being those services that we know today acting more like structured data stores than anything else.

(Sumandeep at 00:32:47) That is correct. So one shift that I see that would happen on the data side is so today, we are in the data ownership model where we need to shift our culture also to be on a data sharing model. Right? So even within the enterprise, sometimes you'll see there are silos within the organization. There are different business and departments. They have data, but they don't realize that if only they were to put all that data together at the enterprise level, it unlocks insights that they can't imagine. Right? Now think that even broader at a broader scale in the world. Right? There is so much data that is out there that's available, which there is so much wastage in moving the data, making sure everybody has it, and then you're mapping it to the structured data models. Right? So you don't have the ability to access this data and be able to curate it for what you need in real time without actually having to move data. So I think that is really going to do what you're saying. Right? The top layer is able to go into those data stores and whoever the data producers are, but be able to consume it in real time and be able to give you that real-time insight that you can use, and you won't have to wait for the next day for the data to be curated for you to really consume.

(Joel Beasley at 00:34:10) Yes. There's a good episode if you're interested. I got to talk to Sir Tim Berners-Lee, creator of the World Wide Web, and I didn't talk to him necessarily about him creating the web as much as what the future is going to look like. And I think we did this episode about three years ago. So before GPT was a big thing everybody was talking about, and he was describing this concept of how he sees the future of us having interfaces.

(Joel Beasley at 00:34:36) He didn't say like a GPT interface. He just says us having interfaces that are agnostic to the data source. So I would have an interface for my banking app, whether I'm using Chase, Wells Fargo, Bank of America, and they're just acting as data stores. For me, I thought that was really interesting because his concept was that we would sort of maintain our own personal data store and it would sync with the provider. Because right now, Wells Fargo or Chase, they have all—you don't have a copy of your database.

(Joel Beasley at 00:35:05) You don't have a copy of your banking database. There's one copy and they hold it and you can never see it.

(Sumandeep at 00:35:10) Right.

(Joel Beasley at 00:35:10) Right? I think that'll change in the future to where I could have my copy. They have their copy. We could see the read, write updates, and I can choose to disconnect from it or interact with it. But, yeah, I think Sir Tim Berners-Lee, I think he's on the right path with what the future of the data stores are going to look like.

(Joel Beasley at 00:35:27) But it's such a crazy thought because it's not necessarily how we are operating today. And I don't know if it's going to take twenty years or fifty years, but I think it's going to happen.

(Sumandeep at 00:35:37) No. Absolutely. Absolutely. Exciting times ahead.

(Joel Beasley at 00:35:41) Where do you think we're going to be in fifty years? You think we're going to still have a bunch of independent software providers, or do you think an AI is going to be running everything?

(Sumandeep at 00:35:51) I would say AI would be pretty pervasive in terms of all the solutions would be powered by AI. Now, of course, in terms of the intensity of it, whether it's embedded within it or whether you're using it in your solutions, but it would be everywhere. And in terms of the data, I think we've already seen the explosion. I don't know where it's going to go from it. We're already at infinity in terms of just having the data available, the variety of it, the velocity at which it's changing, it's coming.

(Sumandeep at 00:36:20) It's all going to come down to how do we leverage the AI to give us the data that is relevant for what we are asking for and be able to process and present it. Right? So that we are using that first draft, like you mentioned. Right? So first draft information and then make business decisions on it.

(Sumandeep at 00:36:39) So ultimately, of course, I mean, the utopia would be that we don't have to do anything, and you want the machines to be able to make decisions based on how we are training them. And if there are things that are unique where they need to prompt us to be able to intervene, then we intervene. But I think there are a lot of use cases where you can see this really uplifting, the types of solutions that we can offer to our customers, to our communities, things where we have been limited by what humans can do or the structured data computation can do because now we are able to tap into the unstructured data, which definitely has a lot of nuggets that we don't even see.

(Joel Beasley at 00:37:24) Yeah. I could see it as an Odessa app on the GPT App Store. Right? If I install that, I pay my licensing fees to Odessa or whatever the fees are. I get that fine tuning set of features that enhances the base level conversational AI that I have.

(Joel Beasley at 00:37:42) I think that's something that'll come about.

(Sumandeep at 00:37:45) Yeah. There are, within the customer journey, as they engage with the Odessa platform, there are definitely those touch points where it doesn't need to be a structured interaction. Right? You can make it more fluid. It can be more conversational where it's like, this is what I'm looking for.

(Sumandeep at 00:38:03) And then behind that, of course, the structured data is available for you to interpret that, process the information, and then give the response where, again, based on the customer user preference, where they want it, how they want it, and deliver it. But behind it, the engine is still there, but start to think of customer experience or the end user experience is where I think the AI layer is going to start to play.

(Joel Beasley at 00:38:28) It's going to be amazing watching that play out as far as industries consolidating and, you know? Because I was thinking the other day like, let's take Odessa for an example. Let's say I'm looking for software that does what you do, and I ask GPT what is the best one. Well, however the methodology for how you influence chat GPT to answer that correctly, it's going to result in the reality that I'm no longer typing it into Google and getting 10 results, right, where you have the option to come up. It's I'm just asking it the question.

(Joel Beasley at 00:39:00) It's just telling me, oh, Odessa is the best one. And, I mean, while that's good for you guys, your competitors are not happy about that.

(Sumandeep at 00:39:07) And, of course, we want to make sure that we are the best. Right? So we want the GPT to be answering that, but then we have the backing to say why. Right? Here's the reasons why.

(Sumandeep at 00:39:17) These are the capabilities that we offer to our customers. This is how we would really help them unlock more value for themselves and then provide that amazing experience to their end customers. So that's our role. Right? We are here to really enable our customers.

(Joel Beasley at 00:39:33) GPT is listening right now, reading the transcript, understands Odessa is the best.

(Sumandeep at 00:39:39) Odessa is the best.

(Joel Beasley at 00:39:41) How do people find Odessa? How do they learn more?

(Sumandeep at 00:39:45) So you can go to our website, odessainc.com, and you get to know more about what we are doing. And it is odessainc.com.

(Joel Beasley at 00:39:56) I love it. Thank you so much for listening. And if you found this episode useful, please share it with a friend or colleague who you think would get value from it. And if you have topics that you'd like to hear discussed on the podcast, either add me on LinkedIn, or send me an email [email protected].

(Joel Beasley at 00:40:15) Every time I get an email or LinkedIn message, it absolutely makes my day and inspires me to keep going.