Q1 2022 AEye Inc Earnings Call
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Good day and welcome to the AI, Inc. first quarter 2022 results conference call. All participants will be in a listen only mode. Should you need assistance, please signal a conference specialist by pressing star then zero.
After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star then one on a touch tone phone. To withdraw your question, please press star then two. Please note this event is being recorded.
I would now like to turn the conference over to Clyde Monteverde, VP of Investor Relations and Strategic Finance. Please go ahead.
Thanks and welcome everyone to AI's first quarter 2022 Ernie's call. With me today, our Blair LaCourt, our Chief Executive Officer, and Bob Brown, our Chief Financial Officer.
Earlier today, we announced our financial results for the first quarter of 2022.
A copy of our press release can be found on our website at investors.ai.ai.
Before we start, I'd like to remind participants that during this call, management may make forward-looking statements including, without limitations, statements regarding our future performance, growth strategy, and financial outlook. Forward-looking statements are based on our current expectations and assumptions regarding our business, the industry, and other conditions.
These four looking statements are subject to inherent risks, uncertainties, and changes in the circumstances that are difficult or impossible to predict.
Our actual results may differ materially from those contemplated by these board looking states.
We caution you, therefore, against placing undue reliance on any of these forward-looking statements.
You can find more information about the risks, uncertainties, and other factors in our reports, filed from time to time with the Securities and Exchange Commission, including in our quarterly report on Form 10Q for the period ending March 31, 2022.
All information discussed today is as of May 13, 2022, and we do not intend and undertake no obligation to update any forward-looking statements, whether as a result of new information, future developments, or otherwise, except as may be required by law.
In addition, today's discussion will include references to certain non- GAAP financial measures.
These non- GAAP measures are presented for supplemental information purposes only, and should not be considered as a substitute for financial information presented in accordance with.
A reconciliation of these measures to the most directly comparable GAAP measures is available in our press release, and you should refer to our reconciliation of non- GAAP financial measures to the most directly comparable GAAP measures in our earnings release. With that,
As you have seen in our earnings release today, we finished our first quarter solidly, meeting both our financial and operating expectations.
In addition, we remain on track to achieve our full year plan.
While we continue to follow external global events closely and monitor market volatility, our main investor themes and objectives for 2022 remain consistent, and our focus on execution remains paramount.
In our year-end earnings call, we outlined our go-forward strategy and our progress to date building product, partnerships, and infrastructure to meet our key objectives. We also spent time differentiating our unique business model and disruptive technology platform versus peers. In our last call, you also had a chance to hear from several customers in the automotive and industrial markets directly.
They shared with us the value the AI intelligence sensing platform brings to their solution.
We would like to first emphasize the importance of 2022 as we intend to both begin shipping the Forsyte product for industrial markets with our partner, Samina, as well as transferring the B sample of our first joint automotive ADAS product to our partner, Continental.
In today's call, we intend to do a quick review of the market dynamics, the differentiation of our disruptive intelligence fencing platform, and illustrate why we and our partners believe AI's sensor-based operating system is uniquely positioned to enable the evolution of smart vehicles, infrastructure, and S.
We will use the majority of our time today to focus on our execution with an update on the fourth key investment theme, commercialization, industrialization, and capital light manufacturing.
We will touch on both the four-site product line, as well as our joint continental eight-ass product. We believe we will be the only company in our peer group to bring up volume production capabilities with multiple manufacturers. We will be the only company in our peer group to bring up volume production capabilities.
The market headline is, sensors are a highly desired addition to many vehicles, infrastructure, and other assets.
Cameras and radars are interpretive sensors with unique strengths and weaknesses, but have one attribute in common. They collect information and intelligently guess.
Light R is a deterministic sensor which can provide definitive data for many decisions, enabling new value added features that can be standalone like hub-to-hub trucking or highway autopilot for consumer vehicles.
or LiDAR can also complement radar and cameras to increase reliability or accuracy for existing features, such as in slower speed traffic jam.
What is clear is that Lightars commercial performance has continued to increase substantially over the last several weeks.
Concurrently, its manufacturability is maturing. And therefore, size, weight, power, and cost continue to be optimized as lighter as being applied across numerous industries.
Many of us already have a LiDAR sensor in our smartphones, advanced driver assistance systems in our cars, and we experience traffic flow optimization on toll roads and other parts of our infrastructure. We believe LiDAR has a wide range of applications well beyond what most people have imagined. That said,
With many traditional LiDAR systems, data is collected in a fixed and limited manner and then passed along to a perception engine.
This is a one-way flow from the sensor into an application software layer. AI software.
