{"id":6700,"date":"2016-05-16T06:00:42","date_gmt":"2016-05-16T13:00:42","guid":{"rendered":"http:\/\/editor.thinkapps.com\/blog\/?p=6700"},"modified":"2016-05-16T11:17:51","modified_gmt":"2016-05-16T18:17:51","slug":"machine-intelligence-preteckt-interview","status":"publish","type":"post","link":"https:\/\/thinkapps.com\/blog\/development\/machine-intelligence-preteckt-interview\/","title":{"rendered":"Preteckt Is Disrupting Vehicle Maintenance via Machine Learning [Interview]"},"content":{"rendered":"

This is part of a series on machine intelligence companies<\/a><\/span>. We’ve interviewed\u00a0Beagle<\/a><\/span>,\u00a0Mariana<\/a><\/span>, and\u00a0Beyond Verbal<\/a><\/span>.\u00a0Now we’re turning our attention to\u00a0Preteckt<\/a><\/span>, which is applying machine learning to maintaining trucks and other heavy-duty vehicles.<\/em><\/p>\n

Few things are more frustrating than a vehicle breakdown. They\u2019re unexpected, impede our ability to go about our lives, and can end up costing more than most of us would like to pay. <\/span><\/p>\n

And that\u2019s when you only have to worry about one vehicle. Now imagine running a business whose success depends on your ability to keep a whole fleet of them on the road as much as possible. <\/span><\/p>\n

I\u2019m ripping out my hair just thinking about the stress that kind of position would bring on.<\/span><\/p>\n

\"Machine<\/a><\/p>\n

Image credit<\/a><\/em><\/p>\n

Preteckt<\/a> is made to help those people keep what\u2019s left of their hair. It gathers vehicle data, predicts when one\u00a0will be due for maintenance, and passes that info on to businesses. <\/span><\/p>\n

The idea is that this service will allow trucking and other heavy-duty vehicle companies to keep their vehicles in good working condition so they don\u2019t lose time and money due to\u00a0a breakdown. <\/span><\/p>\n

We recently talked to the company\u2019s chief operating officer, Sasha Kucharczyk<\/a>, about how Preteckt is using machine learning to realize its goal of minimizing breakdowns for its business customers.<\/strong><\/p>\n

[Editor\u2019s note: The interview questions and responses below have been edited for clarity and length.]<\/em><\/p>\n

What’s your role at Preteckt\u00a0and what\u00a0does that entail?<\/h2>\n

As\u00a0a co-founder and COO, there is no day-to-day job for me.<\/span><\/p>\n

Of the three co-founders, the CTO really focuses on all the tech work, obviously, and the CEO focuses on all the front-end business work. <\/span><\/p>\n

As COO, I cover all the back-end business work, so a lot of the marketing strategy, finance operations, etc. The type of work that might involve Excel is usually the stuff that I end up doing.<\/span><\/p>\n

\"Machine<\/a><\/p>\n

How did you end up joining the founding team?<\/h2>\n

I went through a transition while working on my MBA. <\/span>When I started, I thought I\u2019d be some corporate jock. But then I realized that corporate life wasn\u2019t for me. <\/span><\/p>\n

In startups, everything\u2019s much more unstructured; you can be a lot more brave in your actions without massive pushback from the corporate hierarchy. So in the second year of my MBA, I started looking into startup life.<\/span><\/p>\n

After graduating I transitioned into the biz-dev world, focusing on sales and marketing for an ag-tech startup. During that time, I was talking to someone at a conference who had the initial idea for what would become Preteckt. <\/span><\/p>\n

We hit it off and decided to turn this idea into a reality. We ended up going full-time about a year ago.<\/span><\/p>\n

What’s the most challenging aspect\u00a0of your role at Preteckt?<\/h2>\n

The problem with having co-founders is that you become friends with them, and it can be hard to be critical of and push friends.<\/p>\n

You have to be on each other\u2019s backs but also assist each other where it\u2019s needed. It can be hard to find the balance between business partner and friend. <\/span><\/p>\n

We also moved the company to another city where none of us really knew anyone else. We had to stay business partners. That actually has the opportunity to really hurt friendships. <\/span><\/p>\n

