Show notes
Host Chad Pytel interviews Monik Pamecha, the Co-Founder and CEO of Toma, a company specializing in AI for the automotive industry. Monik discusses how Toma automates phone calls for car dealerships, enhancing customer service and streamlining interactions. Despite advancements in digital communication, phone calls remain crucial in the automotive sector, and Toma leverages AI to improve these experiences significantly. Monik shares his journey in the tech industry, detailing Toma's evolution from experimenting with different AI applications to focusing on voice AI. He explains the challenges and successes faced along the way, highlighting how AI technology has matured since his early work with chatbots in 2016. The conversation reveals how Toma's voice AI quickly gained user traction, validating their focus on this innovative technology. The episode also delves into the practical implementation of Toma's AI solutions in the automotive industry. Monik emphasizes the importance of integrating AI with existing dealership software and the gradual rollout process to ensure effectiveness. He discusses the need for clear communication about AI's role in customer interactions, reflecting diverse responses across different demographics. Monik's insights provide a compelling look at the future of AI in automotive customer service. Toma Follw Toma on X, LinkedIn, or Facebook. Follow Monik Pamecha on LinkedIn. Follow thoughtbot on X or LinkedIn. Transcript: CHAD: This is the Giant Robots Smashing Into Other Giant Robots podcast, where we explore the design, development, and business of great products. I'm your host, Chad Pytel. And I'm joined today by Monik Pamecha, Co-Founder and CEO of Toma, which provides AI for the automotive industry. Monik, thanks for joining me. MONIK: Hey, Chad, thanks for having me. CHAD: Obviously, in fact, as evidenced by the guest list that we've had over the last few months, a lot of companies are either integrating AI into their products or starting new companies. And you've been around doing AI for quite a while now. Tell us about Toma. MONIK: Yeah. So, Toma automates phone calls for the automotive industry right now, and we build a lot of different AI products as well. It's an interesting market, but one of the leading users of phone calls for doing business. So, a lot of the business, which is buying cars, you know, the first touch happens over the phone, you know, people bringing in their cars for service, getting updates, and all that, like, mostly happens over the phone, even though you have had websites and apps and all of these around. And to give you, like, an idea of scale, like, there are 290 million cars in the U.S. alone, which is, like, about 90% of the population has at least one car. So, scale is massive, and Toma is making that experience of getting service and just dealing with anything related to automotive, like, 100 times better. CHAD: So, I would encourage people to go to the website and check it out, because, I have to admit, I was a little skeptical, at first, about how good the phone call could actually be. And I was impressed by how natural it was, how it was able to respond in the video demos that I saw. So, how did you know that this was going to be possible? MONIK: I think a lot of it comes from our own experiences, I mean, not with automotive, but with technology. So, I've been in tech for a long time. I mean, I started writing code when I was, I think, 11 or 12, a similar story for my co-founders as well. But I've been doing machine learning research as well in the past. In fact, this was in 2016 when I wrote a paper on this as well, and we built a chatbot that was based on generative models. And, at the time, in 2016, it was really funky. Like, Google had come up with something called Sequence to Sequence, and we were using that to train it on a little bit of data that we had, and we had something that kind of worked. And, at the time, I was thinking that, I mean, when you were working with that, you'd see it, like, go off the rails and, like, do something really stupid. It couldn't even get grammar right. And, at the time, I saw all the holes that I was like, if somebody plugged these, like, you know, this would be phenomenal. Like, this is what it takes for it to work, you know, these are the places, more from a practical experience, right? Like, if you had to take it to production, like, what would you need to fix? And then, six years later, I see that things actually started picking up, right, like, they actually fixed all those holes. And it came back to me, and I was like, all right, this is the time. You know, those were the issues. They're all fixed. Now you can go ahead and build. So, I think a lot of it came from experience as to like, all right, this is what we should build, or this is why we should build, like, in terms of the technology. But we didn't really arrive at this idea, so to speak, you know, at least as a founding team. It was a lot of pivots. CHAD: What was the original sort of idea that you said, okay, we're going to start a company to do this? MONIK: Well, that was very different from this very, very different. So, my co-founder and