Gatik’s Gautam Narang on the importance of knowing your customer

Gatik is something of an outlier in the autonomous vehicle space. Whereas most companies are either trying to scale robotaxis or commercialize long-haul self-driving with Class 8 trucks, Gatik is more focused on smaller box trucks and middle-mile logistics.

Gatik CEO and co-founder Gautam Narang said there are two main reasons behind this go-to-market strategy. First, an autonomous solution for middle-mile logistics solves specific customer problems. Second, it’s a solution that can be deployed at scale, with no driver behind the wheel today — not in five years.

Gatik is the third company that Narang and his brother, Arjun, founded together. Their first company was in Delhi, India, a medical robotics startup that focused on the rehabilitation of stroke patients using robotic arms. The problem was that labor is cheap in India, and rehab centers and hospitals didn’t see the need for an expensive and unsociable robotic arm when they could hire nurses.

Narang said he and his brother took that lesson to heart and decided not to create technology for technology’s sake, but rather to focus on validating the real customer pain point.

The customers, in Gatik’s case, were grocers and retailers that were struggling to meet the expectations of the end consumer for same-day delivery. Those expectations have already created a shift in the logistics chain that Gatik has been able to grasp onto.

Gatik defines “middle mile” as distances or routes up to 300 miles. The company has around 40 trucks today that move goods in a hub-to-spoke model (rather than a hub-to-hub model) from a distribution center to microdistribution centers and from those centers to multiple retail locations.

Today, Gatik does daily driverless operations with Walmart and Georgia-Pacific in the U.S. and Loblaw in Canada.

We sat down with Narang to learn more about why Gatik doesn’t do free pilots or accept short-term partnerships, the importance of knowing your customer and what investors are looking for in today’s funding environment.

You and your co-founders have strong backgrounds in robotics. What made you want to pursue the box truck approach to self-driving technology?

Matching the customer needs to what was possible from a technology standpoint is how we started the company. When my co-founders and I decided to start Gatik, the criteria we had in mind was firstly starting with a real customer pain point. Back in 2015, 2016, many companies in our space were approaching this problem mainly from a technology angle, building technology for technology’s sake. The thinking was, we’ll figure out the tech and then worry about the use case and business model later. We wanted to do things differently.

Second, we wanted to focus on an application that was more near term, so that’s how we went after this middle-mile or B2B short-haul segment of the supply chain.

The insight we had was the world of supply chain logistics is moving closer to the end consumer. The online grocery segment was growing like crazy, but making that two-hour or three-hour delivery window was becoming more challenging for the grocers and retailers. In an effort to be able to meet that delivery window, they were moving their supply chain to the end consumer by building out microdistribution centers.

All this is to say the routes were getting shorter but more frequent, and the size of the trucks was getting smaller, as well. So that’s how we came up with the category of Class 3 to 6 vehicles going after this mid-mile. And the best part about this mid-mile was we had to operate the trucks back and forth on fixed and repeatable routes. The whole idea was, let’s not try to solve autonomy over a large geofenced area. Rather, let’s focus our efforts on these fixed and repeatable routes, overoptimize the technology for these routes and get to the point of driver-out faster and safer than the competition.

How fixed are these routes? Are your vehicles just driving from point to point?

We’re still operating Level 4 autonomy, but yes, the operational domain is narrower compared to a company that’s going after robotaxi or last-mile delivery. Instead of going after, let’s say, a large geofenced area like the city of San Francisco, we operate our trucks back and forth on these repeatable routes.

Today we are the only autonomous trucking company doing daily commercial deliveries on public roads without anyone on board. When we started out, we were doing shorter routes, like less than 10 miles point to point, so moving goods from one warehouse or distribution center to one retail location. Over the last few years, the technology has matured to a point where we can do pickups from multiple nodes and do deliveries to up to 50 retail locations as well as any combination in between.

To give you an example of a partnership where we’re doing exactly this is with Georgia-Pacific. So in Dallas, Gatik is moving Georgia-Pacific paper products from one of their distribution centers (DCs) to a network of 34 Sam’s Club locations. So on a daily basis, the exact route changes, and we are touching about five to seven stores. As long as the network is manageable and the routes are known and repeatable, we can handle those kinds of networks.

That’s how we think about our business as well. We focus on specific routes where the technology is solvable today, we get to the point of validation where we can take the driver out, and then we do that again across other markets.