It\u2019s a fine balancing act that can be very difficult to manage, yet is\u00a0very important.<\/span><\/p>\n

\"Machine<\/a><\/p>\n

What was the inspiration behind Preteckt? What made you focus on this space?<\/h2>\n

The initial idea was that getting maintenance for your personal car was a horrible experience. Very commonly you bring your vehicle in at the beginning of the day\u00a0only to hear, \u201cGreat we\u2019ll phone you at noon saying what we think needs to be done.\u201d <\/span><\/p>\n

They call you at noon, tell you what they think it is, and say they have to order parts. Then a week later you finally get your vehicle back, along with a bunch of unknown charges. <\/span><\/p>\n

The dealerships aren\u2019t trying to make life difficult \u2014 they\u2019re doing what they can with what they have \u2014 but on the driver side, there are a lot of unknowns.<\/span><\/p>\n

We ran into some difficulties, however, in customer discovery. Everyone who owned a car did not like the experience of a breakdown. But the emotional pain that they had related to it varied a lot. <\/span><\/p>\n

So we went from B2C to B2B and started talking to small vehicle fleets. We\u00a0received\u00a0a bit more interest because they cared about the financial cost and tracking it and trying to minimize it. <\/span><\/p>\n

The issue, though, was that when a taxicab breaks down on the road, it might not be the most expensive incident. It might cost a few hundred dollars, but it might not happen that often. <\/span><\/p>\n

So someone suggested looking at trucking fleets. If you look at trucks, if it breaks down in the middle of the desert somewhere, the company could be out thousands of dollars. We ended up focusing on that and have been iterating on that space ever since.<\/span><\/p>\n

\"Machine<\/a><\/p>\n

How does Preteckt help drivers or trucking companies?<\/h2>\n

Our main premise is that if you know something\u2019s going to break down ahead of time and know when, you can factor\u00a0that into your operation schedules and get maintenance ahead of time. <\/span><\/p>\n

So they can get the truck in a week before something\u2019s supposed to happen, get the necessary repairs done, and get the truck back on the road without any downtime or associated\u00a0costs. <\/span><\/p>\n

Combine that with regularly-scheduled maintenance, and you can kill two birds with one stone.<\/span><\/p>\n

How have big rig companies responded to Preteckt? Are they excited or cautious?<\/h2>\n

We are working with five fleets right now that have between 200 and 800 trucks each. <\/span><\/p>\n

We have another pipeline of about 15,000 to 30,000 trucks interested in us and considering engaging with us. But we haven\u2019t moved forward yet because we\u2019re still in the validation stage with the technology and working on new features, so we can get to the point where it\u2019s scalable.<\/span><\/p>\n

When you go from a vision that they think is cool to the early stages of what that will look like with the product, it requires quite a lot of innovation to figure out what things matter in the short term. <\/span><\/p>\n

The question becomes what are the biggest pain points that we can work on solving now to show them and get their interest.<\/span><\/p>\n

\"Machine<\/p>\n

What can we expect from Preteckt in the future?<\/h2>\n

If I\u00a0wanted to be extremely grandiose, I would say\u00a0to make vehicle breakdowns a thing of the past. <\/span><\/p>\n

A more\u00a0realistic vision for the next five years is staying in the heavy-duty vehicle space. We\u2019re moving to buses and vocational trucks (garbage trucks, mining trucks, etc.)\u00a0because they all use the same communication standard, so they\u2019re much easier to develop on. <\/span><\/p>\n

Once we have that done, we can start thinking about going to other types of vehicles or industries.<\/span><\/p>\n

What’s the most exciting trend in machine learning from Preteckt’s perspective?<\/h2>\n

One of the exciting trends we\u2019re looking at is autonomous vehicles.<\/span><\/p>\n

One of the reasons we\u2019re really excited about that is, to make an autonomous vehicle work, you remove the driver from the vehicle yet you still have to know the health and the current state of the vehicle for maintenance purposes. <\/span><\/p>\n

For those vehicles to take off, a system similar to what we\u2019re working on today is going to be needed, so these vehicles don\u2019t break down in the middle of the road all the time.<\/span><\/p>\n

