How Indico Raised $4.5M and Reached 20 Customers, Three of Them Big Financial Services Firms (Interview with Slater Victoroff)

Nathan Latka

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01:58see you there. Nathan Latka here. Good morning, guys. How's everyone? You're really gonna enjoy today's episode, and tomorrow is even more fun. You'll you'll learn from Neil Desana of Senna Hill. They transacted over $200,000,000 in the financial technology industry in 2016. Many of you guys are very interested in fintech. You won't wanna miss this. He gives me his seven predictions for 2017. Good morning, folks. Nathan Latka here. Our guest today is Slater Victoroff. He is the CEO

02:26and founder of Indico Data Solutions. He's a poet, a coder, an MMA fighter, vegan Buddhist, and red letter Christian. Slater, are you ready to take us to the top?

Slater Victoroff

02:35I'm absolutely ready, Nathan.

Nathan Latka

02:37Maybe my most favorite bio I've ever read.

Slater Victoroff

02:39Oh, perfect. That's what I was aiming for.

Nathan Latka

02:41Alright. Tell us what Indico does and how you make money.

What Indico Does and How It Makes Money

Slater Victoroff

02:44Yeah. So Indico at the highest level is a text and image analytics provider. We focus on a specific area of deep learning called transfer learning, and our focus is on allowing people to make their own text and image analytics with very little data and be able to deploy it in a variety of situations. Specifically, right now, we make money, particularly selling this into financial services, and we found a really good sort of use case for the

03:13analytics suite that we provide in managing information overload for investment analysts.

Nathan Latka

03:19Okay. Interesting. And what is the... What's the model? Mean, is it a SaaS model or pay as you go?

Slater Victoroff

03:24Yeah. So we... We've got actually a couple of different. So we've got sort of a freemium that we make open to developers, which is very important to us. So it's a very, very sort of generous free tier and then sort of volume based pricing like you'd expect from most APIs. And then we also have sort of an enterprise plan and, sorry. We have an enterprise cloud plan and then also an enterprise on prem plan.

Nathan Latka

03:44Okay. Wow. So there's a lot. Which one of these is kind of your main revenue channel? Which one does the best for you?

Slater Victoroff

03:51Yeah. The the second two, the the enterprise cloud and on prem offerings. The nice thing is we use Docker, so the two are both pretty straightforward for us. There's not a huge difficulty in doing on prem solutions.

Nathan Latka

04:01Is the reason you're doing... And and just define on prem so our audience understands.

Slater Victoroff

04:06Yeah. So this is us bringing a physical box onto the client's premises. Or, you know, more and more frequently, it's us figuring out whatever GPUs they've got kicking around in their basement and figuring out if we can get Indico running on that.

Nathan Latka

04:21I picture Slater, like, walking through a blizzard in, like, downtown, like, Cambridge or something or the financial district, like, lugging servers to install in a basement somewhere.

Slater Victoroff

04:30No. I mean, it's it's about right. I mean, the the one thing that I'd make sure to add to your picture is remember that I'm wearing flip flops in blistering. Other than that, you're spot on.

Nathan Latka

04:39Yeah. So, guys, on premise, this is basically... It's just more secure, and a lot of these firms that care about security and speed will kinda require that later. Right?

Slater Victoroff

04:47Yeah. Yeah. That's exactly right. Or what we found is is almost a bigger requirement for a lot of these people is that they've got old contracts back before sort of cloud infrastructure was was a big thing that require them to keep all of their data on premises. So they actually have legal obligations not to allow any of the data to leave

Nathan Latka

04:47Okay.

Slater Victoroff

04:47Their

Nathan Latka

05:06Let's get into some history here real quick. What year did you found the business in?

Founding Story and Year Founded

Slater Victoroff

05:10So we found the business in 2013. Normally, it was sort of a dorm room business. So that's, you know, the the incorporation date of the company, but it was still a while before we started working on it full time.

Total Funding Raised

Nathan Latka

05:21Okay. And what funding to date, how much have you raised?

