RoadBotics: The Early Days Of An American Startup That Provides Smart Road Assessments – with Mark DeSantis [Ep#17]

The Traction Stage

We all want our roads in good conditions. Don’t we? But, the definition of a ‘good’ and a ‘bad’ road may vary a lot. This is the challenge that governments and companies run through in the process of road maintenance: assessment subjectivity.

RoadBotics was born to solve this and other problems regarding road inspections. Through the same technology used to make autonomous vehicles to “see” the road, the startup makes computers analyze road conditions.

In this interview, Mark DeSantis, cofounder of RoadBotics tells me about the early days of the startup, since the idea until it started gaining traction.

SHOW NOTES

Let’s understand the problem you’re solving and the solution RoadBotics is offering to solve that problem…

THE PROBLEM

Road inspection has been a staple of road maintenance for a long time.

There are millions and millions of miles of paved road in the world. So, the process of doing that manually around the world is expensive, it’s tedious. But the bigger problem is you’re using humans to look at the surface and make judgments about it. And everybody’s opinion about what is a good road or a bad road is different.

THE SOLUTION

Basically, you download an app into a cell phone, put the cell phone in the windshield of any kind of vehicle, camera pointed forward, turn the app on, records everything it sees. As soon as the cell phone hits a friendly Wi-Fi, all that data goes up to the cloud, and a deep learning platform that isolates the road in the image, then begins assessing the surface of that road pixel by pixel.

And what it’s looking for are about three to four dozen distinct patterns that show up on any kind of asphalt or concrete road—like alligator crack, block crack, edge crack.

So, we’re able to do that by using a standard cell phone, some deep learning and assess that road in a far cheaper, far more efficient and consistent way for roughly about 160 municipalities, counties and states in a dozen countries.

LOOK TO THE ROAD!

The idea happened not exactly in a garage, but inside of Carnegie Mellon University. Right?

Exactly. Carnegie Mellon (CMU) is famous for its AI program. I think most people would argue they’re probably the number one AI program in the entire world. And among the programs they have inside the AI program is the now-famous Robotics Institute.

Within that, they have a lab that focuses on transportation. In fact, the Uber Lab and the Argo Autonomous Vehicle Lab—both of which are based in Pittsburgh—were ultimately spun out of Carnegie Mellon.

That same group came up the notion: “We’re using image processing to move a vehicle around. Couldn’t we use the same data to assess the surface? Because after all, we’re looking at the road.”

So, the idea was born out of the autonomous vehicle lab.

INVESTIGATING THE PROBLEM, TESTING THE SOLUTION

What were the first practical steps you had to do in order to develop the startup?

We did over 100 interviews with people, either in the business of road assessment, road maintenance, who kind of lived that life. We made no mention of our AI platform. We didn’t talk about any solution or anything.

We simply talked about their problems. “How do you assess roads? How do you determine what is a good road and what is a bad road? How do you collect the data?” All those questions allowed us to really get deep into the world of the customer. And then once we collected it—maybe 75-80 interviews—we knew that what we could do addressed that problem.

The second step was to create an MVP. We were fortunate we had already started, because some of the core technology was developed at CMU, but it needed a lot of work to get its commercial grade.

All those questions allowed us to really get deep into the world of the customer. And then once we collected it—maybe 75-80 interviews—we knew that what we could do addressed that problem.

Parallel to our market discovery—the hundred interviews—we developed a basic working version of the product such that when people used it, they could determine of whether or not this thing really added value for them. It’s not so much a way to make money—and we charged for it by the way—but it was more a case of to get elicit a response to see what customers were really looking for.

It [the MVP] had a lower resolution. Let’s just say we couldn’t see as much detail; It didn’t have the user-friendliness that the current version has; It wasn’t able to see all the things that needed to see; It wasn’t exactly presented in the most useful way.

But for the most part, everything that’s in the current product showed up in some version in the MVP.

HOW ARE YOU DISAPPOINTED?

What were the customers’ reactions that told you: “we have evidence that this is going to work, we can accelerate and try to scale it?”

That’s a really good question. People don’t pay enough attention to the type of feedback. Reactions like “Hey, this is great.” or “This is really cool.” weren’t terribly useful.

In fact, what we wanted is them to critique it and tell us where it wasn’t useful. In other words, we typically would get a reaction something to the effect of “Wow, this really saves me time and money, and has reduced the hassle!”

Source: https://www.roadbotics.com/

But, we were not satisfied with that response. We would say “When you say ‘save time’…exactly how? How does this compare to how you did it before? What do you mean by time? What aspect of time is it? The time on the road?”

And we were constantly probing for areas where they were dissatisfied. We’d say, “Look, you’re not going to hurt our feelings here. Right? Don’t worry about hurting our feelings. Where is this disappointing? Because, before we showed this to you, you had an impression of what it could do. We gave it to you, you’ve used it, and you have to be disappointed in some way. How are you disappointed?

THE REASON WE LIKE IT

Did you find any insight in these interviews or showing them the MVP that made you iterate the product?

Definitely. In summary, we had a primary emphasis on “This is a cheaper and easier way to do the work you do now. Just put the cell phone in the windshield, camera pointing forward automatically assessing. Cheaper and Easier.” And it is, substantially.

Source: https://www.roadbotics.com/

But after a number of interviews, users started giving us feedback, they said “That’s not why we like it the most though, that’s not the reason we like it. The reason we like it is you solve the subjectivity-objectivity problem.” That’s something we hadn’t really thought of.

