Latest / Beyond Fulfillment Podcast / From Harvard Hackathon to Silicon Valley with Omneky founder, Hikari Senju

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From Harvard Hackathon to Silicon Valley with Omneky founder, Hikari Senju · Beyond Fulfillment Podcast

• 0:00
  Hikari Senju is the founder and CEO of Omnikey.
• 0:06
  In this episode, Hikari shares his inspiring journey from studying computer science at Harvard to creating multiple successful tech startups.
• 0:15
  He discusses his early exposure to entrepreneurship, his experiences at hackathons and his foray into the tech sector with his company Quikup, which was eventually acquired by a larger firm.
• 0:29
  Hikari also dives into his latest venture, Omnikey, a cutting edge company that leverages AI to optimize advertising campaigns and generate creative content at scale.
• 0:41
  He provides intriguing insights into the challenges and opportunities of growing an AI driven business, especially in the ever evolving landscape digital marketing.
• 0:53
  Whether you're a budding entrepreneur, a tech enthusiast, or someone interested in how AI is transforming industries, Hikari's journey offers valuable lessons and a glimpse into the future of technology and market.
• 1:09
  As always, if you found value from this content, please like and subscribe.
• 1:14
  Hello everyone and welcome to another episode of the Beyond Fulfillment podcast.
• 1:19
  I'm your host Dave Gulas and this week my guest is the founder and CEO of Omnikey, Hikari Sanju.
• 1:28
  Welcome Hikari.
• 1:29
  Thanks for having me Dave.
• 1:30
  Really excited to be here.
• 1:32
  Yeah, we appreciate you taking the time.
• 1:35
  So if you could, for everyone, Hikari, can you tell us how you became an entrepreneur?
• 1:40
  Sure.
• 1:41
  I started my first company when I was in college.
• 1:44
  I was studying computer science at Harvard.
• 1:47
  I was at a hackathon and created this app so students could connect with other students just to meet up.
• 1:53
  And I kind of roped in my roommates to start this company with me and that was my very first company.
• 2:00
  We went through an incubator and that was my and you know, learn how to pitch to VCs, how to create a deck, how to get users and tell a story.
• 2:11
  Then I started another venture backed company in college soon, you know the year after which was an ad tech company called Quick Help and that was acquired by another business in San Francisco, another, another edtech company where I
• 2:24
  became head of marketing.
• 2:26
  And so those were kind of my you know, first two companies venture back companies started in college separately.
• 2:31
  Even prior to this I worked at my uncle Run right like pretty, like a, like a, like a medium sized like Internet company startup as well.
• 2:39
  He, he actually also started a social networking app in, in Tokyo and so I was interning there for, during the summers in high school and so that was also kind of my foray into learning what it's like to
• 2:55
  work for, you know, like an eight person team, you know, very early stage startup, getting your first customers, building the product for your customers.
• 3:02
  Etc.
• 3:04
  And then even prior to that, you can even go back and say that my grandfather worked at IBM and then he was a venture capitalist after that.
• 3:10
  And so kind of an early, you know, like education and technology and building technology products and, and seeing prototypes and seeing demos and, and learning what it means to, you know, start a technology company.
• 3:24
  And so, yeah, like my.
• 3:27
  Even though my very first company I started in college, I'd been kind of, you know, building projects, doing projects, working at startups, and learning about startups and technology products way before then.
• 3:37
  Okay, so you, you were exposed to business and entrepreneurship very early on.
• 3:44
  Tech.
• 3:45
  Did you always, you know, have the.
• 3:48
  Have the idea that you'd go into something in the tech field?
• 3:51
  Yeah, I mean, like, the reason why I wanted to be an entrepreneur was because of my deep passion in technology and that I felt that entrepreneurship was the highest leverage way of building technology products, at least quickly.
• 4:09
  And, and so I grew up in Westchester, New York, near the IBM headquarters where my grandfather worked.
• 4:18
  And my mother also went to the same high school as I did.
• 4:21
  And so first and foremost was just the excitement of technology, how every six months the world changes.
• 4:30
  You have Moore's law that exponentially improves the power of information technology systems, and technology enabled products exponentially every two years or 18 months.
• 4:42
  And that, that is just an exciting space to be in that, you know, what was unimaginable, you know, five years ago, you know, through exponential advancements, suddenly becomes, you know, reality and becomes normal.
