Automating Billion Dollar Brands

Diana Hu 0:00 [upbeat music] I'm excited today to welcome the founders of Confido. Here is Kara and Justin, and congratulating you on a $55 million raise for Series B led by Insight. So you almost didn't make it to Demo Day five years ago with this company. We'll talk a bit about that, but let's get started with what Confido is today.

Justin Hunter 0:27 So Confido's building the AI agent workforce for consumer brands. So think of any brand that you might see in your refrigerator or your medicine cabinet. They'll use us for everything from accounting to sales planning, to figuring out how many raw materials they'll need to actually produce their products.

Diana Hu 0:42 Who are some of your top customers that you can name?

Justin Hunter 0:45 Yeah. So we have divisions of companies like Mars and Unilever, some of the largest CPG companies in the world, and then high growth brands like Olipop and Dude Wipes and others.

Diana Hu 0:54 Pretty cool. And some of these are six, seven-figure deals. What exactly do you do for them?

Justin Hunter 1:00 What we're really, really proud of is just how broad the platform is. So we'll help with everything from accounting automation, to sales planning, to operational planning in a single system. So underlying all of this is the unique retail data that these brands have, and we use it to power key workflows across the business that automate labor.

Diana Hu 1:16 Let's go back to a little bit, uh, the origin story of Confido. I think you applied to the Summer '21 batch with a very different idea and different name. The name of the company was Outfit. Do you remember what it was?

Kara Holinski 1:31 Yes. Outfit was doing WeWork for fitness instructors at a time where a lot of fitness was moving outside due to COVID.

Diana Hu 1:39 And you two had met back in Boston. You were just graduated from MIT and Harvard and decided to do a startup, and it was during the remote batch.

Kara Holinski 1:49 Yes.

Diana Hu 1:50 What had happened to that idea? Because you basically didn't present to Demo Day.

Kara Holinski 1:54 Yes. So for that idea, we had some very sage group partners who told us it may not be the best idea as soon as we joined YC, um, and essentially told us that you need to pivot. And we looked at the numbers, and they were not lying. So we went through a long, long pivot hell.

Diana Hu 2:16 It was for, like, a year.

Kara Holinski 2:17 Yes.

Justin Hunter 2:18 Mm-hmm.

Diana Hu 2:18 And you were basically in the desert searching for water for an idea, and how did this idea come

Diana Hu 2:26 about?

Justin Hunter 2:26 Yes, it was interesting. It was an idea that was hiding in plain sight. When I was in college, I had worked for a couple of consumer companies. So I worked for a football helmet manufacturer that was owned by a family office that I worked for, and then I worked for Anheuser-Busch as well. I saw the problems that we solve today in those companies, and it's funny, even my parents worked on other, either side of these problems. So, uh, my mom was a retail store manager, so I lived-- I basically grew up in a retail store, and my dad sold software to largely consumer companies. So it's funny. I don't know why it took us a year, but, um, you know, it was, it was very much a hiding in plain sight problem.

Diana Hu 3:00 I mean, that's fascinating. You, you, the-- You had this idea within you this whole time.

Justin Hunter 3:04 Mm-hmm.

Diana Hu 3:04 But you thought it was too simple or it's not... it's nothing burger.

Justin Hunter 3:08 Yeah.

Diana Hu 3:09 But there's something that made you decide to go into this direction. What, what was that?

Justin Hunter 3:14 What was really interesting was when we were doing initial, like, discovery and validation, we chatted with some of the largest CPG companies in the world. We sent them cold emails, and they responded within a couple of days.

Diana Hu 3:24 Mm.

Justin Hunter 3:24 So we talked to companies like Coca-Cola and Dr Pepper, and all of these folks were just willing to talk to us for hours. I, I remember talking with someone from Coca-Cola and they were like, "Hey, do you have two hours?" And I thought, I thought they meant like, "Oh, can I call them back in two hours?" They just wanted to talk to me for two hours about their problems, and it just shocked me at, at just how manual and, uh, ultimately underserved this market has been.

Diana Hu 3:48 Do you remember that moment when you closed that first customer?

Kara Holinski 3:52 Yes. We actually closed our first customer with a Figma, so prior to writing a single line of code. Um, so yeah. I think that it was abundantly clear at that point that it was a real visceral pain and strong need, um,

Kara Holinski 4:11 when folks were willing to work with a shitty two-person startup. [laughs]

Justin Hunter 4:16 Yeah.

