Transcript:

Luke Renner: As most of you may recall, we’re going to be talking about industrial autonomy. I’ll be giving you an overview of the role autonomous technology is playing in the world across a variety of industries right now.

So following two decades of research, development, and beta testing, autonomous industrial vehicles have grown beyond their startup phase, and have risen to become, really, an industry necessity at dizzying speeds.

In recent years, autonomous vehicle innovators have really proven the efficacy of the complex sensor technology and AI algorithms necessary to run AV. 

Today, Autonomous Vehicle Manufacturers are focused on producing more specialized, refined vehicles — and ramping up production to meet demand.

The bottom line is really, this technology is everywhere. It represents a significant opportunity for not only investors but for businesses across entire sectors looking to streamline their operations, shore up supply and labor shortages, and get work done.

Okay. So, for this webinar, we’re going to really go deep here. We have a ton of content to cover, plus we’ll have time for Q&A at the end like I mentioned. Nonetheless, if you have any questions, you can drop them into the Q&A widget, which my colleagues will be monitoring and we’ll get to them at the end.

The most important thing that I can share with you on this slide is that there is some exciting bonus content at the end. We are trying to create a little incentive there to get you all to stay for the full presentation.

Okay. Last little bit of housekeeping before we dive in. Since I did see a lot of new registrants, I just want to ensure that you know a little bit about our company, Cyngn.

So Cyngn is a publicly-traded industrial autonomous vehicle company. We deliver safe and sure-fire self-driving vehicle solutions to logistics, manufacturing and heavy machinery organizations today — we are going to have a broader discussion today about autonomy across multiple industries but these are the main industries that we really play in.

Moreover, we have a number of strategic partnerships across these sectors that enable us to deploy our self-driving technology to multiple vehicle form factors.

The vehicle you see there, the Columba Stockchaser, is our flagship product. It represents years of R&D and is now being scaled and commercialized in multiple warehouses across the United States.

So we’re going to explore how industries are employing industrial autonomy. But before we do that, I wanted to set the stakes a little bit by showing you this chart, which illuminates the dramatic changes in spending that have come to this space. 

Taking Supply Chain as an example, MHI Deloitte’s 2021 Industry Report noted that companies have shifted their expenditures over the last decade in favor of scalable digital technologies. Here are the top 4 categories of expenditures for 2021.

So, obviously, we have Robotics and Automation at the top but really, all of these things are happening together. There is a race, essentially, to digitally transform not just the digital world but the real world as well. It’s this old, “software eats the world” idea. And it’s robotics and autonomy that’s enabling these transformations out in the real world.

We can also see these trends continue. So, basically, the story I’m trying to tell here is one that’s happening in almost every industry. Decision-makers will continue to make technology investments to ensure that their businesses can run smoothly — and really, this is happening everywhere.

The basic premise of this presentation is that this shift is seismic, it’s happening quickly. In fact, in a moment we are going to go through all the ways that autonomy is shifting the way businesses operate. Before we do that, though, I just wanted to pause and talk about some of the root causes of this shift.

As you see there, there’s two main drivers. The first is labor shortages and the second is the ecommerce boom.

The most recent report from the U.S. Bureau of Labor Statistics showed that job openings had risen to 10.9 million, which is a near-record high. Based on other projections, the U.S. workforce will continue to shrink even more in the next decade as more workers get to retirement age. 

In fact, we’ve been in discussions with folks who have told us that they would hire 500 people right away if they could. 

On the e-commerce side, sales have increased 50% since 2019. This, of course, has driven the urgency of manufacturers and logistics providers to streamline their operations and ship more goods. And, of course, as demand increases, that ripples across almost every other sector.

Today, approximately 12% of US manufacturers have already integrated autonomous vehicles into their workflows. The majority of these early adopters attributed cost savings as their number one reason for adopting autonomy. 

Ironically, those who haven’t yet embraced autonomy cite cost as the main barrier to adoption. We’re going to talk about costs a little later in this presentation but the reality is that failure to adopt at this critical juncture will make organizations less competitive, less scalable, less profitable, and really, underprepared for the ongoing labor shortages and market shifts that are happening right now.

So, one of the persistent myths that we encounter at Cyngn is that this technology is still in its infancy. The truth is, the power and efficiency gains of autonomous vehicles are being brought to bear across almost every sector of the economy. In short, if a business is manufacturing something, making anything out there in the real world, they are likely using automation.

So in a sort of flash moment, I just want to fly through all of these industries and give you a sense of the scope of this technology. My goal is to blast through all of these in just a couple of minutes.