• 4:55
  You know, kind of like ChatGPT is today or image, you know, AI image generation is today, you know, almost unimaginable five years ago.
• 5:01
  And so that was really what got me excited.
• 5:04
  I felt that entrepreneurship was the best medium for me to have the most impact in terms of building these kinds of products quick, getting them to scale.
• 5:12
  It was highest leverage way for me as an individual to build these products and kind of, you know, have an impact and connect with consumers.
• 5:21
  And so that.
• 5:22
  That really is.
• 5:23
  Is like a vehicle for building technological change, is the.
• 5:32
  Is like my path through entrepreneurship.
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  To the next level.
• 6:02
  And so you're at Harvard and you, you started the first.
• 6:06
  The first company.
• 6:08
  You said you were at a hackathon.
• 6:11
  Yeah.
• 6:11
  So Throughout Harvard.
• 6:12
  You know, I mean, I studied, was studying computer science.
• 6:14
  I was taking classes at mit and then on weekends I would go attend hackathons and, and I would actually even go to like Michigan University of Michigan or go to Berkeley and fly there.
• 6:25
  You know, the university system, there would be these hackathons that these universities would host and get students from all over the country to meet up and mingle and then, you know, build a project over the weekend.
• 6:36
  And so I was doing that as well where I was going to hackathons.
• 6:40
  And one of the projects that I started was this, you know, friend meetup app.
• 6:44
  Another one was the EdTech company.
• 6:46
  But so, yeah, like, and you know, even to this day, a big fan of hackathons and I attend hackathons and we sponsor hackathons as well.
• 6:54
  And I think it's just a really great place to quickly prototype ideas and demo ideas and so, and to meet talented individuals.
• 7:01
  And so, yeah, I mean, I, I'm a big.
• 7:04
  Yeah.
• 7:05
  So the first, you know, like study computer science and doing quickly building these demos was a big part of my college experience.
• 7:13
  Okay.
• 7:13
  And then for the next one that got acquired, which was Quick Help and that, that was a tutoring app.
• 7:21
  Yeah.
• 7:21
  So it was on.
• 7:22
  It was.
• 7:22
  Is a social, local mobile application focused on tutoring.
• 7:26
  So it would, it would be an app that would.
• 7:29
  You could take a kind of like ChatGPT does this today very well.
• 7:33
  And so you can.
• 7:34
  But like, you know, back then, you know, you was.
• 7:37
  If you had a hard homework problem, there was.
• 7:40
  You were kind of stuck.
• 7:41
  You, you.
• 7:42
  This.
• 7:42
  What this app would do is you could take a photo of the problem and they'll connect you with tutors who can help you solve that problem.
• 7:46
  And one of the benefits of being stay in Boston where there's a high density of students, is that usually there's somewhere somebody within that network can help, you know, knows how to help you solve that problem.
• 7:57
  They would actually, you could actually meet up, you know, at a cafeteria or you know, like, you know, in a, in a, like a dorm cafe or something and then they can help you and they can tutor you
• 8:07
  to help solve that problem.
• 8:09
  And so that was, that was the application.
• 8:12
  Okay.
• 8:13
  And so at that time too, you went through an incubator that also.
• 8:18
  That did not go through an incubator.
• 8:19
  With that we received financing from.
• 8:22
  We received a grant from Harvard and MIT through some competitions they had.
• 8:26
  We went through the, we were part of the Harvard Innovation Lab, which is kind of a, kind of Harvard's own kind of incubator for its students.
• 8:36
  And then we received some, some angel funding and some early investments from Dorm Room Fund and Rough Draft Ventures, which are two kind of college oriented funds that are subsidiaries of General Catalyst and First Round Ventures.
• 8:50
  And so yeah, that was kind of enough for us to get, you know, for me to be actually able to work full time on it after graduating.
• 8:57
  Okay, and so what was the process like?
• 9:00
  Because like you said, you're exposed to entrepreneurship very early on.
• 9:03
  You had all these ideas, you're going to the hackathons, you're, you're networking and collaborating with other young entrepreneurs, like minded people.
• 9:12
  But now you have a real company and you actually get funding and like you said, it affords you the ability to work on it full time.
• 9:19
  What was that process like growing like a tech startup as such a young adult?
• 9:26
  Yeah, I mean it's, it's, it's a, I mean being a tech CEO or being a founder is, you know, it's a skill.