Diana Hu 4:16 The thing that might be counterintuitive is that CPG or consumer packaged good space is typically not very tech friendly. They're not usually buyers of tech solutions that much. But you figure out something, and something with the way you build the product, and AI has something to do with it. Tell us about that.

Justin Hunter 4:39 Yeah. What's really interesting is CPG brands are big buyers of services. They will buy BPOs, they'll work with consulting firms, they'll use these, what are called third-party brokers that they'll pay 5% of revenue to, to do work for them. So when we came with a proposition of, "Hey, we'll do the work for you," it's something they were very used to. And the way they talk about it is never as software. It's as, "Hey, is this replacing or augmenting the labor we might otherwise require?"

Diana Hu 5:04 What were some of these first, uh, workflows that you solved?

Kara Holinski 5:08 Yes. Our first workflow was around a very manual process of logging into many different portals and pulling down information, and then automating cash application and accounting workflows. And then from there, our customers asked us to keep doing more things for them.

Diana Hu 5:26 The

Diana Hu 5:27 interesting thing is that you're explaining basically things that traditionally a ERP or accounting system would do.

Kara Holinski 5:33 Yeah.

Diana Hu 5:34 But they were not using something like a NetSuite. Why is that, and how did you win versus those?

Kara Holinski 5:41 Yeah. So traditionally, folks have either used Excel sheets or disparate point solutions. So they will have one system that's a Postgres wrapper where they plug in all their information, and then they read it back to them. There hasn't been a sort of cohesive platform where the data flows in, um, automatically and the insights are driven agentically.

Diana Hu 6:04 So you basically got to the point where you're closing these six, seven-figure deals and charging the same price as a NetSuite, which took them about probably like a decade to get there.

Justin Hunter 6:14 Yeah.

Diana Hu 6:14 And you did it in less than two years.

Justin Hunter 6:16 No

Diana Hu 6:17 What's the value prop there?

Justin Hunter 6:18 So what's really cool within these businesses is we can touch almost every line item on the P&L. So there's heavy manual work that goes into these workflows across accounting and planning. We can automate that work and help them save on headcount. There's also outcomes that we can drive that they otherwise wouldn't be able to achieve. So an agent can reconcile down to a $10 transaction. A human never could. Um, we were actually chatting with a public company that just signed with us. They didn't review transactions less than $10,000 in this area because it was just so manual. So the system can not only automate the work they were already doing, but go chase after things they never otherwise would have gotten, so it's free money. And then similarly on the planning side of things, you'd be shocked to learn billion-dollar businesses are basically forecasting off of historical averages. Um, so there's just massive levers on every line item on the P&L that we can touch that an ERP would just

Justin Hunter 7:09 simply never be able to do as, as just ba- a basic database.

Diana Hu 7:13 When Confido is successful, how will the world change?

Justin Hunter 7:17 For us, if you walk into a retail store, we'll know if we've been impactful if we look and see the brands on the shelf and understand that basically every part of that process had been touched by Confido, whether that's procuring the raw ingredients, pricing the product, forecasting how much is on the shelf. If we touch all of those workflows, we'll have made a big impact.

Diana Hu 7:35 I think there's something interesting about you guys. You are all based in New York, and I hear that you don't have any product managers in your team.

Kara Holinski 7:44 Yes.

Diana Hu 7:45 How does someone who succeed working at Confido look like?

Kara Holinski 7:49 We have a group of amazing engineers who are very curious and very technical and able to drive to clarity in a lot of ambiguity. So one of our engineers, shout out to Ben, is our longest tenured engineer and is currently leading our new modules around supply planning. And, uh, he's doing everything from roadmapping and talking with experts and onboarding customers and enabling and being involved in the sales process. So we have some insane engineers on our end who are able to really just own super gnarly problems and drive to clarity and

Kara Holinski 8:31 solve them for our customers.

Diana Hu 8:32 Which seems pretty fun, having an engineer that has full ownership of the product-

Kara Holinski 8:37 Yes

Diana Hu 8:38 ... and customer interactions.

Kara Holinski 8:39 I think it makes it a lot more fun.

Diana Hu 8:40 All right. I think that's all we have. Thank you so much for coming and chatting with us.

Kara Holinski 8:43 Amazing.

Justin Hunter 8:44 Thank you.

Kara Holinski 8:44 Thanks, Diana. [upbeat music]