Slater Victoroff

05:24About $4,500,000.

Nathan Latka

05:27Okay. And did you... Was that all in kinda one round, or did you do a seed round early on?

Seed Round and Bridge Capital

Slater Victoroff

05:30So we sort of did this big seed round when we first started of about $3,000,000, and then more recently, we raised sort of this bridge capital about 1.2 to really help us attack this financial services vertical, and then we'll probably raise again near the end of the year.

Nathan Latka

05:47So a lot of... You're a perfect person to talk to this about. A lot of CEOs, their egos worry them when they think about doing a bridge round for a lower amount than their seed because they they worry the market perception is that they're not not doing well. But, actually, bridge rounds can be very effective for minimizing dilution, right, and and growing valuation in the meantime. Did you how did you manage your own emotions going through

06:07that?

Managing the Bridge Round Emotionally

Slater Victoroff

06:09So it's a pretty good question. I like to think that that's something that I'm relatively good at. I mean, one thing for me is that I don't really come at the CEO position from a business perspective, but I'm very much coming more from the engineering design sort of product side. And, you know, even though I'm sure there are lot of product managers out there that really let their egos get the best of them, And it wasn't

06:29a huge problem for me. You know, I think even even as much as six months to a year before that bridge round happened, we basically were looking around the space and realizing, hey. Look. A lot of the companies out there, really, really good companies, are still having trouble hitting this product market fit. And we really think that sort of we're trying to get us sort of this extra year of space is going to be the time

06:49that we need. And and at the same time, you know, we kind of got to got to clean house, sort of use that as a really good event to get all the investors, all the employees sort of totally aligned in this new direction.

First Year Revenue and 2016 Growth

Nathan Latka

06:59Yep. It make... Makes a lot of sense. What... Do you guys remember what first year revenue was back in 2013?

Slater Victoroff

07:05Oh, 4

07:07figure. You know? So we were pretty much consulting business back then, really just proving out, hey. Is there any desire for this? So first year revenue, I'm sure, was between 5 and $10,000.

Nathan Latka

07:17It's a super low, but, hey. You gotta start somewhere. Right?

Slater Victoroff

07:21Right. No. I mean, we were based out of

Nathan Latka

07:23So so fast forward is now in 2016. What'd you guys grow revenue to?

Slater Victoroff

07:28Yeah. So I won't share the exact number, but I will say we're sort of in this mid progressing into upper six figures revenue. So we're hoping to hit a sort of a million dollar recurring revenue in 2017.

Nathan Latka

07:41Got it. And that's ARR or MRR recurring?

Slater Victoroff

07:44Oh, ARR. I wish we had a million dollar MRR.

Nathan Latka

07:47Hey. So so at the end of twenty yeah. At the end of twenty seventeen at your holiday party, you'll be popping champagne if you hit a million bucks in total revenue 2017.

Slater Victoroff

07:56Hopefully, it's higher, but...

Nathan Latka

07:57Yes. That's great. So I'm gonna... I'm just gonna... This is a total guess. You can confirm or deny. Is it fair to say you're doing somewhere in between, call it, 40 and $60,000 in monthly recurring revenue to date?

Slater Victoroff

08:07Yeah. That sounds about right.

Nathan Latka

08:08Yeah. Very cool. And, I mean, part of the part of the reason I'm I'm trying... In my mind, I'm having trouble thinking about this is you have so many different pricing plans. It's hard to... You can't really categorize you maybe as a SaaS company. Do you think of yourself as a SaaS company?

Slater Victoroff

08:21Yeah. We we do think of ourselves as a SaaS company. I mean, e... Even in the on prem sort of deployment option, what we're basically doing is, you know, everyone using the product still uses it as a SaaS product. They just happen to be hitting instead of a server on our AWS cloud or their AWS cloud, They're hitting one that happens to be, you know, in the basement.

Nathan Latka

08:38And how many customers are you currently working with here in January 2017?

