Navigating AI in Startups: What VC and PE Firms Look For
Welcome to today's episode of TGIM. Thank goodness it's Monday, Able's podcast that celebrates the joy of work, innovation, and the exciting projects that drive us forward. And today, we're talking to Arnon Bruno again, and we introduced him last time on our last episode. And I won't go into his very extensive background again. But essentially, he's an expert in AI with over a decade of experience.
Larissa:He's getting his PhD in artificial intelligence, and he is also our principal AI engineer here at Able. Thanks for joining us again, Arnon. So I just wanna dive right in. So you've been central to our partner AI conversations, and we work a lot with venture capital and private equity firms. So what I wanna know is what have you learned from what PE or VC firms want to see when it comes to startups incorporating AI into their business models?
Arnon:Yeah. That's a very good question. I think what I've seen so far is, like, PE & VC firms there are looking for a very clear value proposition that AI brings to business, like showing how it enhances efficiency, decision making, or customer experience. And something that I also notice is that they're looking to understand exactly how scalable AI can be. So how scalable the solutions can be in order for their businesses to also grow with the solution in the future.
Arnon:Right? So the solutions that they want to develop with AI need to be scalable enough to grow with the business. And also having a strong technical team capable of handling AI development and, deployment is crucial. So I I think they're also looking for people that can work with, those AI systems in a way that it could potentially derisk any scale up issue that might come up in the future. So those are some of the things that I have seen so far.
Larissa:Do a lot of these firms actually know the the potential of AI, or is it just a buzzword that they wanna jump on board with?
Arnon:Yeah. I mean, not all of the startups need to incorporate AI to their business models. Right?
Arnon:Yeah. Yeah. I mean, that's essentially I know that most of the companies these days that they're hearing about AI, they fear that they will be left behind. So they will miss this big opportunity, which is leveraging AI for their specific business model. But as I said, not all tech startups or startups as a whole need to incorporate AI into the business model.
Arnon:Right? So while AI can provide significant advantages, its necessity depends on, for example, the nature of the business and the problem it aims to solve. And I think startups should assess whether AI genuinely adds value to their core offering and aligns with their strategic goals. Because for some, traditional methods might be more efficient in terms of cost, also more effective. So incorporating AI just for the sake of it can lead to, like, unnecessary complexity and expenses without meaningful benefits, especially if you don't have, like, a lot of data to feed your AI systems.
Larissa:Do companies come to Abel without AI and then want to incorporate it? How how's that process work?
Arnon:Yeah. I mean, we have seen a lot of partners coming to us asking on how they could leverage AI to the benefit of their own businesses, and this is also something that we could do. So we also work on this ideation phase, so by combining their ideas with all of the things that we could do in terms of AI. So we also try and incorporate this AI consultancy service while interacting with partners and then use that to maybe provide them a very easy to understand and a very initial idea of how this AI system or how this AI idea could incorporate to their application. Right?
Arnon:And what we have seen so far is that most of them usually come to us with some data, and then we are capable of generating a very quick prototype and show them how this would work. But even for those partners that do not necessarily have data, we are capable of, you know, at least creating synthetic data to have a proof of concept and show them how this would work in the future in a way that we could develop something that is future proof. So it's prepared for whenever they have a lot of data, they probably will have this AI system working and ready to perform what they're intended to do.
Larissa:Oh, that's really cool. So then just in general, what are we building at Able whether or not this with AI or not, but or how are we incorporating AI?
Arnon:Yeah. Let let me focus more on the AI aspect of it. So we are building a lot of things for our partners and also internally. So internally, we're working with agents and generative AI to build chatbots. So we have couple of different strategies where we have seen that AI can help us be more efficient in terms of understanding documents, interacting with people, and eventually also helping in engineering.
Arnon:So we have seen a lot of benefit of using AI in our engineering teams by helping them to create automatic tasks, to increase the overall quality of our systems, to help us better understand the context of the code that we are building. So this is one of the ways that we are currently working with AI. But then I would also say that there's this component about AgenTek AI, where we have seen that there is a lot of possibility for us to use this great capability of AI to analyze massive amounts of data and combine this with our expertise. So combine the attention to details of AI and human expertise to create really good things that adds a lot of value to our partners. Partners.
Arnon:So these are some of the things that we have been building in terms of AI here at Able, and there's a lot more to come.
Larissa:Nice. I'm excited for that. Well, thank you, Arnon. This is amazing and very insightful. I learned a lot.
Arnon:Thanks a lot, Theresa.