I, like, most founders, like, the first thing they do is they try to look for problems that they themselves have. And we're like, huh, looks like...what do we have in common? We have some chronic conditions, and we've used diet to, you know, manage them. So, maybe let's build a tool to help, you know, patients manage conditions with, you know, diet recommendations. And we spent six months on that, and it went absolutely nowhere. Also, I think consumer products are just different. They require a different kind of thinking. But, you know, we were just trying to throw something on the wall and pray it sticks. And, you know, it was honestly pretty miserable because we got banned on a bunch of communities on Reddit and Facebook trying to promote it. And, like, all the people who tried our product they just never came back again, and, you know, things like that when you have something that people don't want, right? So, we see that side. I mean, and after that, we go ahead and we try to do...I think it was during it, I don't know, like, when you get a sense of, like, something's not going to work, where, like, then we realized maybe we should stick to what we know best, which is, you know, we're both technical. So, maybe we should do something that's, you know, more relying on those skills than something entirely different, which I think Y Combinator calls it founder-market fit. I think that's also very true. Of course, you can, like, build something for a business you know nothing about, but there must be some compatibility. So, yeah, we started with that, kept on experimenting. And then, I think, at some point, we were so annoyed that we made, you know, a list on Google Sheets. And we're like, all right, let's just, you know, vomit out 10 ideas that we have had, and let's write them all, and let's go after them one by one. Let's spend two weeks until we hit something that, you know, maybe we think has legs. And the third idea or the fourth idea on that was building something with voice AI. And, at the time, even that was, like, just a horizontal platform. That was it. All right, so we go ahead and commit to that. So, if we go through the list, try the first two or three ideas, I think the first thing was...then we went on the other extreme where we're like, all right, let's do something we do all day long, which is, as engineers, we are on call. So, you know, even at, I don't know, 2:00 a.m. in the night if your system is down, you get a pager on your phone saying, "Get on the computer and fix it." And we're like, how could we make that better? That was the first thing on that list. We spent some time trying to do it and, again, we kind of get that feeling. I think the more you fail, I guess, the better you get at detecting failure. I don't know about success but failure for sure it works like that. I think the third or the fourth idea was voice AI, and then we go ahead. We hack a prototype over a weekend and then put it out on...again, the communities that we know how to market were, like, Facebook groups and Reddit. And it picks up. Like, within, like, 3 days, we had 200 demo calls set up. And that just blew our minds because having been on the other side, we're like, oh, this is what it feels like when people kind of want something, what you have. I mean, it's still not clear, right? But -- CHAD: And you put it out there as automated voice assistant for businesses? MONIK: No, actually what we did [laughs], I mean, nobody will want to click that if you put it like that [laughter]. You know, just out of curiosity, I was like, "Hey, you know, I've built this thing. It does this, you know, what do you think? Do you think this has any use for you?" And that's it. Like, people are, you know, messaging me nonstop, like, DMing me that, "Can you please share it with me? You know, I run this business. This might be helpful." It was, like, more genuine. Like, I was just exploring, but, you know, that was a question that I posed. And that had, like, so many people show up, and they're like, "How about you just give us that and we can make money off of this?" And then, we started, you know, digging deeper, and we're like, oh, okay, it looks like you have so many manual processes and across industries. So, we had, like, some people from healthcare, some people from, like, you know, MLMs, multi-level marketing, so many different industries, optometrists, some in construction. Anyway, so we're, like, thinking at that point, huh, okay. Maybe there is something here. Again, no mention of automotive, no mention of dealerships, nothing. We had a single dealership then. And I would say this was, like, about six months. I don't even know how many months ago, but, like, a couple of months ago. I think, at the time, is when we applied to Y Combinator as well. CHAD: So, you applied to Y Combinator with the voice idea. MONIK: Right. And we put something out there. I forget if it was the healthcare idea or the voice idea, but it's probably one of the two. I mean, that's also the other thing about Y Combinator. I think they don't really focus on ideas as much as they just focus on teams, which I think is probably the best practice. You know, we pivoted