Gatik’s Gautam Narang on the importance of knowing your customer by Rebecca Bellan originally published on TechCrunch

Getaround braves chilly public markets with SPAC combination

This column would like to apologize for somehow missing the buildup to Getaround‘s SPAC combination, which was voted on yesterday and began trading this morning. I don’t know how we managed to get so far behind on this particular news item, but we will rectify our tardiness today.


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Getaround allows consumers to rent cars from one another, taking a cut on the transactions. As you can imagine, it’s a marketplace-style company. And it was a venture capital darling, raising hundreds of millions of dollars while private, including a $200 million round in 2019 and another $140 million in 2020.

It had a choppy early-COVID period but has since managed to announce and close a combination with a special purpose acquisition company.

Early direction of Getaround’s stock after the deal closed and it began to trade under the “GETR” ticker symbol has been sharply negative. Indeed, in the first moments of its trading under its own name, Getaround lost around 65% of its value. It now trades for around $3 per share.

Getaround braves chilly public markets with SPAC combination by Alex Wilhelm originally published on TechCrunch

Einride founder on building an underlying business to support future tech goals

Swedish startup Einride was founded in 2016 with a mission to electrify freight transport. Today, that means designing electric trucks and an underlying operating system to help overland shippers make the transition to electric. In the future, it will mean deploying electric autonomous freight — more specifically, Einride’s autonomous pods, which are purpose-built for self-driving and can’t accommodate human drivers.

Einride founder and CEO Robert Falck told TechCrunch a year ago that he felt a moral obligation to create a greener mode of freight transport after spending years building heavy-duty diesel trucks at Volvo GTO Powertrain. On top of that, he saw the need to eventually automate the role of long-haul trucking.

Falck, a serial entrepreneur, decided against the route many autonomous trucking companies have taken — doggedly pursuing self-driving technology, even if it meant putting sensors and software stacks on diesel vehicles. Rather, Falck chose a two-step process to bring Einride to market. The first involves working with OEM partners to build electric trucks and partnering with shippers to deploy them and earn revenue. That revenue then goes back into the business for the second step, which is the development of an autonomous system. By the time Einride is ready to go to market with its autonomous pods, it will ideally already have a range of commercial shipping partners in its pipeline.

Einride’s current shipping clients across Sweden and the U.S. include Oatly, Bridgestone, Maersk and Beyond Meat. The company said it clears close to 20,000 shipments per day.

Over the past few months, Einride has completed a public road pilot of its electric, autonomous pod in Tennessee with GE Appliances, launched its electric trucks in Germany in partnership with home appliance giant Electrolux, announced plans to build a network of freight charging stations in Sweden and Los Angeles, and introduced its second-generation autonomous pod.

We sat down with Falck a year after our initial interview with him to talk about the challenges of reaching autonomy when connectivity on the roads is lacking, why the Big Tech crashes are actually healthy for the industry and what consolidation looks like for autonomous driving.

The following interview, part of an ongoing series with founders who are building transportation companies, has been edited for length and clarity.

Einride founder on building an underlying business to support future tech goals by Rebecca Bellan originally published on TechCrunch

Mobileye IPO warns of potential potholes in the road to autonomous driving

Mobileye, Intel’s automated driving division, filed Friday for what is expected to be the year’s largest IPO, but its success is far from guaranteed.

The Israeli company, acquired by Intel five years ago for $15.3 billion, touts a broad vision: An autonomous future “where congestion is seen only in history books.” But its S-1 filing with the U.S. Securities and Exchange Commission underscores its precarious position in the ever-evolving self-driving vehicle industry.

Founded in 1999, Mobileye has benefited from its first-mover advantage, supplying automakers with computer vision technology to power their advanced driver assistance systems (ADAS). Now, as Mobileye expands its business model, it faces a proliferating number of rivals — from every side — in the wild and woolly world of automated vehicle technology.

The company’s list of competitors in its S-1 extends beyond the “Tier 1” suppliers in its core business to now include robotaxi developers like Argo AI, Aurora, Auto X, Baidu, Cruise, Momenta, Motional, Waymo and Zoox, as well as what it describes as “consumer AV” competitors Apple, Sony and former customer Tesla.

TechCrunch pored through the S-1 to identify the speed bumps and bright spots in its pursuit to dominate autonomous driving.