First, we can control hardware components individually using a software-based operating system located on the sensor with two-way communication to change the way the sensor works, depending on different environments.
In addition, the Foresight operating system does not silo itself from other centers.
Customers can create unique systems that can use maps, cameras, radars, and IMUs to trigger the LiDAR so they can be more intelligent and efficient when collecting critical information, as recently demonstrated with Continental's integration of its current ADAS suite, including radar and camera, with our joint LiDAR product.
Finally, and most importantly, this software-defined architecture is natively compatible to manage data over its local sensor network and to be enabled for over-the-air updates.
So we can change the way the hardware performs through software, allowing our customers in the future the ability to upgrade and to add new features and functionality.
While this seems too good to be true, you only have to look to your smartphone to see the path that is already being taken by many durable goods manufacturers and infrastructure providers. In automotive specifically, the acceleration of EVs provides a natural greenfield opportunity to create software definable platforms for cars. The future is now.
One powerful example of this software definability is adaptive placement. The four-site platform enables automotive OEMs to embed the same light-ar sensor in various integrated locations, using AI's proprietary sensing software. This optimizes performance for the vehicle-specific packaging and integration without detracting from design or limiting performance.
AI's operating system provides OEMs with the ability to transform the sensor performance and enhance data capture across various mounting locations and the
This is in contrast to most traditional sensors today, which cannot be optimized for placement, tolerances, and applications, making them suboptimal across a platform with multiple brands and models.
At the end of the day, the ability to change the mounting locations and the height, as well as correct for curvature and transmissivity of external surfaces, allows us to increase platform adoption, optimize feature implementations, and reduce cost and complexity.
This same adaptive placement capability and software definability, conversely, allows AI to customize across markets.
allowing the use of the same hardware on a roof mount at four meters and a negative 40-degree angle on a Class A truck as a grill mount at 65 centimeters and a negative 15-degree angle on a Trendy Sport.
Up until this point, we have been talking about how our adaptive systems can add intelligence into current vehicles, infrastructure, and assets.
So let's take a step back and discuss the future and what differentiates the software divine vehicle from a traditional vehicle today that has intelligence siloed in many subsets.
On the left you see a vehicle with all of its technology and functionality set when you purchase
In many cases, you would need to physically change or alter a component to adjust the hardware functionality of the vehicle. On the right, you see a vehicle with a more streamlined platform reference.
reducing complexity and allowing for the flexibility to control the hardware more efficiently as part of an overall
As we continue to advance cars with software, you will see systems begin to consolidate into software-definable platforms with more connectivity both within and outside the vehicle. With this added connectivity and distributed intelligence within the vehicle, the opportunity to add value and increase revenue from software expands.
The AI operating system model is architected to complement this migration.
Focus not on hardware alone, but on collecting the best data for decision making, adding features to add safety and performance for the consumer and driving profitability for the OEM. For example, in the future, a rain sensor may trigger a rain performance mode, or a camera may trigger a light hour to confirm an object. This distributed intelligence is key for what we consider a software-enabled vehicle.
In a recent report, it was estimated that Tesla today makes 67% of its profits from these types of software-enabled products.
While our products already have the adaptability to be definable across multiple applications using the same hardware, the real power in the future, where cars may be driven for 10 years, may be the ability to continue to adapt over time and update remotely using OTA, an acronym for over-the-air update.
As an example, as new vehicles increase software content, OEMs will be able to update software over the life of the vehicle, similar to how your phone gets updates today. Vehicles will be able to send and receive data, enabling them to continuously increase in value. These updates will allow new features and functionality, translating to improved safety and performance.
As vehicles and infrastructure head towards over-the-air evolution, we believe our software-defined sensor will be a key enabler of these new business models.
In summary, we believe the power of AI's unique sensor platform is that it is intended to be a set of hardware components that can be manufactured, then configured, for any high-value use case in the software.
For instance, OEMs or Tier 1s could use the sensor's operating system to enable ADAS features that can be bundled for a range of consumer vehicles.
The same operating system could be used by system integrators in the ITS, or Intelligent Traffic Systems market, who are able to optimize the sensor for a pedestrian safety at intersections or forecasting traffic flow on toll roads.
Trucking can leverage high-performance, high-reliability sensors designed for first-mile, last-mile, or hub-to-hub applications.
In the high demand rail and aviation markets, each tensor can be optimized for the extreme range and the resolution they require.
So let's talk about execution and our progress around commercialization and scalability. There's no better place to start than our latest product, the Foresight M, which we intend to transfer to volume production later this year.
I would now like to introduce Tom Fallon, Executive Vice President of Strategic Business Development at Samena, our Foresight Manufacturing Partner. Take it away, Tom.
