Are you an angel investor looking to navigate the AI landscape and make strategic investment decisions? In this episode of The Angel Next Door Podcast, host Marcia Dawood sits down with special guest Katie Taylor, the CEO of Narratize, an innovative AI company. Katie shares her journey in the AI space, from her time at Purdue University to becoming one of the seven developer ambassadors advising OpenAI with ChatGPT. She explains how Narratize’s approach to AI differs from other companies, emphasizing the importance of large language model agnosticism and responsible AI principles. This episode is a must-listen for investors seeking insights into the evolving AI marketplace and the strategies they can employ to make informed and impactful investment decisions. This episode offers a compelling exploration of the AI marketplace and the critical considerations for angel investors. Katie’s perspectives shed light on the evolving landscape of generative AI and the potential for its exponential growth. With insights on security, privacy, and diversity in AI leadership, this episode equips listeners with the essential knowledge to make informed investment decisions in the dynamic AI space. Whether you're an experienced angel investor or someone interested in the world of AI entrepreneurship, this episode provides valuable insights and thought-provoking discussions that make it a must-listen for anyone interested in the intersection of AI and investment.
Are you an angel investor looking to navigate the AI landscape and make strategic investment decisions?
In this episode of The Angel Next Door Podcast, host Marcia Dawood sits down with special guest Katie Taylor, the CEO of Narratize, an innovative AI company. Katie shares her journey in the AI space, from her time at Purdue University to becoming one of the seven developer ambassadors advising OpenAI with ChatGPT. She explains how Narratize’s approach to AI differs from other companies, emphasizing the importance of large language model agnosticism and responsible AI principles. This episode is a must-listen for investors seeking insights into the evolving AI marketplace and the strategies they can employ to make informed and impactful investment decisions.
This episode offers a compelling exploration of the AI marketplace and the critical considerations for angel investors. Katie’s perspectives shed light on the evolving landscape of generative AI and the potential for its exponential growth. With insights on security, privacy, and diversity in AI leadership, this episode equips listeners with the essential knowledge to make informed investment decisions in the dynamic AI space. Whether you're an experienced angel investor or someone interested in the world of AI entrepreneurship, this episode provides valuable insights and thought-provoking discussions that make it a must-listen for anyone interested in the intersection of AI and investment.
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Marcia Dawood
Well, hi Katie, welcome to the show.
Katie Taylor
Thank you so much for having me.
Marcia Dawood
Well, I am excited to talk to you because as a consumer, I have learned obviously, about AI through chat GPT, like the rest of the world has. But there are so much to know and as angel investors, I think we really need to get some kind of like a benchmark or some way that we can start to look at and due diligence on companies that deal with artificial intelligence. So, since you are the CEO of Narratize, which is an incredible AI company, I would love it if you started with your background and tell us a little bit about what Narratize does and how it's different than the other AIs that are out there.
Katie Taylor
Well, first of all, I'm a huge fan of your podcast and so grateful for all of the angel investors in the world. Narratize would not exist without you. So thank you for paying attention. I'm sure you're inundated right now with generative AI deal flow. So happy to share my perspective as an AI leader founder. My story is I've been in AI for about three years. Originally, I did my PhD in narrative science at Purdue University, and I founded my first company while I was still there and grew it over the last decade. And the problem that we look to solve, we solve today at Narratize.
Katie Taylor
It's the problem of enterprise communication, internal and external, in science, tech and medical industries, where the subject matter is complex and it's oftentimes deeply technical. Our vision is to help those enterprises share their boldest ideas in a way that helps them get internal and market traction. And really spent the first six or seven years of running my first company doing that without artificial intelligence, even though my degree was really around the formation of language narrative algorithm. And so I was really, I think, primed to enter the world of AI, as it turns out, because of that unique blend that I had, that me and my team had around narrative science, data science, and really understanding enterprise communication challenges. We were actually tapped by OpenAI, which is the company that launched Chachipt, of course, as everyone knows. And we became one of seven developer ambassadors into OpenAI three years ago. And that came right on the heels of us completing a longitudinal study alongside our enterprise customers at the time, where we were looking at the idea of innovation storytelling. So how do your teams internally and externally communicate their innovative work? And what narrative algorithms show up within research and development and product innovation and marketing that help them get buy in? And as we were finishing that work, we were know working with OpenAI and their earliest versions of GPT.