Vertical integration

In the filing, Mobileye warned that its historical reliance on a handful of automaker partners may jeopardize future revenue. For the first six months of the year, Mobileye reported that 76% of its revenue was derived from eight automakers. But now big spenders such as General Motors and Mercedes-Benz are starting to develop their own autonomous driving systems in-house.

Mobileye IPO warns of potential potholes in the road to autonomous driving by Jaclyn Trop originally published on TechCrunch

Mobileye IPO warns of potential potholes in the road to autonomous driving

Mobileye, Intel’s automated driving division, filed Friday for what is expected to be the year’s largest IPO, but its success is far from guaranteed.

The Israeli company, acquired by Intel five years ago for $15.3 billion, touts a broad vision: An autonomous future “where congestion is seen only in history books.” But its S-1 filing with the U.S. Securities and Exchange Commission underscores its precarious position in the ever-evolving self-driving vehicle industry.

Founded in 1999, Mobileye has benefited from its first-mover advantage, supplying automakers with computer vision technology to power their advanced driver assistance systems (ADAS). Now, as Mobileye expands its business model, it faces a proliferating number of rivals — from every side — in the wild and woolly world of automated vehicle technology.

The company’s list of competitors in its S-1 extends beyond the “Tier 1” suppliers in its core business to now include robotaxi developers like Argo AI, Aurora, Auto X, Baidu, Cruise, Momenta, Motional, Waymo and Zoox, as well as what it describes as “consumer AV” competitors Apple, Sony and former customer Tesla.

TechCrunch pored through the S-1 to identify the speed bumps and bright spots in its pursuit to dominate autonomous driving.

Vertical integration

In the filing, Mobileye warned that its historical reliance on a handful of automaker partners may jeopardize future revenue. For the first six months of the year, Mobileye reported that 76% of its revenue was derived from eight automakers. But now big spenders such as General Motors and Mercedes-Benz are starting to develop their own autonomous driving systems in-house.

Mobileye IPO warns of potential potholes in the road to autonomous driving by Jaclyn Trop originally published on TechCrunch

Treepz founder Onyeka Akumah on how to succeed in transportation tech

In sub-Saharan Africa, only 33% of the urban population has access to public transportation, compared to 75% in Europe and North America, according to UN statistics. That means that most of the continent faces challenges chasing new job opportunities, going to school, accessing healthcare and just having a night on the town.

This lack of access to transportation is in stark contrast to other upward metrics on the African continent, like its growing access to equitable education and healthcare. In fact, Africa has the largest return on education of any continent, with each year of schooling raising earnings by 11% for boys and 14% for girls. The combination of an increasingly educated workforce and still-sucky public transportation means the way people move is ripe for disruption. Treepz, the Nigerian startup that’s scaling its bus-hailing service across the continent, might be one of the main drivers of that disruption.

“We can’t continue to complain about the downturn. I’d say it’s helping us become sturdier.” Treepz CEO Onyeka Akumah

Since Treepz, formerly Plentywaka, was founded in 2019 in Lagos, the startup has expanded west into Ghana and east into Uganda. Co-founder and CEO Onyeka Akumah said those locations will serve as launchpads for further expansion across the sub-Saharan region.

We caught up with Akumah, whom we first interviewed a year ago, to check in on Treepz’s progress and discuss why a conservative funding environment makes for better business, how the African startup scene is maturing, and what it takes to succeed in transportation technology.

The following interview, part of an ongoing series with founders who are building transportation companies, has been edited for length and clarity.

TechCrunch: You last closed a $2.8 million seed round in November. I’m assuming you’re currently raising for your Series A. How are you finding the funding environment amid the economic downturn?

Onyeka Akumah: We are preparing to raise our Series A, and we already have some interest. Some of our current investors want to invest, but they’re waiting for us to go to market. We were about to go to market before the downturn in the economy hit.

The funding environment has changed, certainly, with the downturn. The funding cycle used to be around six months for a round to pull through, and now we’re seeing it take 12 to 18 months to close. You’re seeing investors make a lot more time for due diligence.

Treepz founder Onyeka Akumah on how to succeed in transportation tech by Rebecca Bellan originally published on TechCrunch

Can the algorithms that ride-hailing and delivery startups use be fair?

In June 2020, taking advantage of a Chicago law requiring ride-hailing apps to disclose their prices, researchers from George Washington University published an analysis of algorithms used by ride-sharing startups like Uber and Lyft to set fares. It spotlighted evidence that the algorithms charged riders living in buildings with older, lower-income and less-educated populations more than those who hailed from affluent areas, an effect the researchers pegged on the high popularity of — and thus the high demand for — ride-sharing in richer neighborhoods.