Customer Count and Enterprise Focus

Slater Victoroff

08:42So we're working with about 20 customers overall, but I would say that, you know, sort of the more important metric for us is how many really big financial services companies we're working with, and that's about three. And the... These are all sort of large enterprise plans, really in this use case.

Nathan Latka

08:59My audience obviously would love to hear a story about one of those firms using you, but I imagine those are wrapped up in confidentiality. Are they?

Slater Victoroff

09:07Most of them are. One of them is not, though.

Nathan Latka

09:09Can you tell us that one? How how do they use you? What's the name of the company?

Manulife John Hancock Customer Story

Slater Victoroff

09:12Yeah. Absolutely. So this is, Manulife John Hancock. So Manulife is the overall name, and John Hancock is their, DBA in The US. And at a high level, we started out working with the innovation lab there. It's called LOFT, the lab of forward thinking, which is sort of this small group of 20 or 30 people within Manulife whose job it is to go out and find emerging technologies and figure out if there's a way to kinda apply

09:38them to real business use cases. And what we did with them is we actually... And they're they're really wonderful team. It was actually very, very happy to work with them, and we we put together a really, really strong bond sort of over the... About a year that we've been working together. So their main goal is they wanted to give their investment analysts a better way to read through sort of these large quarterly and annual reports. Right?

10:02You know, you get the 10 q and the 10 k's that come out, and these can be anywhere from dozens to hundreds of pages depending on the company and sort of how rigorous their reporting is. And just reading through that for an investment analyst is extremely time consuming and extremely tiring, especially when, you know, searching through the whole thing. They're usually only looking for a few key pieces of information.

Nathan Latka

10:20Like what?

Slater Victoroff

10:21So the the numbers... So it'll be things like, oh, they missed earnings. There was some change in leadership. Right? So of the... You know, let's say you got 200 page annual reports. Of those 200 page reports, you know, 80 to 90% of the report is going to be nearly identical. Like Like legalese, but more like, you know, here's our earnings section and it follows the same format. But the interesting thing that we found, right, is that

10:47even though each analyst only cares about maybe five to 10% about what's in that report, that five to 10 is different for each analyst. Right? So if I'm super fundamentally based, right, I might only care about changes in leadership. I'm a very quantitative investor, then I might care very much about earnings, but I don't care so much about the leadership. You know, if I'm a different sort of macro view analyst, I might really care about any,

11:12sort of overseas expansion that this company is doing. So it really varies quite a lot analyst by analyst, and that's actually where we found our our big niche is that right now for most text analytics companies, right, if I say each one of our users wants to have sort of a different classification algorithm that's going to go and sift through these documents and surface what's relevant to them. You know, they say, well, you know, there's no

11:35way we can do that because we can't make a custom model for each user. Really cool thing about transfer learning is that we can actually... You know, if a user gives us 10 or 20 examples, then we've got a totally performing classification algorithm that's personalized to them, that doesn't, you know, kill the servers because we've got another deep learning algorithm deployed that lets them sort of analyze these reports just the way that they want.

Nathan Latka

11:58So the installation happens at John Hancock. Again, the Indico installation's complete. They do the first four or five manually so you can read their patterns, and then you kind of try and codify that. So moving forward, you just give them what they want.

Slater Victoroff

11:58Well,

12:11sort of. The one the one delta I would say is that we're actually not involved in the process. You know, we were in the first couple of months sort of getting them up and running, but the really cool thing is that, so the powerful thing about transfer learning is it's... There's no rules. There's no hard coding. Right? What we give them is an engine that after you give us four or five or, you know, 10 or

12:3020 examples in that range, the algorithm is just good to go. And it'll continuously learn, and we sell sort of all of that type work, right, all of that functionality they get in a really easy set of APIs.

Nathan Latka

12:42Hey, Slater. I have a question for you. This is kinda more emotional and big picture.

Slater Victoroff

12:42Oh, great.