again [laughs]. But yeah, so we did voice AI, and then spent some time just trying to do everything, right? Trying to build a horizontal layer for voice, where building assistance for all kinds of businesses. And, you know, one of the businesses, at the time, was a dealership. I always like to think of this as an arranged marriage, where, you know, we have the customer. We kind of work through it -- CHAD: So, you had an actual dealership that you were partnered with as sort of a expert in the industry? MONIK: Our first customer, right. And they were very progressive dealers, so they're always trying new things. And, at the time, we were working with a bank. We were working with some healthcare locations as well. We had some construction industry... whatnot. And we were going crazy trying to build something because everybody had these different requirements. And then, in practice, like, if you push AI out in the wild, to make it work, you need a lot of things, like deep domain expertise being one of them. So, that realization is happening, you know, where we're coming to terms with that. And, at the same time, it works really well for the dealership, and they bring another customer. And they're like, "Oh, they also want to use it," and we're like, "Okay, sure. We'll turn it on." Then we do it. And then, it works again. And then, they bring more customers. And then, we're like, wait a minute, you know, like, we're not doing any outreach. We're not pushing out anything, and it seems like customers want it. And then, there are these other places where we're struggling so much. Like, even with healthcare, you know, the regulations in banking and healthcare they slow down, you know, any sort of, like, AI implementations. So, even that world was very different with the automotive space. And you kind of do more of it and then you're like, oh, okay, looks like there is something here, and then we just decide to double down on that space. And then, we go further deep in and you realize, oh -- CHAD: Did Y Combinator...that can be a difficult decision for founders to make. So, did being in Y Combinator help you sort of give you the push to make that kind of bold decision? MONIK: At least from our experience, it's always been that they're, like, get to the truth very quickly, whatever it is, and then make a decision. Do not delay it. I think we were, in fact, slow to do that. I think they were probably pushing people to do it more because we saw companies pivot in our batch, like, two times, three times right before demo day, which is the end of the program. Like, two weeks before, they just completely changed the company, and that's completely okay. CHAD: So, how does an implementation actually happen? How does it roll out to a new customer? MONIK: I mean, this is also very new, right? I think as you come across new customers, you have to adapt the process. But the essence of it is that you first have some data to start, which is, for example, for us, we work with a bunch of call recordings because a lot of our customers are already recording a lot of their calls. So, that gives you, like, some data as to what the experience is like today. Then the next thing is you get an idea of what you know your customers want the experience to be like. And then, you're basically now figuring out the delta between the two. And then, you're configuring the AI agents, making sure, testing it. And then, you have, like, a period of, like, a week or so where you get through all of that. Then you work through integrations with existing softwares. That also, by the way, is another, like, I would say automotive is a sleeping giant. Like, an auto dealership, on average, like, per month will be spending $50, 000 on software. CHAD: Wow. MONIK: Because the whole business runs on software—everything starting from sales, inventory, parts, service, everything, repair orders—all of it comes through that. CHAD: Now, is there a single common platform that a lot of dealers are using? MONIK: Unfortunately, no. There are some major players; CDK Global is one of them, which actually was hacked recently. And it's in, like, over 15, 000 dealerships, and all of them shut down. CHAD: Wow. MONIK: Like, they just couldn't do any business, and they had to come up with creative workarounds. So, it was pretty painful, kind of, like, a COVID, you know, COVID moment for them. And then, yeah, we've been trying to help our dealers, whoever used that software, to, you know, again, come out with workarounds, where the AI is actually capturing all the information. And, you know, instead of dumping it into that system, it's, you know, finding workarounds on how to get it to our dealers. But yeah, so you integrate with them. That is, like, another major step. And they're, you know, they're not the most tech-forward companies so, you know, that can be a little challenging. CHAD: Right. So, they use a lot of software, but they're not necessarily tech for...they probably don't have big IT departments and that kind of thing. And then, the users are probably non-technical. MONIK: Correct. Yeah. The thing about dealers, I think, is th…
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