Katie Taylor
And so the light bulb went off and we said we could solve this challenge at scale and help science and tech and medicine tell the right communications, tell the right stories if we build it with this incredible large language model technology. And we've been growing and tackling that challenge ever since.
Marcia Dawood
That's incredible. Okay, so go back a little bit. Tell us a little bit about what it has been like to be one of the seven people who are advising OpenAI with chat GPT. Tell us more about that. Did I get that right?
Katie Taylor
Yeah, that's right. So chat GPT is the consumer facing chat bot version that sits on top of the large language models developed by OpenAI. And so OpenAI has several different LLMs, as they're called. And we were first working on GPT-3 essentially, and then we continued to be developer ambassadors, and now, of course, they're launching four and five, et cetera. And really what it meant was weekly meetings where we were following those updates. We were supporting and helping to create understanding around enterprise use cases, et cetera. So those were really the earliest days of Narratize, and we're very grateful for that partnership. I think as angel investors.
Katie Taylor
Right, as you weed through the ocean of opportunity and deal flow in this space, it's important to look at the back end technology. And I know you already know that, but looking at the vast number of large language models that are being developed today, and I think sometimes that word gets thrown around a little bit too easily. And sometimes I hear folks say things like, oh, we're building an LLM. Well, most companies cannot afford to spend the billions of dollars required to build a large language model. But that doesn't mean there's not a strong marketplace of LLMs. Everyone from meta to Google to Nvidia been creating their own over the last several. So, you know, while our relationship with OpenAI was part of our origin story, we decided very early on that narratize itself would not only call into the GPT models coming out of OpenAI, we would be large language model agnostic. And we did that because we knew in order for the Enterprise to extract the highest quality outputs and the best value from generative AI, they would need to have the capability to call across multiple large language models.
Katie Taylor
And on top of that, because responsible AI is a North Star for us and it's a North star for so many enterprises. Those are the ones who, by the way, we're most excited to work with. We believe there will continue to be a competitive pressure in the marketplace for those foundational AI model companies to outcompete when it comes to transparency, explainability and ethical bias training, things like that. And that's what we look for. And so we essentially said, yes, we're excited about GPT, but let's leverage all of the various LLMs and essentially give the Enterprise the power to toggle on or off the right one, and allow us to design and embed AI into people's workflows in a way that helps them have that power and extract value across.
Marcia Dawood
Interesting. So explain exactly what Narratize does and how it's different than the other AI softwares that are out there today.
Katie Taylor
Yeah, so at Narratize, we support divisions across the entire enterprise. We do tend to sell into the Fortune 1000, and we support their teams with communicating and writing content that they could never write in chat GPT effectively. So things think of like everything from a technical report to a project proposal, to an external facing white paper or research report or insights article. These are the types of use cases that we build into our core technology at Narratize, and then on top of it, we strongly believe that the right spark for AI transformation, like true adoption across an enterprise, will come by embeding AI into your team's existing workflows. And not expecting everyone to become a senior level prompt engineer who's going to change all of their workflows to center around a chat bot. We know everybody's really excited about chatbots, and we are expanding into some of those features too, around AI assistance inside of Narratize. At the same time, our core belief today is we use a reverse prompting architecture. What that means is as a user, when you log in, instead of being met with a blank screen and a blinking cursor, Narratize dynamically knows what questions to ask you to help you get your work done.