Nathan Latka

12:42A lot of people believe the election... You know, there are echo chambers that Facebook created. Right? Because their learning engine is so smart. They they know what content to show me in my newsfeed that I'm gonna engage with and that I like. But what happened is that created echo chambers, which some people think are good or bad, but generally,

13:01maybe there's less empathy in the world because of it. Right? You could argue that. Do you worry that if your system gets too smart, the company is supplying the information. We'll understand how to kinda game the system and hide important things, and your people are only reading the stuff that your algorithm tells them to read. Does that worry you ever?

Echo Chambers and AI Ethics

Slater Victoroff

13:20So that's a really excellent question, and it does absolutely bring me. I think the the interesting thing that I'll say on the on the first part about the echo chambers is that it's absolutely true. But as far as whether people think it's a good or a bad thing, you know, Facebook's algorithm is not designed to create echo chambers. It has echo chambers because we've told it that that's what we want. Right? Kind of for better or

13:41worse, it's

Nathan Latka

13:41That makes it more dangerous.

Slater Victoroff

13:41Right. Which makes it far more dangerous, which means that unless you very intentionally build a product and a system that avoids that and is geared towards presenting the widest possible context, then an echo chamber is going to be the end result. So, you know, part of that is saying, you know, don't don't shoot the messenger. Right? Facebook

Nathan Latka

14:02Slater, you cut out real quick. So while you're reconnecting, I'll just articulate.

Slater Victoroff

14:05Right. Our goal was very much to provide the greatest amount of context possible. Right? So we're making tools that... You know, right now, there are these 100 page reports, but we're in the process of building out sort of this front end that comes with the data packaged in. And the goal there is instead of only allowing you to read through one or two or, you know, maybe 10 articles on a on a given company, we can

14:26actually give you this high sort of holistic level overview of thousands of different sources, right, that come from different publications, right, that ideally spread not just the political spectrum, but also the spectrum of, you know, people that are pro tech and anti tech and, you know, ideally, just as many different viewpoints.

Nathan Latka

14:43Yeah. It's fascinating getting your viewpoint on that. And, guys, you know, listening, I'd love your perspective on this. This is one of my concerns about AI and and just intelligence in general is that it's gonna create, like, echo chambers. Once you program it or once it learns from your patterns and it assumes you want those patterns to continue over time, it helps you get super specific. And does that tunnel vision make you miss stuff? I'd love

15:05your all's perspective on that. Slater, it sounds like you're already thinking about that, so that's great. Real quick, we're running out of time, so just last few questions here. Has it... Have any customers left you that started paying you, say, a year or two ago or whatever?

Customer Churn

Slater Victoroff

15:17So none within the very sort of crucial areas. I mean, I think there's a there's a couple of areas definitely sort of in the freemium or sort of our lower lower tier customers that weren't paying as much that... You know? So so an example is when we started out, we started doing a decent amount of marketing, and we always knew it was kind of a temporary vertical for us for a lot of reasons. And so as

15:37we sort of moved on, you know, a lot of those customers... Yeah. Sort of I should say a lot. One of those customers left.

Nathan Latka

15:43Okay.

Slater Victoroff

15:44Right? But it was very much we were moving away from the vertical, and they were shifting their product, and it was something that we kind of expected was going to happen.

Nathan Latka

15:52How much per month are you currently spending on marketing?

Marketing Spend and Team Composition

Slater Victoroff

15:55Zero.

Nathan Latka

15:55Okay. So no marketing spend. So most of the money you raise is what? Engineer salaries?

Slater Victoroff

16:00Yeah. Yeah. You know, sort of for better or worse, one of the requisites to to play in this space is you have to have an extremely robust and functional back end. So Yeah. We're still very engineering focused.

Nathan Latka

16:11And what's the team size?

Team Size and Location

Slater Victoroff

16:13We're about 10 people right now.

Nathan Latka

16:14All in Boston?

Slater Victoroff

16:16All in Boston.

Nathan Latka

16:17Very cool.

Slater Victoroff

16:18So we've got one consultant in Malaysia that used to be in Boston, but unfortunately, we couldn't get her visa through.

Nathan Latka

16:23Got it. Yeah. Man, it's such a challenge. Guys, I get asked all the time. Nathan, you host all these interviews, hundreds of them per month.