What advances in machine learning have benefitted Preteckt the most?<\/h2>\n

Here’s something that’s not a super recent development but is\u00a0an evolving trend:\u00a0data costs for pure data plans keep going down, which makes gathering lots and lots of data more feasible. <\/span><\/p>\n

Knowing that you can be collecting a lot more data at much cheaper prices is rather exciting. <\/span><\/p>\n

Outside of that, I think the fact that a lot of cloud computing servers (AWS, Digital Ocean, etc.)\u00a0are\u00a0becoming mainstream, which means your processing power doesn\u2019t need to be local. There are scalable solutions out there for something that used to be extremely costly and extremely time-intensive to build. <\/span><\/p>\n

I\u2019m assuming in the past you had these big operation problems in terms of having to figure out what you need and how you can build it. Now you can spin out new servers and scale on-demand, which gets rid of that infrastructure cost associated with data work.<\/span><\/p>\n

Are there any limitations on machine learning Preteckt would like to see removed?<\/h2>\n

Right now we\u2019re building our own data set to get our own predictions. We\u2019re doing some tests with OEMs to figure out if the data set we\u2019re collecting is unique and if so, how. <\/span><\/p>\n

If five years of vehicle data on everything happening on a truck\u2019s computers magically appeared in front of us, that would essentially be a godsend. If we had that, it would be like \u201cOh my god, I just hit the holy grail of data.”<\/span><\/p>\n

Does Preteckt consider itself a machine learning company?<\/h2>\n

We actually do. We consider ourselves a machine learning or data science company first, and everything else second. <\/span><\/p>\n

One of our core assets and core areas we\u2019re building is our data science team. They\u2019re about half the company right now, and they\u2019ll probably stay\u00a0that way for the next year. <\/span><\/p>\n

That\u2019s a fundamental area where we can provide unique value propositions based on our ability to understand what\u2019s happening on vehicles and predict what will happen in the future.\u00a0<\/span><\/p>\n

To put it another way, we\u2019re a data science company working on heavy-duty vehicles right now.<\/p>\n

Do you have any serious competition in this space?<\/h2>\n

In terms of competition from another startup, I don\u2019t think so. At least not to the same extent that we\u2019re trying to do. <\/span><\/p>\n

In terms of incumbents, though, that is a bit of a difficult question. <\/span>Bits and pieces of what we\u2019re trying to do or what we could technically do are being done elsewhere. But I\u2019ve not seen any companies\u00a0trying to accomplish the same scope that we are and trying to accomplish it in the same way. <\/span><\/p>\n

That could be because what we\u2019re doing right now as a data science company is iterating a lot, building our algorithms, improving their accuracy, and making them better. <\/span><\/p>\n

The first generation will probably be lower accuracy and have room for improvement. And I don\u2019t know if an established brand could release something like that publicly without some backlash.<\/span><\/p>\n

How do the AI and machine learning efforts from Facebook, Google, etc. affect you?<\/h2>\n

One way they have provided\u00a0a huge benefit is that a lot of them have made APIs and things similar to APIs available. <\/span><\/p>\n

I don\u2019t do too much of the in-depth data science or ML work at the company, but I know that the team is using Cassandra<\/a>, which is an Apache tool, and what it does is essentially provide a repository of different functions other people have created to make data science and machine learning with Apache much easier. <\/span><\/p>\n

Google has released a whole repository of stuff for people to access. Microsoft has too. IBM has stuff out there as well. <\/span><\/p>\n

All of that\u00a0makes coding and development much easier. If you know what you\u2019re doing, you can start plugging different things in and seeing what happens instead of having to code your own result.<\/span><\/p>\n

When I was working on my Masters of Engineering, I actually did my own AI work. I remember having to code a lot of the basic machine learning algorithms from the ground up. <\/span><\/p>\n

Now you can just drop-and-use a lot of these things, which lets development happen much faster and just makes life much easier.<\/span><\/p>\n

 <\/p>\n

This post is part of a\u00a0series of\u00a0interviews with\u00a0machine intelligence companies<\/a><\/span><\/em>\u00a0that\u00a0are harnessing the power of machine learning and artificial intelligence in innovative ways. Stay tuned for more!<\/em><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

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