• 9:34
  You need to learn how to market, you need to learn how to sell, you need to learn how to build products, you need to learn how to finance and raise money from venture capitalists, you need to know how
• 9:44
  to build a team and recruit, you need to know how to manage people.
• 9:49
  And so it's, there's a lot of stuff you need to learn very quickly.
• 9:53
  And I think there's a benefit in learning in, in starting this journey slightly sooner because it gives you more time to learn to learn some of these skills, at least in the context, at least for, in my experience.
• 10:06
  And so yeah, I mean like, you know, you start off and you know, you start off because you usually can build a prototype and you can get some users and maybe, you know, you can give in some investors
• 10:17
  to give you some, some seed money or pre seed money.
• 10:20
  But you know, to get that to the next stage you need to quickly level up, you need to close bigger deals, you need to get you know, order magnitude more users, you need to raise more money, you need
• 10:30
  to hire, you know, more people and really like really great people.
• 10:34
  And so you know, initially you're kind of failing at all these, you need to get attention.
• 10:38
  I think that's the most important thing is, you know, startups, attention is a very kind of important currency I think for, for a new product to get attention so you can get, you can get these other opportunities and
• 10:49
  so you just learn to hustle and that, yeah, you're just kind of, you know, you're just kind of putting, pulling things together and you know, just moving Quickly and just doing things and getting things done and incrementally just,
• 11:09
  you know, improving in various ways every day.
• 11:12
  And then, you know, hopefully, you know, a couple, you know, weeks or months later, you can look back and okay, we build a product and we have some users and we have some investors and.
• 11:23
  But, yeah, but I think the other benefit of starting company early is you kind of start seeing a lot of the patterns regarding, you know, startups and building a product from 0 to 1 and, and getting users and,
• 11:36
  you know, you, you turn to, you learn to not be phased by certain challenges perhaps that you face as well, because you kind of seen various permutations of it yourself.
• 11:46
  And so those.
• 11:47
  I think that that's another advantage of, of starting sooner.
• 11:51
  And what, what was the process like in terms of growing the company?
• 11:55
  Did it, what did it take off right away?
• 11:57
  Or did you run into some initial roadblocks in terms of getting customers and growing the business?
• 12:05
  So Quick Help, we pivoted to this system that would connect students, I'm sorry, connect tutors to students in all over the world, particularly in Asia.
• 12:15
  And so there's these in Asia, particularly at that time in the mid 2010s, a real desire to learn English.
• 12:23
  And we were connecting students, students there to tutors in the US and that ended up becoming a bit more of a lucrative business.
• 12:30
  But even then it was kind of hard to scale education companies.
• 12:35
  It's, it's just, you know, you're often competing against, you know, free product, you know, local.
• 12:40
  Usually most, you know, a lot of, most places have free education of some form.
• 12:46
  And so, and then.
• 12:49
  Yeah, and so that was kind of the challenges.
• 12:50
  So we end up selling the company to another ad tech company.
• 12:53
  And then I was kind of thinking about what my next company would be.
• 12:56
  And that was really when I had this idea of using AI, which was by fashion from college, generative AI in particular, which is.
• 13:06
  I studied machine learning.
• 13:07
  I focus on machine learning at Harvard and mit, applying that technology in the space of advertising.
• 13:13
  And that became the company that I've been scaling since 2018.
• 13:19
  Okay.
• 13:20
  Yeah, and we'll definitely get into Omni Key and, and what, what you do there.
• 13:25
  Just, just quick question too.
• 13:27
  On, on Quick Help and when you scan.
• 13:29
  So in terms of the, like the, the acquisition, was it more so like the tech company would be in better position to really scale it?
• 13:38
  So it was almost like divesting it in, in, in terms of, to free you up to, to work on your next venture?
• 13:44
  It just made sense.
• 13:45
  Is that how that works?
• 13:46
  Yeah, yeah, I mean, I think, you know, we had a lot of tutors on our platform.
• 13:49
  They were looking for a system for connecting with, with, with more tutors on their platform and kind of, I think they also appreciated my hustle to kind of boot in essentially.
• 13:57
  You know, we raised a little bit of money, but got some grants, but it was like for a lot of money and you know, kind of bootstrapping to a certain size.
• 14:03
  They, they appreciate that hustle and so, and so, yeah, it made, made sense.