Uber and Lyft rejected the study’s findings, claiming that there were flaws in the methodology. But it was hardly the first study to identify troubling inconsistencies in the apps’ algorithmic decision-making.

Riders aren’t the only ones to be victimized by routing and pricing algorithms. Uber recently faced criticism for implementing “upfront fares” for drivers, which leverages an algorithm to calculate fares in advance using factors that aren’t always in drivers’ favor.

In the delivery space, Amazon’s routing system reportedly encourages drivers to make dangerous on-the-road decisions in pursuit of shorter delivery windows. Meanwhile, apps like DoorDash and Instacart employ algorithms to calculate pay for couriers — algorithms that some delivery people claim have made it harder to predict and figure out their earnings.

As experts like Amos Toh, a senior researcher for Human Rights Watch who studies the effects of AI and algorithms on gig work, note, the more opaque the algorithms, the more regulators and the public have a hard time holding companies accountable.

Can the algorithms that ride-hailing and delivery startups use be fair? by Kyle Wiggers originally published on TechCrunch

Drover AI’s Alex Nesic on using tech to regulate the scooter market

As shared micromobility continues to take over cities, operators have found themselves implementing different forms of scooter “advanced rider assistance systems” or scooter ARAS, that can detect when a rider is doing the thing cities hate most — riding on the sidewalk.

Drover AI, a startup that had the gumption to launch in May 2020, is one of the companies enabling this trend to take off. The startup builds computer vision IoT modules that have been mounted on scooters from the likes of Spin, Voi and Beam. The modules are built with cameras that use machine learning to detect things like sidewalks, bike lanes and pedestrians, which then send that data back to the scooter’s brain in order to send the riders alerts or, in some cases, actually slow them down.

Alex Nesic, one of the founders of Drover AI and its CEO, didn’t always have a burning passion for AI or computer vision. In fact, Nesic spent the better part of the aughts as an actor, appearing in TV shows like “Sleeper Cell” and “CSI” (Miami and New York!). But Nesic enjoyed chemistry in high school and was good at converting tech speak into actionable marketing language, so he jumped at the opportunity to get involved in a high school friend’s venture that dealt with nanotechnology and surface modification chemistry.

After rising up the ladder fairly quickly until he reached the role of VP, Nesic got pulled into the mobility sphere by a company called Immotor, which probably launched about five years too early to be successful. Immotor built a three-wheeled portable scooter with swappable batteries and was connected to an app via Bluetooth.

“The fact that operators and even manufacturers are trying to replicate our approach is very validating.” Alex Nesic, Drover AI CEO

“I would travel with it because the batteries were TSA-compliant, and I would put it in the overhead bin and it was my introduction to moving through cities with micromobility that I could carry with me everywhere,” said Nesic.

This was around the time that Bird started launching shared scooters, so the market wasn’t yet ready for a $1,500 consumer-facing scooter that was being lumped more into the hoverboard category than a useful transportation device.

So Nesic pivoted and founded Clevr Mobility, a shared e-scooter operator that also provided a turnkey solution for cities and other private operators. Nesic said that Clevr was one of the first companies to start the conversation around detecting and geofencing sidewalks, only it was relying on GPS to try to achieve submeter accuracy. It was the failure to actually do so that led Nesic to denounce the inadequacies of GPS and go on to found Drover AI, which meets the demand for precise location awareness using computer vision instead.

We sat down with Nesic to discuss the possibilities of integrating computer vision tech into privately owned scooters, what it means when a larger company steals your idea and why tech pedigrees are overrated when it comes to running a startup.

Editor’s note: The following interview, part of an ongoing series with founders who are building transportation companies, has been edited for length and clarity.

TechCrunch: You closed a $5.4 million Series A in July, and at the time you told me the money would go toward your next-gen product but also toward exploring other integrations farther up the supply chain with vehicle manufacturers.

Alex Nesic: The end game for me is also to try to help inform the regulatory environment because it’s not reasonable to expect there to be two different sets of rules for the shared operators and private scooter owners. Operators are constrained and have all these hoops to jump through, but then anybody can buy something on Amazon that doesn’t offer any similar safety features.

Drover AI’s Alex Nesic on using tech to regulate the scooter market by Rebecca Bellan originally published on TechCrunch