Feel free to time me if you want. Okay. Let’s do this.

Luke Renner: We’ll start with agriculture. So, in agriculture, it’s estimated that 15% of farmers are using IoT and self-driving tech on about 250,000 farms — and this is great news because the industry estimates that IoT and self-driving technology may increase productivity by up to 70% by 2050. 

It’s also estimated that we’ll have to increase our output by 60% in that same time to feed all of the new mouths on the planet. So, by 2050 we can really think of autonomous agriculture as more or less being able to completely handle the increased demands on our food supply.

So for aerospace – the aerospace industry is currently using autonomous mobile robots for a wide variety of manufacturing uses, such as unloading trailers, warehouse transportation, tugger and trolley replacement, and pick-and-place.

Construction. In addition to AVs for material transport, the use of autonomous bulldozers and excavators continues to grow. The global construction robotics market is expected to reach $7.9 billion by 2027, according to Allied Research.

Consumer goods. In addition to warehouse and transportation robots, retailers are ramping up efforts for autonomous delivery vehicles, and are currently utilizing autonomous cleaning and security robots at grocery stores and other retail outlets.

In the chemical industry, safety is obviously a major concern which is why they have been adopters, early-adopter of robotics and sensor technology. AGVs are used to transport raw and finished materials, and to inspect hazardous or hard-to-reach areas, resulting in a safer, more productive operation.

Dairy. The dairy industry has been relying on a multitude of sensor technologies to monitor herd conditions as well as product. With labor accounting for more than 20% of production costs, the industry is now employing autonomous vehicles to roam pastures and monitor herd health and soil conditions, as well as autonomous grass harvesters and feeders.

In defense, we’ve been hearing a lot about drones, but the defense industry uses autonomous vehicles for hazardous environments and unmanned scout missions, with both on and off-road capabilities. Unmanned Ground Vehicles (UGVs), also known as “Bots on the Ground”, are really poised to not only impact but revolutionize land operations.

Logistics and Supply chain is really a big place that Cyngn plays and we do a lot of warehouse and 3PL transportation. Warehouse transport aside, the last-mile phase of delivery has historically been challenging. Retailers are looking to AVs to surmount this and other rifts in supply chains. With the use of robust 5G networks, natural language processing, sensor technology, and AI, AVs can bring reliability, speed and efficiency to last-mile delivery.

The Mining industry, another area that Cyngn plays, is an early adopter of autonomous dump trucks, drills, and vehicles to transport ore. The autonomous mining equipment industry is expected to grow from $2.28 billion in 2020 to $3.44 billion in 2025 at a compound annual growth rate of 5%.

Meat processing, kind of a couple to the dairy industry. The meat industry is switching over from conventional forklifts to autonomous ones, which load AGVs that transport product across the plant to areas such as packaging, refrigeration, and loading docks. Considering the perishability of meat products, the efficiency that autonomy provides is a key consideration. In addition to warehouse transport applications, the meat industry is using IoT sensors to monitor temperature during transport.

Metals. In sectors such as the aluminum industry, Hot Metal Carriers (HMCs), autonomously handle and transport tons of molten metal from the smelter to the casting shed, where it is then converted to block products. Smaller AVs then transport block products to other plant areas.

A lot has been happening in the Oil & Gas industry. They are currently utilizing autonomous drones, autonomous snakes, above-ground AVs, and underwater autonomous vehicles for leak detection, pipe inspection, and security purposes. According to a recent World Economic Forum report, robotic land and underwater vehicles and drones are expected to be the highest adopted technologies in the oil and gas industry in the next 5 years.

Pharmaceuticals. Pharma is highly automated, from employing robots to fill and pack with high accuracy and efficiency, to using AVs to transport goods along manufacturing routes. Pharmaceutical companies have also begun using autonomous vehicles for product delivery.

Search and Rescue — a lot of fires happening in California right now. According to a report by Market Research Future, the Search and Rescue Robot market is projected to grow at a compound annual growth rate of 18.2% by 2027. Autonomous vehicles can traverse hazardous conditions, access hard-to-reach places, and send camera and sensor data to communicate findings with rescue workers.

We already have it in snow removal. Driverless snow plows are already in use in countries such as Sweden and Canada. Minnesota is currently testing similar vehicles with advanced lane edge tracking which enables this kind of work in low-visibility and high-wind scenarios.