• 14:09
  And, and, and I got to learn a lot about how to work and, you know, lead a slightly bigger scale company because I just, at that time, I think one of the main things I realized when I was
• 14:23
  starting this company about my previous company was just how much I didn't know and I just wanted to like, learn.
• 14:29
  And so by selling, working for a slightly larger company, I learned a little bit more about especially one of the benefits also was I got to move to the Valley because this company was based in Silicon Valley, so
• 14:40
  it's originally in Boston.
• 14:42
  Moved to Silicon Valley and being in Silicon Valley, just kind of learning, you know, what it, what it means to run a Silicon Valley tech company is a kind of a distinct animal in the flavors of entrepreneurship as
• 14:54
  well.
• 14:54
  And so that was a great experience and a great learning experience for me.
• 14:58
  And then, and then quickly after, you know, you know, about a year and a half after that, going and starting my own company again, this time with, with Silicon Valley investors based in the Valley, with Silicon Valley talent.
• 15:09
  That was, you know, kind of a good pivot from, for me in terms of the space, you know, good pivot for me in my entrepreneurial journey.
• 15:20
  Okay, so yeah, it sounds like that helped you out a lot.
• 15:22
  So you sell the company and then you stay on to work for the company that acquires you for, for a year and a half and you get to move to Silicon Valley.
• 15:31
  I mean, you, you were at Harvard, which, I mean, it's very high level education, right?
• 15:37
  How, how, how much of a, how different was it going to the Valley and jumping into that business world where is such a, such a hotbed of successful tech companies and being immersed in that scene?
• 15:51
  Well, you know, I think Boston has a lot of really great, you know, there's a lot of, it's a very scholarly place and there's a lot of really smart people, very knowledge and you learn about how to think
• 16:05
  about problems critically and deeply and also how to think just how to think more critically and strategically and you gain a lot of skills.
• 16:15
  But starting A company in Boston, it's like trying to swim through molasses.
• 16:21
  Everything is just hard.
• 16:22
  Recruiting is hard, fundraising is hard.
• 16:26
  You can barely even get to the.
• 16:28
  You can barely get off the ground because you're struggling with step point one and step point two of getting company off the ground.
• 16:34
  But one of the benefits of Silicon Valley is that you get the benefit of the tap.
• 16:37
  You know, people are often willing to invest in your vision with slightly less traction as long as the market, you know, perceived market is large enough.
• 16:45
  You know, people have more experience investing in startups and so they have, you know, they can ask more intelligent questions about, you know, the ways to think about your business plan and the ways you're thinking about the opportunity
• 16:58
  and the plan to kind of pursue that opportunity.
• 17:01
  And so I just.
• 17:03
  You just learn a lot about company building, being in Silicon Valley, because now suddenly the, you know, you're kind of in this petri dish of all these other successful companies and people who worked at these other successful companies
• 17:14
  and what they learned and other angel, you know, smart angel investors invest in a lot of successful companies and, you know, the pattern patterns that they've seen.
• 17:22
  And then you kind of learn quickly from that.
• 17:23
  And so things just move faster, which is great because, you know, time is of the essence for startups.
• 17:30
  You know, they think that, you know, startups, you know, startups are operating very short time frames because the resources are more limited.
• 17:37
  And so, you know, if things can move faster, that means more cycles for the company, more shots on goal, more faster learnings and therefore higher chance of success.
• 17:49
  Okay, all right, so after, after you spent your time there working at.
• 17:55
  Yup.
• 17:57
  Then you went on to, to start, to start Omnikey, which is your current company.
• 18:02
  So tell us what that company does.
• 18:05
  Yeah.
• 18:05
  So Omni Key generates and optimizes advertising campaigns and creatives.
• 18:09
  So what we do is we analyze performance, historical performance of advertising creative.
• 18:13
  So we integrate with your ad networks, your social ad platforms or display ad platforms.
• 18:18
  We discover what are the trends in terms of the creative, the design, the messaging that's resonated with consumers.
• 18:24
  And then we use those insights and generate content at scale.
• 18:27
  So oftentimes, business, they have multiple SKUs, they have multiple audiences, they're targeting, they have different platforms that they're trying to advertise on.
• 18:35
  And it's just a lot of work to create content in all those variations.
• 18:39
  If you have quickly the kind of the complexity, multiplier space on, you're trying to advertise, say 20 different SKUs on five different platforms.