Katie Taylor
And so that looks like prompting you with questions. Tell us about the problem this is solving. Tell us about the communication you need to share. Who do you need to report this to? Who do you need to amplify this with? And it builds based on the human's ideas, but it also guardrails those ideas using a very unique data architecture that we're creating with industry and domain expertise. And so that creates guardrails around what's output. And on top of it, like with the top performing AI companies, we're building really exciting rag architectures that enable us to train on the enterprise's existing corpus of knowledge, so that what you're outputting is not just following industry and domain, best practice. But it's drawing on the tacit knowledge that lives within your unique enterprise, and that's really where the value gets unlocked, is it's human led, it's large language model agnostic, and it's drawing on your company's historical and current knowledge that's very.
Marcia Dawood
Interesting, very different than what we know chat GPT does.
Katie Taylor
Right? Yeah, yeah.
Marcia Dawood
So I know at one point when we were talking in the past, I was understanding that narratize is also kind of doing everything in its own vacuum. Maybe, I would say maybe that's not the right word for it, but just the idea that I took away from it was some of the concerns around chat GPT have been around that they're pulling things off the Internet, some of the things are false. You could end up asking it a question and it'll give you an answer that looks to be true, but it's maybe not. And a lot of the things within narratize, there's privacies and different ways that narratize is able to protect the intellectual property.
Katie Taylor
Yeah, protection, yeah, absolutely. I think there are two sort of dynamics to what you're describing. On one side is security and privacy. So how do you protect customer data? So we made a commitment very early on because we wanted to serve the enterprise and accelerate their rates of innovation. We had to protect their IP, we had to make sure that the customers data never went to training a large language model and that it could never leak. And so that's the number one again, another north Star for us, it's one of our responsible AI pillars, is security and privacy. The second part of that is how do you get a large language model to produce an answer that is actually accurate? And that is really complex, technically, actually, because it is trained on the Internet, and the Internet is full of lots of different types of information. And what that means is it's a lot easier for something like Chachi PT to create misinformation and our belief, because our mission and our vision is a world amplified by bold ideas, and to help science and tech and medicine tell the right story.
Katie Taylor
Those are industries that are called highly reliable industries. That means the margin for error is so incredibly small and there are lives at stake when something is, when information is propagated in the wrong way. And so that's really critical, I think, as you are evaluating and working to understand the AI marketplace, look for those startups and those companies that have really, number one, prioritized security and privacy features in order to create ridiculous scale right across enterprise use, you have to tackle that first and you have to get that right. And then, number two, I think those who are building into domain and industry specific knowledge based architectures are also going to have much stronger accuracy rates. And that's really critical if we want a world where AI can be trusted.
Marcia Dawood
Right? So you mentioned, like, for example, the medical community using it, and there's obviously very small margins of error that could ever happen there. So can you give us an example of how they might use Narratize and how it would help to accelerate treatment plans or even cures for certain diseases?
Katie Taylor
Yes, absolutely. So for Narratize, today, most of our medical industry customers are on the research side. We do have clinical researchers in the platform today, one of our largest customers is a very well known large pediatric health system, and they're conducting research every single day. Much of that research is not just quantitative data collection. Right, but qualitative data collection, meaning patient interviews, caregiver interviews, and some of our story building and research hub features enable those research teams to essentially ping one or 1000 or 1 million different populations and get them to answer a series of prompts and generate their own testimonials or their description of a challenge or a pain point that they felt within their patient journey. And this is unlocking for those research teams beautiful, human rich insights into the patient experience, into the caregiver experience, into the provider experience. And it is shaping how we think about treatment and how we think about everything from mental health implications of disease to the ways that we track and understand how diagnoses lead to certain experiences for patients at the ground level. So that's one really exciting use case that our customers are using in the medical.
Marcia Dawood
Very interesting. So what do you think are some of the things in the future that we're going to see with AI? Is it going to keep accelerating at the level that we've seen it accelerate? And we didn't even know what chat GPT was until around November of 2022. And here we are, like not even 18 months later. And I feel like there are just so many options of what we can use related to AI. Now there's AI incorporated into things like your email. It seems like every type of company is trying to incorporate AI somehow into their workflow. So what are your thoughts on how it will be over the next couple of months, years?