Sanmina is one of the world's leading integrated manufacturing solutions.
Headquartered in Silicon Valley with a global footprint. We have earned a reputation for innovation, reliability, and quality. We're the passion for customers.
It is important to understand that we only win when our partners.
So we are very selective in where and when we invest in new processes and emerging companies.
Each year with our customers, we bring about 3,000 new products to market. So we are approached by a lot of companies.
We proactively choose to partner with the companies where we see a mutual alignment around ideas and process.
We also look for a well-defined market opportunity that is large and rapidly approaching. With AI,
We also found that AI has a compelling vision and business model.
We believe AI's smart, software-definable sensors will be a driving force in the automation of cars, infrastructure, and assets across many industries.
At the core of our relationship with AI, there are three fundamental pillars we have found important to increasing the probability of...
First, AI decided early not to build a factory, but rather invest their time and resources in designing their systems for outsourced manufacturability with an eye toward optimizing efficiency and cost without compromising on industry leading performance and reliability.
Second, AI's innovative approach of aligning component suppliers with their reference system.
Utilizing modular components sourced from proven automotive-grade suppliers not only allows accelerated innovation, but also is a tremendous advantage in helping us to scale and harden our global supply chain.
We believe this approach creates a strategic differentiation from others by optimizing time to market, volume, quality, and cost.
Third, AI has transferred much of the system complexity from hardware to the software layer and its unique sensor-based operating.
We don't usually see companies make that leap until four or five generations of product releases.
This allows one manufacturing line to produce the sensor hardware at scale, and software is used to customize the sensor per market or partner and to enable continuous enhancements in functionality over time.
Most importantly, AI and Sanmina have worked as one team.
From the beginning, we have leveraged these other strengths to develop integrated design, manufacturing, and testing processes that will bring the AI Foresight LiDAR system to the market faster and with greater reliability and performance.
San Mena believes that what we make makes a difference. We are very proud of our purpose.
Thanks, Tom. Earlier this year, we mentioned the convergence of our components across markets and the focus on shared volumes and cost reduction to drive adoption. Tom also referenced our joint efforts to design for manufacturing, reliability, and the power of converged supply chains.
One example of this collaboration we would like to share for the first time publicly is how this effort drove advancements in our MEMS component.
Custom design and built around standard industry processes for manufacturability.
The small dot in the center of the chip on this picture is our micro-mems, significantly smaller, faster, and more adaptable than any we have seen in commercial production.
proving that record breaking performance indeed does come in small packets.
Another concrete example of how AI and Semina are innovating together is our new joint calibration and testing facilities. Located on Semina's San Jose campus is a perfect complement to AI's indoor range and double.
Industrialization and reliability at the core of any successful path to scale and highly regulated admission critical system.
This large, dedicated, state-of-the-art facility not only allows us to do environmental and performance testing, but also to bring customers and integration partners into an immersive and flexible testing environment. This jointly developed facility gives us tremendous flexibility in validating the performance of our Foresight sensors.
Working with Semina and our end user customers, we have developed rigorous testing methodologies that help us fine tune the performance of our sensors and a wide variety of use cases and applications.
You can see in our video our ability to quickly reconfigure the operation to run customer driven tests this week. From small object detection at speed, a rider down motorcycle scenario, intersection pedestrian safety, to much larger applications for acquisition and countermeasures in the aerospace and defense market.
In addition to our extensive in-house testing with Semina, we have extended domain-specific testing resources by partnering with some of the largest tier one automotive suppliers in the world. In this process, we are exposed to their world-class processes, including environmental standards, product validation, functional safety, and performance benchmark.
This has led us to collaboratively working with some of the most influential and respected third party testing groups in the world. We have also taken the unique step of releasing these results when appropriate to the public.
As an example, we were closely with VSI, a leading independent researcher of active safety and automated vehicle technologies to validate the performance of our LiDAR for ADAS application.
We do this at locations such as the American Center for Mobility, where we were able to test and independently verify the ability of our products to perform.
In this VSI designed, produced and verified testing scenario, we were able to detect very small objects such as bricks at long range in inclement weather while inside a tunnel.
On top of that, we are demonstrating these capabilities with our lighter looking through windshield glass.
Opening yet another unique placement opportunity, not available to most traditional time of flight.
I will now turn things over to Bob Brown, our CFO , to discuss our financial update. Thanks, Flutter, and good afternoon, everyone.
Gap operating expenses of $24.5 million in the first quarter rose $14.1 million from the first quarter of last-
Our non-GAP operating expenses were $19.2 million in the first quarter, which excludes $5.3 million in stock-based compensation.