• 18:47
  Targeting maybe a dozen different audiences, even that's suddenly very complex.
• 18:52
  And what we do is we have a system for creating all those variations based on data, and it results in significant time savings for our customers because what used to take months of work, it can now be done
• 19:04
  kind of within minutes.
• 19:06
  And then also results in higher ROI for their advertisers because now the ads are more effective, the ads more personalized, the ad's more relevant as it drives higher performance for our customers in terms of the roi, the return
• 19:20
  on ad spend.
• 19:22
  Okay, all right.
• 19:23
  And so this is using AI machine learning to do all this.
• 19:27
  And you started this in 2018?
• 19:30
  Yes.
• 19:31
  Okay.
• 19:32
  So at that time, vast majority of the world didn't know what AI is.
• 19:38
  We've certainly seen an explode in popularity since, you know, the beginning of 2023.
• 19:45
  But what was it like growing a company and, you know, at that time and pitching it to people when, you know, many people didn't really understand what AI was?
• 19:58
  I think, I mean, it's, you know, I mean, studying computer science at Harvard, you know, focus on machine learning, taking machine learning courses at mit, and then being in Silicon Valley, you know, at the kind of epicenter of
• 20:11
  a lot of this research technology, a lot of things I took for granted.
• 20:14
  You know, I thought, oh, it's pretty obvious that this is going to be massive.
• 20:17
  Just because I was seeing early signals of that, you know, from, from, you know, at least a decade ago and within.
• 20:25
  Yeah, when you're communicating with investors, you know, or even marketing, especially marketers who aren't necessarily in technology, you know, they're like, well, isn't AI all vaporware?
• 20:34
  Isn't it?
• 20:35
  It's not real.
• 20:35
  It's.
• 20:36
  It's always this thing that's in the future but never really arrived yet.
• 20:39
  And, and, but thankfully, we also were able to find customers early on in Silicon Valley that did believe in the AI and did believe in its potential.
• 20:48
  They were generally technologists.
• 20:49
  And so our first comp, our first customers and, and probably the first million in revenue was from other technology startups who.
• 20:58
  And marketers who work in Silicon Valley, startups who understood the potential for AI.
• 21:04
  And so, and also, you know, at the same time, I think there was this kind of give it forward mentality, you know, willing to also nurture and help other startups in the ecosystem.
• 21:11
  And so that was, that was beneficial.
• 21:14
  Again, I think if I was trying to start an AI company outside of Silicon Valley, maybe a bit of a slightly difficult and different story, I'm telling you right now, but luckily Being based in Silicon Valley, I was
• 21:23
  able to quickly find investors and angel investors and customers that were willing to quickly take a flyer on the vision and help us out.
• 21:34
  Okay, and then when AI and ChatGPT was released in early 23.
• 21:42
  Right.
• 21:42
  And it became so much more common, I mean, how did that impact the company and what you're doing in terms of like competitors or other market trends?
• 21:52
  Yeah, I, I mean it definitely increases competition, but also raises general more market awareness and it creates more opportunities as well.
• 22:00
  The, the online technology has also come a lot further along than, than what it was, you know, when I started the company.
• 22:06
  When I started the company, we'd have to like custom.
• 22:09
  There's this open source platform called Hugging Face and we'd have to take embeddings from Hugging Face and then custom fine tune these models would take us a day to onboard a customer so that we can generate copy that
• 22:19
  mimic their brand.
• 22:20
  And this was like in 2019, 2020, this was, you know, not scalable.
• 22:25
  Now with all these advancements in AI predominantly coming from Silicon Valley, a lot of these things are scalable.
• 22:32
  And so yes, there's more competition, but there's also more opportunity because we're now so much closer to this vision of a fully autonomous system that generates and optimizes ads at scale, manages your campaigns at scale, and does all
• 22:45
  the work that, you know, a marketing team or an advertising team traditionally did.
• 22:50
  Okay.
• 22:51
  And so your, your, your customers are creatives or just, just companies.
• 22:56
  Right.
• 22:56
  In terms of handling their, their business and their, their marketing on various channels and customizing it for, for that, that platform or that channel.
• 23:05
  Is.
• 23:05
  Is that right?
• 23:06
  Yes.
• 23:07
  And what do you see the biggest challenges that companies have, you know, when they're trying to do this or when they're trying to, I guess, market on all these various platforms and channels that are available to them?
