A Product Market Fit Show | Startup Podcast for Founders
00:00:00 · Sean McCarthy
[00:00:00] S0: So what we started doing was just building the use cases for the customer and giving them the entire use case, and the ROI analysis that they could present to their board with their branding and all the information that we've gathered to try to make it as light of a lift as possible. Candidly, the platform that we had set was just not built for that scale, and so we made the tough decision to stop selling and just rebuild the platform and so we rebuilt the platform to make it an enterprise-grade AI platform. And then we introduced this AI process center, which alleviated the burden of getting all of this in from the human head. The biggest hindrance we had was, let's say I'm selling to you. You're like, all right, that sounds good. Let's get started. We'd sign the contract, and we'd say, just send us the SOPs that you have for the process, and that's how we would get started to train the agent. And we would go into months where the customer would just kick the can down the road to not write up an SOP. Because nobody wants to sit there and write an SOP, or they have them but they're old. So what we did is we created an SOP recorder into the platform and so they can go to our platform. It records the screen, obviously records the audio, and tracks all the metadata from the clicks. And that's how we build out the SOPs.
00:01:12 · S1, Pablo Srugo, Sean McCarthy
[00:01:12] S1: That's product market fit. Product market fit. Product market fit. I called it the product market fit question. Product market fit. Product market fit. Product market fit. Product market fit. I mean, the name of the show is product market fit. [00:01:24] S2: Do you think the product market fit show, has product market fit? Because if you do, then there's something you just have to do. You have to take out your phone. You have to leave the show five stars. It lets us reach more founders, and it lets us get better guests, thank you. Sean, welcome to the show, man. [00:01:40] S0: Thanks for having me. I'm looking forward to it. [00:01:42] S2: Same here, dude. You're on one of those now-becoming classic AI stories, right? You started less than two years ago. You've raised over $30 million now, doing millions in ARR and growing very, very fast. And you were telling me maybe a few months ago, you were going up against a very well-known, we won't say the name, but a very well-known, like, large AI enterprise. One that we would all recognize, on these two large enterprise deals and you're putting your best foot forward, but you also effectively assumed that you're going to win neither of them because, you know, long odds. And you didn't win one, you actually won both. Tell us that story because that's kind of the product market fit moment.
00:02:24 · Sean McCarthy, Pablo Srugo
[00:02:24] S0: Yeah, I'm happy to. I actually told our board members that I thought it would be a five percent chance and don't get excited about it. Just because I thought it was such a long shot. At the time, and especially when this started, all the way to as we came to the end of it last year. We were still, I mean, less than, obviously, two years old. This company, as you mentioned, is very well known and I just felt like it was, a David and Goliath kind of scenario. And so I told them not to get excited, did everything we could on our side to show that we deserve to be in the race, and were able to give, and go above and beyond on some of the documentation, that we provided and where this goes. And yes, we're early, but this is where it will end for you if you utilize us. And didn't hear anything on both of these deals for, probably two months and just kind of considered them DOA, and then received an email randomly asking for all of our SOC 2 information and, you know, security infrastructure documents and all of these things. And got, obviously, a little excited that maybe there was something here. And told the team actually the same thing, don't get very excited. I don't think this is going to happen and then we were finally awarded the deal officially. It was an incredible moment for us and really changed some of the trajectory of the company. [00:03:45] S2: What size deals are we talking about?
00:03:45 · Pablo Srugo, Sean McCarthy
[00:03:45] S2: What size deals are we talking about? [00:03:47] S0: Entry points are six figures. So you're looking $200 000 to $300,000 on those deals. But we have a usage component on top of that and then where this goes, those should clear to seven-figure deals next year. So that's kind of our entry point. But for us, they're also major logos. So really, like leaders in their spaces. So along with the deal size is just kind of that marker of getting those number one or number two folks in those verticals. [00:04:13] S2: Maybe tell me a little bit about what your company actually does. It'll help with some context. [00:04:17] S0: Yeah, so BackOps is an AI-native shipping operating system. What that means is we've templatized much of, specifically around the warehousing last mile. On problems that you can think would happen to a package or a pallet, like maybe it's lost, stolen, damaged, and then what would be the downstream effects of something like that. Or maybe if it's a temperature breach, you can imagine there's a lot of paperwork, claims that need to be filed. We'll ingest that information. We'll chase down and gather all the documentation and then make sure that our customers file. In that case, one hundred percent of the claims, or it's reshipping a package. But that's being handled autonomously and so we're taking a lot of the repetitive work from the back office. And then very quickly branching that out into adjacent business units like finance or customer service or ops. Depending on where we start.
00:04:17 · Sean McCarthy, Pablo Srugo
[00:04:17] S0: Yeah, so BackOps is an AI-native shipping operating system. What that means is we've templatized much of, specifically around the warehousing last mile. On problems that you can think would happen to a package or a pallet, like maybe it's lost, stolen, damaged, and then what would be the downstream effects of something like that. Or maybe if it's a temperature breach, you can imagine there's a lot of paperwork, claims that need to be filed. We'll ingest that information. We'll chase down and gather all the documentation and then make sure that our customers file. In that case, one hundred percent of the claims, or it's reshipping a package. But that's being handled autonomously and so we're taking a lot of the repetitive work from the back office. And then very quickly branching that out into adjacent business units like finance or customer service or ops. Depending on where we start. [00:05:05] S2: Maybe walk me through a type of customer and a specific package. And what would normally happen, and what happens with backups.
00:05:11 · Sean McCarthy
[00:05:11] S0: Yeah, so to conceptualize this, and obviously in supply chain, there's not a lot of folks that are really familiar. And so I'll give you a very basic example, and then a more complex example of what we sell for today. Because when we started, we were handling the very basic examples, selling to mom and pop warehouses, 3PLs. And you can think of it as a consumer where you order a lamp, and the lamp gets shipped to your house, it's broken. As soon as you open the box, you realize it's broken, you call customer service and you say, hey, I just ordered this lamp, send me a new one. They're going to assign that to operations, operations will send you your new lamp, and then they have to file a claim with, say, FedEx. Because FedEx broke the lamp, and then finance needs to track that to make sure they get their money back. That's three business units on a fairly non-complex workflow, being a lamp that's broken and so, when you take that to a much higher complexity. Say we're talking about grocery where you have a truck of food that might have Tyson's chicken and berries from Driscoll, and Happy Egg, and all these different vendors on that truck. And maybe the temperature on the refrigeration unit breaks or exceeds where it's supposed to be. What happens then, right? Now you've got all of these vendors at a much higher complexity with invoices and BOLs, and documentation that needs to be gathered. And so, rather than somebody going and doing these manual reports, they can just pick up the phone from the loading bay and say, hey, we just received this truck. There's a temperature breach, and we'll take it from there, run and gather all the paperwork, and make sure that a hundred percent of those claims get filed. Which is millions of dollars a month on these larger enterprises and so, that same scenario can be done with pharma, with lifesaving medicine as an example as well.