Katie Taylor
Marcia, you're completely right. So, according to Business Insider, the cagar for the AI marketplace and just generative AI alone is 42%. And so it's expected to grow from 40 billion in 2022 to 1.3 trillion over the next several years. 93% of companies say that they're actively seeking to buy Gen AI solutions.
Katie Taylor
Most of them today are still in the exploration or proof of concept phase. Most of them haven't deployed it at scale yet. So this is coming, and it's not slowing down anytime soon. When you look at some of those charts and you see the bar charts say that 70% are in exploration and only 15% are at the pilot stage. As proof and ROI and outcomes and feedback start to resonate and amplify over the coming months and especially years, that adoption will scale dramatically.
Marcia Dawood
So what are your thoughts around what we can do as angel investors? To be smarter, maybe, or just do our diligence. When we are looking at a company that either is a full AI company or there's like an AI component, what are some of the things that we can do to kind of protect ourselves and know, is this something that's long term, or are we looking at something that's a flash in the pan and we may lose all our money very quickly?
Katie Taylor
Yeah, I think there are probably two or three key points to make around that. Number one, be wary of the wrapper. And I think most investors are attuned to this now. But if the solution is truly a wrapper around one large language model, most traditional one being an API call into GPT. So if the tech stack diagram just shows one call into GPT as an API, I think to be wary. I think unless the application is so niche and has so much power to scale that way, that's not going to outcompete at scale. So I think be wary of the wrapper and watch for that as you look at tech stacks. Number two, you have such an important opportunity to make diversity in AI better.
Katie Taylor
Look for founders who don't necessarily fit the traditional AI leader role. And perhaps I say that with a bit of bias because I am a very unique female founder in AI and my co founders are also women. When you look at the statistics, it's remarkable and it's deeply unique. And when you look at the statistics, women who lead AI companies get 0.3% of the venture capital that goes into artificial intelligence. Bias is already so challenging in venture, but when you look at it in AI, it sort of becomes abysmal. And I think we have a way to change that. The enterprises that we sell into at Narratize believe in a strategic imperative, not just around their adoption of AI, but around diversity, equity, inclusion and accessibility. And we align with them in those ways and help them amplify both imperatives at once.
Katie Taylor
We're not a DEI solution, but the way that we build is set through our north stars around responsible AI. And so I suppose my point here is there's .2 Part A, which is fund diverse founders in AI, and there's a part two B, which is look to those companies who are clear about their pillars of responsible AI. At narratize, those are being human led, doing AI for good intent de I and prioritizing de I in the way that we build, being secure and private, and finally being explainable and transparent. Those are our core pillars and everything that we do will be centered around that. And we believe that AI is going to experience increased pressure to be explainable and transparent from the enterprises and the companies and the people who use it. In the same way that sustainability really grew from consumer pressure to be more environmentally friendly, to be more circuitous in the way that we design and use materials. And so unfortunately, that part of business didn't really spark up and become such a strategic imperative until there was market pressure. And I think that with AI, we have a chance to get it right from the start instead of figuring that out later.
Katie Taylor
And I strongly believe that the AI companies that prioritize that from the start will win and be the sustainable ones that grow forever.
Marcia Dawood
That's great. Well, Katie, this has been very informative. Thank you so much for coming on and telling us all about Narratize AI and what we can do to make sure that we're looking out for the right types of companies to invest in, because this is a little bit of the wild, wild west, but there's a lot of opportunity and some really cool things happening, so we don't want to sit on the sidelines for sure.
Katie Taylor
Thank you to everyone listening for the impact that you make as investors. I would not be where I am today without you. And I'm so grateful for the dialogue that we're having.
Marcia Dawood
That's right. Because you just did close around.
Katie Taylor
Yeah, that's right. We've had several incredible angels. Part of that in the earliest. So. So grateful for that. Yes. Cheers. Cheers.
Marcia Dawood
Cheers for that.
Katie Taylor
Thank you. All right.
Marcia Dawood
Well, thanks so much, Katie.
Katie Taylor
Thank you. See you soon.