• 23:22
  Yeah, I mean, I think like the systems they have in place.
• 23:31
  So for example, oftentimes the creative team might not have access to the data in terms of the performance and so be able to get the data from that company's marketing department and the creative team, which kind of tend
• 23:43
  to operate in silos is one hurdle.
• 23:48
  And so oftentimes we would run a POC just on the generative side without the creative, so without the analytics or depending on which team ends up being a beach head.
• 23:58
  So if it's the marketing team, then it's maybe that starts with analytics.
• 24:01
  If it's the creative team, then maybe it's on the creative workflows, but it really Is shocking how these two teams are so dependent on each other, are operating silos and actually don't have a lot of sway with each
• 24:14
  other.
• 24:15
  The marketers don't really understand a lot about design and are not very involved at all in the creative process or very limited involvement.
• 24:22
  Maybe they have some guidance but generally kind of kept separate from the creative department which has very little visibility of how their ads are actually performing.
• 24:31
  And so that, that especially, you know, the bigger the company that you go tends to be the case I think making sure, you know, customers having all their assets and brand information in one place so you know, the
• 24:46
  brand guidelines, their product assets and kind of organized in, in a very centralized way.
• 24:54
  Not that isn't always the case.
• 24:57
  Generally different marketing departments have different types of creative workflows and there's really infinite combinations of this.
• 25:04
  Some people, you know, some, a lot of marketing teams increasingly have their marketing in house but maybe their creative is outsourced, maybe their creative is in house, but the media buying is outsourced.
• 25:15
  You know, they may have a, you know, a large in house creative team.
• 25:18
  They may have like one person being their in house creator.
• 25:23
  And so and you know, even at the biggest sizes there's kind of different permutations of this and so and so there's kind of that organizational complexity.
• 25:34
  And then I think more kind of saliently especially the bigger the company go is like things, you know, concerns associated with copyright, concerns associated with indemnification.
• 25:45
  If you know you actually generate something that's IP violates somebody else's IP data security and safety.
• 25:53
  Is the data that I'm sharing with you not going to be leaked, not going to be used to train some other model that what could help my competitor is my data going to stay on prem.
• 26:03
  And then yeah, and then there's kind of like the tech stack as well.
• 26:06
  Like you know what is their tech stack that they use to build creative and launch ads and then do we need to build integration that and so yeah, I mean it's, there is kind of a myriad of different
• 26:21
  challenges that you know, for each customer when it comes to kind of implementing such an autonomous generative system.
• 26:28
  Okay, and so do you, do you target like a certain size company?
• 26:34
  Yeah, so generally we target mid market customers, companies that are kind of trying to scale their advertising.
• 26:41
  These are generally consumer oriented companies.
• 26:43
  So consumer finance or consumer e commerce companies, you know, a large percentage of our customers are e commerce companies with a lot of SKUs.
• 26:53
  Okay, all right.
• 26:54
  And then it sounds like too is there a solution Even for, for the legal challenges too.
• 26:59
  It sounds like you alluded to that in terms of like automating that.
• 27:03
  Well, I think when it comes to like the liability concerns, it's just there's still a lot of gray area.
• 27:07
  It's not always clear, you know, when an AI generates a piece of content, who's taking on the liability of that content.
• 27:18
  It really depends on the model provider.
• 27:19
  Some model providers take full indemnification.
• 27:23
  I mean, you know, let's say, you know, if you use our model, we're going to take all the risks to that.
• 27:27
  In some model providers, no, we don't take any liability.
• 27:31
  That's on you.
• 27:32
  And so there are different types of licenses with these open source, these open source models, different names, licenses.
• 27:39
  You know, some open source models are just purely for research purposes.
• 27:42
  You actually can't commercialize them or if you do commercialize them, you have to, you know, kind of figure out some kind of separate deal.
• 27:49
  And so yeah, like licensing issue with the models and underlying models, the copyright concerns regarding, you know, the models, you know, those are some of the different illegal risks associated with, with go to market of an AI product.
• 28:04
  Okay.
• 28:05
  And so in terms of your role as a founder, like you've already founded a couple other earlier, earlier companies and now with this one being the main one you're working on now, how is your, your role as a
• 28:17
  founder evolved?
• 28:19
  Like are you still hands on with a whole bunch of different things?