But after a number of interviews, users started giving us feedback, they said “That’s not why we like it the most though, that’s not the reason we like it. The reason we like it is you solve the subjectivity-objectivity problem.”

For example, a city like London uses hundreds of inspectors. If those inspectors disagree on what a good road, a bad road or a so-so road is, the data, all of it, is frankly suspect. Our system solves that problem.

KEEPING THE BALANCE

From the idea until you got traction, what was the biggest challenge in the way?

It’s a balancing act. Every entrepreneur has to balance three things.

You have to raise money—that’s just the nature of the beast, for most tech companies. You can’t necessarily self-fund or grow organically—you have to build a team, and then, you have to build a customer base.

You have to do all three of those things, simultaneously. The biggest challenge for the entrepreneur is to keep them in balance.

Entrepreneurs out there who really don’t want to be bothered raising money or getting customers or, another entrepreneur who really doesn’t have technical skills to build the product, but really is a great salesperson, I would say to them: “Okay. If you’re not going to do that, somebody’s got to do that. And that somebody has to care as much about the company as you do.”

THE MILESTONES

What were the most significant milestones that shaped what RoadBotics is today?

One was nine months or so after we founded the company. I met a team from an incubator called UrbanX—BMW’s incubator in the United States—who is just phenomenal.

They really know the game and they helped me rethink our strategy going forward. They also invested cash and introduced me to BMW, who cares a lot about what we do. So, when you get right partners like that early on, who can invest and give you wise advice, they can really accelerate your growth.

When you get right partners like that early on, who can invest and give you wise advice, they can really accelerate your growth.

A second milestone was when we got to around two dozen customers. It’s one thing to get four or five customers; It’s quite another thing to have two dozen. We had enough data, with that number of customers, that really convinced us that we had something and that we knew what we were doing.

The third milestone was when we got our first couple partners, and they actually sold our services to their customers. When they started to pick up two or three customers, we realized: “Hey, we’ve got something here!”

The partnering strategy—the idea that an engineering firm would sell our product or use it for multiple customers—really encouraged us a lot.

The partnering strategy—the idea that an engineering firm would sell our product or use it for multiple customers—really encouraged us a lot.

MATCHING, INSTEAD OF SELLING

What is the most valuable learning from all RoadBotics’s fundraising experiences you’ve had?

Two things…

One is that fundraising is not a sales effort. It’s a matching problem. Early on in my startups, I used to think I had to convince people to invest in my business. I was wrong. It’s not like selling a product. It’s a matching problem.

[…] fundraising is not a sales effort. It’s a matching problem.

There’s a group of investors out there who are looking for someone at your stage, with your background, with your point of view, who care about the problem you’re solving, and the way you’re solving it. Here’s the problem: there are also hundreds of investors who are not that person. So, your challenge is to sift through all of these potential investors to find those perfect matches.

The other thing is do not underestimate the level of effort it takes to solve the matching problem. People will say: “I’ve done 20 pitches, and nothing’s happened.” I would say to the people out there seeking investment: count on not a couple of dozen presentations. Count on 100 or more, before you find those three or four investors.

As a CEO, I probably spent two-thirds of my time raising money or doing something related to raising money. Fundraising demands your attention, so be prepared to give a substantial amount of your time and be persistent.

Fundraising demands your attention, so be prepared to give a substantial amount of your time and be persistent.

IT’S NOT ABOUT YOU

A piece of advice to startup founders that are listening to us… What would you say them?

For any entrepreneur out there, think first and foremost about solving a problem and building an institution to solve the problem, not about building an ego. And I say that because sometimes it’s hard for entrepreneurs to accept that.

They think of their company as their company. It is not their company, it is something they created. A beautiful magnificent thing, that’s solving an important problem.

But if you find yourself emotionally attached to the status associated with being the founder or the CEO, you’re going to set yourself up for failure.

Your sheer satisfaction should come from giving other people the opportunity to create wealth—investors and employees—giving your employees the opportunity to have a life-changing experience, and the most important personal growth opportunity they may have ever experienced in their lives.

[…] if you find yourself emotionally attached to the status associated with being the founder or the CEO, you’re going to set yourself up for failure.

If you can draw satisfaction from those things, you can create not only great wealth for other people, but great wealth for yourself, and you have a much higher likelihood of being successful.

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MORE ABOUT MARK DESANTIS

Mark F. DeSantis (LinkedIn) – Mark is a serial tech entrepreneur and is currently Managing Partner at MIR Ventures in Palo Alto. Most recently, he was cofounder and CEO RoadBotics, an AI platform for assessing roads and roadways infrastructure. Prior to that, he was cofounder and Executive Chairman of kWantix, a quant hedge fund, cofounder and CEO of kWantera, a GE Ventures-backed energy trading company and CEO of Think Through Learning, a venture-backed online tutoring company and US Managing Director of ANGLE Technology, PLC, a UK-based venture capital firm and consultancy.

MORE ABOUT ROADBOTICS

RoadBotics (LinkedIn, Facebook, Youtube, Instagram, LinkedIn) – RoadBotics is an industry leader in road assessments. At RoadBotics, we provide objective road assessments to over 100 customers across the world and help them fix the right roads at the right time. Our mission is to drive objective infrastructure decisions and help improve critical infrastructure that impacts people’s lives every day.

Founded by Mark F. DeSantis, Dr. Benjamin Schmidt, and Dr. Christoph Mertz, RoadBotics spun out of Carnegie Mellon’s Robotics Institute in 2016. The company has raised $3.9M in venture capital investment to date and has disrupted the subjective and expensive pavement inspection process.

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