When it’s not snowing the streets are still getting dirty. Street Cleaning, a $1.9 Billion industry in the US, has begun development of fully autonomous, electric street sweeping robots, saving labor costs and reducing dependence on fossil fuels.

ransportation. Driverless cars, trains, buses and shuttles, are in various stages of use and development. According to a report from Fortune Business Insights, the worldwide self-driving car market was estimated at $1.45 billion in 2020, and is forecasted to reach $11.03 billion by 2028.

Luke Renner: So those are the main industries that I wanted to talk about. So, now that we’ve gotten through that grand tour, Let’s talk about some of the benefits.

So the first we have there is labor shortages. 50% of leaders across manufacturing, transportation, and supply chain cite employee retention as their single biggest challenge.

And this makes sense, right? When you think about how it can take 30-60 days to fill a position — sometimes longer — plus additional time for training and onboarding. It’s a big challenge. In fact, it’s estimated that by 2030, unfilled manufacturing jobs could cost the US economy more than $1 trillion.

Autonomous vehicles address this issue head-on. We estimate that AVs could free up as much as 50% of a skilled worker’s time enabling them to be reallocated to higher-value tasks.

Human error and boredom. A study by Vanson Bourne found that a whopping 23% of unplanned downtime is caused by human error alone. Error and tedium go hand in hand. Boredom leads to safety issues, lower morale, and employee churn. Autonomous vehicles take up the boring tasks, enabling employees to move onto more engaging tasks and responsibilities.

Increased efficiency and productivity. A recent report from Sapio Research revealed two key results after implementing automation: 1. a 48% improvement in productivity, and 2. a 42% decrease in operating costs.

Autonomous vehicles make your organization more agile. So AVs offer the ability to move goods with greater flexibility. Previously, manufacturers depended on transport methods such as fixed conveyance or drive-by-wire systems. The problem with these approaches is that they are semi-permanent and really inflexible.

By contrast, it’s very easy to reroute an autonomous vehicle. You can essentially bring autonomy to any workflow, no matter how often you want to change it. This agility can be particularly important these days as supply chain disruptions may require you to organize your teams or your stations differently to respond to changes on the ground.

Autonomous vehicles make it easier for companies to scale — particularly without having to invest in additional labor resources. Moreover, autonomous vehicles can be rented as opposed to purchased, which means that as demand fluctuates, your fleet can grow or shrink. So you can imagine seasonal fluctuations or swarming up an autonomous fleet when you embark on a new contract or construction project.

Safety considerations are a big one here. According to the US Bureau of Labor Statistics, 614 workers lost their lives to forklift-related incidents between the years 2011 and 2017. Moreover, there were more than 7,000 injuries each year.

And obviously, the deaths and the injuries are the most terrible part about these incidents. But they can also be very expensive for the business. For instance, the average American warehouse experiences 9 accidents per year, each of which cost the business about $42,000. In 2019, the cost of preventable workplace injuries in the US was $171 billion.

In stark contrast, the Material Handling Institute (MHI) reports zero, zero known AGV-related injuries. Completely wiping away the possibility of injury ends up being a huge driver for organizations to shift to autonomous vehicles.

Luke Renner: The final thing I’d like to say about the benefits of autonomy is kind of what we can refer to here as, “bob can keep his job” — which is to say even though we’re positioning autonomous vehicles as a solution to labor shortages, autonomous vehicles are really designed to augment the efforts of your existing workforce.

A recent study in Germany showed that fully bringing autonomous vehicles to manufacturing and logistics will increase employment by 10%, increasing demand for employees with IT and engineering skills. While it is possible that automation may replace a percentage of unskilled laborers, we have discovered that it will contribute to the creation of jobs as well — and also really give existing employees the opportunity to uplevel their skills and take on more responsibility.

So, now that we’ve gone through the benefits of autonomous vehicles, I want to talk about ROI.

We recently deployed our self-driving stockchaser at Global Logistics and Fulfillment. They are a third-party logistics provider, based in Las Vegas. We worked closely with that team and their management to measure the effect of our autonomous vehicles on labor costs and throughput.

The results, if we say so ourselves, were dramatic, and almost immediate. So, here’s what we found as you can see there. We found a 64% reduction in human labor costs when using Cyngn's autonomous stock chaser vs. using a forklift. We also found a 33% increase in efficiency when using Cyngn's autonomous stock chaser as opposed to using an electric pallet jack.

So we’ve talked about the benefits, we’ve talked about the ROI. One of the obstacles we encounter when talking to folks is the idea of replacing a fleet of industrial vehicles with autonomous ones may seem like a really gargantuan endeavor, right,, such a big overhaul that it would kind of shut down the conversation entirely and prevent any further consideration on the matter.