• 28:24
  Are you, are you able to delegate more?
• 28:26
  Like what, what does being a founder look like for you present day?
• 28:31
  Yeah, I mean I'm still very involved in, in, in, in, in, in everything we do.
• 28:38
  Marketing, product, you know, co fundraising.
• 28:44
  Probably the only thing I'm probably not doing is like actually writing the code.
• 28:47
  But I am, I'm pretty involved.
• 28:49
  I mean I'm currently speaking with our Sunnyvale offices, which is where our engineering team meets every day in person to build products.
• 28:55
  And so yeah, I would say I'm deeply involved in all the elements of the company.
• 29:01
  Okay.
• 29:02
  All right.
• 29:03
  And so you've been, the company's been in business six years.
• 29:07
  What's given your current growth, like what, what's next and where do you see, where do you see the company heading over the next like 12 to 24 months?
• 29:17
  Well, I think it's continue to just hone and refine the product, make it better, make it more, you know, more, you know, to a broader audience, keep adding additional capabilities to make it more useful for our customers.
• 29:28
  I think more kind of in the medium term there's kind of this agentic future that we're working towards where it really, you know, you have an agentic system automating entire marketing departments or advertising departments or creative departments.
• 29:39
  And so there's that kind of direction more on a financial sense, really working towards growing revenues and building product to power that revenue growth too.
• 29:47
  So we can IPO the company.
• 29:50
  Okay.
• 29:51
  All right.
• 29:51
  And let me just ask you another question with regards to AI and marketing.
• 29:54
  I mean, clearly, right, there's been all sorts of projections about how AI is going to change work as we know it.
• 30:00
  And some people think it's going to take jobs, some people think it's, you know, it's going to create a whole set of new jobs and really help automate some of the more tedious tasks.
• 30:10
  But specifically with regards to marketing, I mean, how do you see AI changing the role of marketing professionals in the coming years?
• 30:20
  Well, I think it's going to create jobs.
• 30:23
  I mean, absolutely.
• 30:24
  When you have a tool that improves productivity, which is what AI does, it creates jobs because it creates more value and results in GDP growth, results in more wealth for company and the country that these innovations are built.
• 30:40
  When a company is more profitable, you know, they're not.
• 30:42
  You know, most companies don't just hand that money back over to their shareholders.
• 30:45
  They tend to use that money to grow their business further.
• 30:47
  So it means they're going to hire more people.
• 30:49
  So if you can improve the efficiency of a company, if you can improve the profitability of a company, it generally means more in jobs because they're going to use that, the those profits for additional growth, whether those new
• 31:02
  product lines are launching, you know, new hires to improve their products or improve their marketing in different ways.
• 31:09
  So my concern is actually the companies that don't embrace AI, the companies that don't embrace AI are going to be out competed by the companies that do embrace AI and those companies are going to lose jobs and those
• 31:18
  companies will not be competitive.
• 31:21
  But if you do embrace AI, I think, and if you embrace AI properly and use it to power your growth, then that should result, you know, that will result in more growth, more profits that you can reinvest into
• 31:31
  hiring more people and kind of growing your business further with new initiatives.
• 31:37
  Okay.
• 31:38
  All right.
• 31:38
  And Hikari, if people want to get in touch with you, learn more about Omni Key and what you do.
• 31:43
  What's the best way that people can reach out to you?
• 31:46
  Yeah, so you can email me@hi omni.com.
• 31:50
  hi omni.com you can follow me on, on, on X on, you can add me on LinkedIn and I'm happy to add you back and, and also follow Omnikey, you know, Mnikey on Twitter or sorry X, LinkedIn, Facebook, YouTube.
• 32:09
  We're constantly producing content, updating our followers on, you know, cool, cool product demos, testimonials of our product, case studies of our product and we have a free trial.
• 32:26
  So actually any one of your listeners today can go to our website and sign up and try our product for free.
• 32:31
  All right, we'll link all that in the show notes for everyone so they have it.
• 32:35
  Okay, excellent.
• 32:36
  All right.
• 32:37
  Well, Hikari, thank you so much for being here, taking the time to, to share this journey, lessons from your journey and what you're doing now.
• 32:43
  We, we certainly appreciate it.
• 32:45
  Thank you, Dave.
• 32:47
  All right.
• 32:47
  And that is all the time we have for now.
• 32:49
  We will see you next time.