Net loss was $24.9 million on a gap basis, and gap ETS was a loss of 16 cents.
Net loss on a non-GAAP basis was $19.5 million in Q1, and non-GAAP EPS was a loss of 13 cents.
Net cash used in operating activities for the quarter was $16 million and our cap X was less than $1 million.
We'll continue to manage our cash carefully going forward and our team is managing to a strict budget.
The vast majority of our spending is focused on R&D operations and sales and marketing, with the goal of scaling our business as efficiently as possible.
We exited the quarter with $144 million of cash, cash equivalents, and marketable securities on our balance.
When we include up to $125 million of potential proceeds from our Common Stock Purchase Agreement, we believe our total available liquidity of $269 million provides us with a sound financial base to execute on our strategy.
We anticipate that we'll begin accessing the Common Stock Purchase Agreement this year. While we're on the balance sheet, I wanted to note that we adopted the new lease accounting standard, ASD842 and Q1.
As a result, you'll notice increases in right-of-use assets and operating lease liabilities. These amounts are primarily related to our-
It's exciting to see how we've grown over the last few years from an R&D focus entity into a commercial operate.
We're starting to reap the benefits of our capital-light strategy by focusing our time, effort, and money on our core competencies, and the activities that will extend our technological lead while getting our products to market fast.
We're executing our plan to develop products for both the automotive and industrial segments based on the same revolutionary architecture.
This is key because unlike most of our competitors, we don't need to develop different products for different applications.
We will use one software to find architecture for all applications across all landmarks.
We expect that this strategy will provide us with economies of scale and improve our margins as we grow the business.
Relative to our near-term outlook, we expect revenues in the second quarter to be about $700,000, as we wind down prototype sales in preparation for the ramp of the commercial version of our four-site M product in Q3.
So combined with the Q1 performance, our revenue for the first half of the year in total should be slightly ahead of expectation.
As we mentioned on our call last quarter, we expect to see revenue growth in the second half of this year as manufacturing of our commercial product starts to ramp at San Mena.
We expect that growth in the second half will enable us to deliver on our revenue goal of $4 million to $6 million for the full year.
We continue to expect a non-gap net loss of approximately $100 million for 2022.
I'm pleased with our team's performance in Q1, and we're tracking to our plan.
We continue to execute well against our strategic milestones, and we look forward to sharing further progress against our financial, commercial, and technical objectives in the coming quarter.
With that, I'll pass it back to Blair to wrap things up before we open the line for questions.
Want to close as we always do with our talent and culture.
We are fortunate that we continue to attract the brightest minds in the industry. This includes our
We started our advisory board very early in our history, and it has been a valuable resource for us as we have built our business.
We expect the latest additions to continue to be a vital part of AI. Let me introduce you to a few new members. Marcus Lepinski, our Blanchford and Dr. Erich Weinmann.
Marcus was most recently the Managing Director at Aptith, a global automotive tier one supplier. Previously he had been a leading executive at DW, Man Trucks, and Domla.
He has a history of delivering digital innovation in both the automotive and software industry.
Art has been an executive at Deineer, now Qualcomm, and Autolive to leading Tier 1 suppliers where he led global teams focusing on active safety solutions.
And finally, Dr. Wyman is extensive knowledge in the OEM space, predominantly as global SPP at Harmon and COO at Alpine electronics, as well as a senior executive at BMW.
We welcome you all to AI and look forward to working together.
cultural is a powerful force. And I would like to share with you today an employee driven initiative that we are very proud of. Over the last two years, we have partnered with Richard Branson and Virgin Galactic, Virgin Orbiter and Virgin Hyperloop to bring together our technologists and engineers to explore the future of transportation.
Part of this exploration has been to look at how we invest in the future and share this knowledge with the next generation.
One key element of this has been the development of the BLAST program. BLAST stands for Black Leaders in Aerospace Scholarship and Training.
by providing mentoring and internships, glass aspires to change the funnel by creating a village with a network of support that helps black students find connections and opportunities.
This program has also changed AI. In the process of mentoring, we learn. And we become inspired. I can honestly say this program has been a significant value ad to our culture and to our effect.
We hope last is also an example of how AI serves as a role model within our industry, and as a leader in providing opportunities to talented minorities for suing a career in engineering and technology.
Looking forward, I want to first thank the team for all their hard work as we've been busy this quarter, setting ourselves up for the rest of 2022, and setting the stage to scale in 2020.
As we mentioned at the beginning of the call, the world is changing quickly.
As a company, we are staying focused on the things we can control and leveraging tight relationships and the community of our employees and our partners.
During this call, we discussed our software platform and how we are implementing disruptive intelligence.