16:31How do

16:31you do them efficiently? And, guys, the answer is simple. People always agree to my calendar, back to back meetings. I batch my interviews to stay very efficient. And the way that I do it is I use a tool called Acuity Scheduling at nathanlatka.com/schedule. And the reason I use them is very simple. They keep my no show rate very low because they send out reminders about when the interview or the meeting is coming up. And, also, they

16:55make it very easy to schedule time. Right? I don't have to go back and forth via email 10,000 times with people I'm trying to meet with. K. At nathanlatka.com forward slash schedule. Helps me so much. And by the way, look, I, like, have so many meetings. I'm the best at meetings. Okay? I do them back to back very, very efficient. You guys know me. Many people say I'm the most efficient they've ever seen. Okay. So I use the tool. It's so

17:19efficient. And by the way, I got Gavin. I said, he's the CEO. I said, want a great deal for my people. He said, Nathan, most people get a fourteen day trial. Isn't that great? I said, no. He's given us a forty five day free trial at nathanlatka.com/schedule. That's not gonna stay up forever, so go get it now. Nathanlatka.com/schedule. Alright. Let's jump into the famous five here. Number one, what's your favorite business book?

Famous Five

Slater Victoroff

17:46I don't have one. I'm sorry.

Nathan Latka

17:47That's okay. No. Don't make one up. Number two, is there a CEO you're following or studying right now?

Slater Victoroff

17:52Not really, actually, weirdly enough.

Nathan Latka

17:55No problem number three. Is there a favorite online tool you have that you use every day like, you know, TopTal?

Slater Victoroff

18:00Stack Overflow.

Nathan Latka

18:02I knew you were gonna say that. Alright. That's good. Number four. Yes or no? Do you get eight hours of sleep every night?

Slater Victoroff

18:08No.

Nathan Latka

18:09How much do get?

18:10Like, four, five, six?

Slater Victoroff

18:12I center around five.

Nathan Latka

18:14Alright. And then what's your situation? Married, single, do you have kids?

Slater Victoroff

18:18I've been with my girlfriend now for a little bit over five years.

Nathan Latka

18:21Okay. But no kids?

Slater Victoroff

18:22Technically, No kids.

Nathan Latka

18:24Alright. And how old are you?

Slater Victoroff

18:26I'm 24.

Nathan Latka

18:27Alright. Last questions, Slater. Take us back four years. What do wish your twenty year old self knew?

Advice to Younger Self

Slater Victoroff

18:32I wish my 20 year old self realized just how much he loved programming, and I also realized that he knew what on earth he was getting into starting this company. Because I think when I made it when I was about 20 years old, I was still definitely a little bit worse than I.

Nathan Latka

18:47Top top job. There you have it. He wishes earlier that he realized how much he loves programming. He likes maybe likes it. He was a little bit rosy in the beginning, but his company's having success over 4,500,000 raised for indico.com, helping financial firms analyze documents and transfer information much faster. They're currently serving 20 customers aiming to break a million bucks in revenue here in 2017, doing somewhere around $50,000 in MRR currently very little churn and no

19:13customer acquisition costs. It's all free right now with their team of 10 folks up there in Boston. Slater, thank you for taking us to the top.

Slater Victoroff

19:21Thanks so much, Nathan.

Nathan Latka

19:23If you enjoyed Slater today, go back and listen to Brynn Jones yesterday. He used to be part of the Canadian National Swim Team. Now he's running Grow Sumo, a YC graduate, helping 70 b to b SaaS companies grow their affiliate programs. So far, they've put... They've helped companies drive over a $100 in new monthly recurring revenue via their affiliate programs. Top Drive, I love giving away free money. I feel like, oh, we're giving away cars, and

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20:12money. Hostgator.com/nathan. Again, that's hostgator.com/nathan. Okay, top tribe. I'll see you bright and early tomorrow morning. And don't forget, before you listen to any other episodes, subscribe on iTunes right now for your chance to win a $100 every Monday.