It’s important to note though, especially with Cyngn’s technology, that an existing fleet can be easily retrofitted with AV technology, which obviously saves a lot of costs right?

So, we have a product called DriveMod Kit. It’s a hardware sensor and AV software kit that converts your existing industrial vehicles to autonomous ones. Installation is fast and simple. Training is relatively straightforward.

Overall, it’s really easy to get a DriveMod-integrated vehicle running smoothly. So, you really get to tap into the power of autonomous vehicles without having to completely replace your fleet and all of the costs associated with that.

DriveMod Kit has been deployed on several vehicles but it’s currently commercially available on the Columbia Stockchaser.

Luke Renner: Okay, I mentioned there would be bonus content and here it is. In the next few days, maybe next week, we’re going to be launching our ROI calculator on our website. I wanted to give everyone here a chance to kick the tires on it. I

If you run a facility, the ROI calculator is an excellent way to start to quantify just how much value autonomous vehicles can bring to your organization. It’s very slick. We’re really proud of it. So I invite all of you to check it out by visiting cyngn.com/roi. That’s cyngn.com/roi. You might want to write that down.

So that is the presentation. As you can see, there are tons and tons of ways that autonomous vehicle technology is impacting industry as we know it. If you want to dive even deeper into some of the things we’ve talked about today, I recommend you download our ebook on the same topic. The ebook was the basis for this presentation and you will be able to see a lot of our sources and take an even deeper dive if you are interested.

So, now I want to open it up to your questions. And either Ben or myself will try to answer.

Ben let’s unmute you here.

Ben Landen: Yup, good to go.

Luke Renner: Hi Ben how are you?

Ben Landen: Doing well, enjoying the presentation.

Luke Renner: Great. As I said at the top, Ben is our Vice President of Business Development.

So, how do you see the importance of the robustness of the system, for example perception, in harsh driving scenarios such as low light, poor weather, etc. limiting useability, uptime, etc., etc.?

Ben Landen: Yeah, this is a good question. Luke ran through I think it was 19 different domains or use cases, now those have varied conditions ranging from very controlled conditions. Like you might have a manufacturing plant to a very exposed and not controllable conditions. Like you might have an open pit mine.

So we have a history of starting to develop our technology much like the robotaxi companies did in one of those less constrained, more difficult, more exposed types of environments which is the city streets. We did our development primarily in California which is relatively friendly weather but we also deployed in a seaport in the Philippines, we deployed a shuttle service at a large corporate headquarters in Toronto, which exposed us to snow. So we kind of got our fair share of bad weather.

And that’s where you start to look how you address that with the Stack with ranges from your sensor selection and we tend to go with automotive grade sensors given that we really started and underpinned our development with the robotaxi methodologies. So we’re using very rugged sensors. We’re working with the hardware manufacturers primarily use either off-the-shelf coming ruggedized or to ruggedize them up for the use case when it calls for it.

But that’s really where we lean on our hardware partners being a software company.

But that’s what we’ve done with a technical aspect using sensor fusion, using a lot of these different sensor feature - because low light conditions, Lidar does really well since it’s an active sensor it actually shoots small beams that don’t really care how dark it is whereas a camera is going to do well in other types of conditions.

So that’s how we address technically with sensor fusion and a smart design methodology.

How we address in an even simpler way is that having developed in those difficult conditions, now as we’re stepping in to commercialization and scaling, we’re actually purposefully focusing on the more constrained situations, like we see, the more constrained operational design domains is the jargon, ODD, that we see in warehouses, in manufacturing plants, where the lighting is controlled. You don’t have unexpected ambient lighting conditions, you don’t get exposed to the elements. You're moving raw material around a manufacturing lot.

So that is just a strategic decision that we made to essentially overreach what our commercialization goals are with our development and now deploy down. And obviously thats not the case when we look at application within the mining sphere, and some of those outdoor applications.

But that’s where we fall back onto that technical development that we’ve done outdoors and back to that whole question of, “what are the right sensors?”, “how are we going to use the data from those sensors in a sensor fusion model?”, and “how are we going to ruggedize those sensors with our hardware partners as is needed for the application?"

Luke Renner: So I want to give everyone one last chance to get your questions in, otherwise we’re going to call it a day here.

I really appreciate all of your time, thank you for attending. If you have any questions that come up later feel free to email me, luke@cyngn.com. Or you can email Ben, ben@cyngn.com.

Have a wonderful day, thank you for your time.

Ben Landen: Thanks all.