Ishar (presenter) describes market prioritization strategies for AI startups: focus on small, high-value niches with potential "domino" effects rather than chasing the largest, most-competitive markets. Use early technical stability and domain-focused 100% solutions to build credibility (examples: Tesla targeted sports car enthusiasts; Amazon focused on books). Leverage partners (AWS) and halo effects across verticals to drive adoption. The speaker emphasizes an explicit mission—"build more capable and ethical AI" (limit bias, preserve privacy, democratize access)—and targets human-centered AI products for consumer devices (smartphones, smart home, teleconferencing, driver monitoring). In Q&A, he advises finding technical and business advocates inside organizations, recognizing latent demand by internal teams building solutions, and choosing bottoms-up or top-down approaches depending on product and buyers.
Chapters
With that base, but also helped establish an elite brand and ultimately drove struck network effects. But the team early on was also full of technologists. So they focused on the stability of the technology, stability of platform. And that allowed them to differentiate their offering from others in the space. As we, as you enter new markets, it's important to kind of look across and identify dominoes that may exist to drive of favorable adoption dynamics. So in AI it's that space that we play in. It's a lot of majority of companies follow industry leaders. So it's important to target those industry leaders. It's important to showcase success in a couple verticals and there's kind of halo effects that then drive adoption. To go back to a familiar example, let's look at Tesla. When they started, they realized to get to low cost mass production, their ultimate vision, they first have to change the perception of electric vehicles cars. It targeted a very small group of sports car enthusiasts to ultimately help make the electric cars cool. This helped propel the brand in the mainstream, tip the dominoes into a larger market with the Model S and a large market with the Model 3. So they use these small markets to tip into larger and larger markets, setting up the dominoes for more mass adoption. Also I think it's important in the early stages to really look for open lanes around competition. Instead of chasing the largest space which oftentimes has the most competitors. It's tempting to chase the largest opportunity. But I think oftentimes there are a lot of white space opportunities that are strategic that allow you to ultimately build a more interesting solution. And I think one of the questions we always ask ourselves is can we provide 100% solution for a particular high value vertical? Can we own the home market for this particular niche? I think a great example of this, a classic example is this is Amazon. They focused initially on selling books online, but they provided 100% solution for books before they even thought about doing anything else. And this really allowed them to understand and validate the online channel to consumers. They built capability they were able to leverage into other domains and other types of products. And ultimately they built strong customer relationships that allowed them to cross sell and build these long standing relationships. It's important that you don't work in isolation and that you leverage your network and your experience of your partners. We've had a lot of support from aws, outside support. You know, as a small company they've provided us great kind of visibility across current and future needs and trends, allowed us to leverage the ecosystem to validate our assumptions and ultimately gain introductions to key clients. So it's important that you don't work in isolation and you really lean on your partners and their experience to gain that insight. Kind of. To summarize, you know, we. You have to identify and stick to your mission. Identify your North Star, stay true to your DNA and leverage your core, core strengths to compete in the marketplace. Identify dominoes to drive faster early adoption and look for open lanes around your competition to kind of help differentiate and scale faster. Where we ultimately landed is we have a mission statement, as I mentioned, to build more capable and ethical AI. This relates to limiting bias, preserving privacy and democratizing access to these AI systems. We identified certain dominoes within the industry around certain types of products and use cases and leveraging halo effects from other industries to kind of ultimately drive us to human centered AI systems. Working with smartphones, smart home teleconferencing, driver monitoring and AI systems in this space. Well, I wanted to kind of thank everybody for kind of listening to me at 7 o' clock in the morning on a Monday morning. And I'm happy to kind of open it up to questions. All right. Okay. So one question I think that often comes up is, I think in these markets is, you know, why not chase the largest opportunity and let me kind of maybe speak to our particular use case and kind of why we decided to go kind of a different route initially. So the, I think the tempting thing in computer vision and a lot of companies have gone this route, especially with synthetic data or simulation and computer vision, is to look at autonomous vehicles. Right? Lots of consumption, lots of investment place where it seemed obvious to go with the technology. But when you look at the space from a 20,000 foot level, there's a lot of competition, a lot of not only from external vendors that we may compete with, but also with internal teams. Right. So if you look at Tesla or Waymo, others, they're building these internal capabilities. And so for us it was important to find an area that we can potentially own, moving into more consumer centric devices and also this align much more with our mission, which is to create more ethical AI systems and help deal with some of the issues around human centered data that exists, privacy, bias and other elements.
Feel free to drop any additional questions in the Q and A or in the chat below.
Okay, we have a great question coming in here. What should one focus on when there is latent demand and there's no single owner in decision making? Yes, it's a great question. I think one of the signs we always look for is that there is latent demand and oftentimes you'll see internal teams trying to build solutions which is a great kind of indicator that there's something there that you need to build. Now identifying a decision maker in an organization, it's completely, you know, could be a whole 50 minute talk onto itself but ultimately it's, you have to find someone who's going to be an advocate for you. We find that there's usually a technical advocate and a business driver advocate so and depending on the product you may have to go bottoms up through the developers or come come top down to the business heads. We found the kind of the right mix for us at least in our in our product was to find and influence kind of the technical buyers initially or the technical users and have them influence the business buyers.
Awesome. If there are no more additional questions, thank you so much Ishar for that great session. We'll have a lot more content throughout the day. Thanks for joining Sasra early.
Well thank you. Thanks everybody, I appreciate it.
