BigBear.ai Holdings, Inc. Q1 FY2023 Earnings Call

Good afternoon, everyone, and welcome to BigBear.ai 2023 First Quarter Conference Call. I'm joined by Mandy Long, our Chief Executive Officer; and Julie Peffer, our Chief Financial Officer. During the call today, we may make certain forward-looking statements. Listeners are cautioned not to put undue reliance on the forward-looking statements, and BigBear.ai specifically disclaims any obligation to update the forward-looking statements that may be discussed during this call. Many factors could cause actual events to differ materially from the forward-looking statements made on the call. These statements are based on current expectations and assumptions, and as a result, are subject to risks and uncertainties. For more information about these risks and uncertainties, please refer to the forward-looking statements section of the earnings press release issued today and our SEC filings. We will also discuss some non-GAAP financial measures during the call today. These non-GAAP financial measures should not be considered a replacement for and should be read together with GAAP results. You can find the GAAP and non-GAAP reconciliations within our earnings release. Now I'd like to turn the call over to Mandy.

Thank you, Shane, and thank you all for joining today's call. The results we posted in Q1 are a testament to our capabilities across autonomous systems, cybersecurity, and supply chain and logistics. Our 16% revenue growth year-over-year, despite a challenging macroeconomic environment, is a remarkable achievement for the entire team and speaks volumes to the value we are bringing to our clients. We're winning in complex markets, setting us apart in the industries we operate in and positioning us for long-term growth. Our established position and ability to execute are evident in new partnerships, new wins, and extensions of our business with existing customers. As you may have seen in our recent press release, we are excited about our new strategic partnership with L3Harris. BigBear.ai is now their exclusive partner to deliver AI/ML-based forecasting, situational awareness analytics, and computer vision capabilities for L3Harris unmanned service vessels. This integrated and collaborative approach brings significant long-term opportunities, and our partnership with L3Harris is another proof point in our continued focus on execution and long-term growth. We are also continuing to bring our autonomous system software capabilities to market, like with the U.S. Navy, where our analytics and computer vision capabilities continue to be assessed and demonstrated in live exercises as shown most recently with Task Force 59 and IMX 2023. We are incredibly excited by the Navy's April announcement to continue to scale unmanned platforms, integrating unmanned systems into their Fourth Fleet in Central and South America and operationalizing the concept Task Force 59 has worked tirelessly to develop. In addition, we believe the Navy's decision to scale unmanned platforms to the Fourth Fleet and their engagement with us through Task Force 59 underscores the importance of autonomous systems in future battlefields. Our advanced AI/ML capabilities enable autonomous systems to operate with unparalleled efficiency and safety, supporting higher-risk missions, expanding operational reach, and most importantly, saving lives. As the battle space continues to evolve, autonomous systems will play an increasingly significant role. As a leader in providing AI/ML-based forecasting, situational awareness analytics, and computer vision capabilities for these autonomous systems, our opportunities to support this type of work are only just getting started. We're continuing to see more rapid adoption of AI- and ML-based solutions and technologies throughout the entire Department of Defense. Innovative approaches to acquiring these AI-focused capabilities, such as the Chief Digital and Artificial Intelligence Office's Tradewind Initiative, provide a marketplace for DoD leaders to rapidly source, fund, and develop solutions in the AI/ML, digital, and data analytics spaces. We are excited to announce the recent addition of two of our products to the Tradewind marketplace. Observe is our massive distributed data collection capability focused on capturing publicly available information at scale and has a proven track record of providing actionable decision intelligence for our customers for more than eight years. Additionally, our AI/ML-based forecasting, situational awareness analytics, and computer vision capabilities originally developed for autonomous systems will now be widely available for many other DoD use cases. We look forward to onboarding other portfolio solutions into the Tradewind marketplace in the coming weeks and months. This is all in the service of supporting the speed, efficacy, and accuracy of our customers' decision-making processes. We continue to operationalize artificial intelligence and machine learning at scale by creating order from complex data, identifying blind spots, and building predictive outcomes. And we're not just winning at the federal level and in defense, the pandemic and subsequent disruption demonstrate the dramatic impact of uncertainties on supply chains and establish the need for intelligent contingency plans to minimize the impact on operations. AI has the power to revolutionize the way we handle logistics, optimize production processes, and improve overall efficiency. Through decision intelligence algorithms, machine learning, and real-time data analytics, we can better forecast demand, minimize inventory costs, and ensure on-time delivery of products. AI can play a similarly impactful role in manufacturing, helping to detect quality issues early on, improve product design, automate repetitive tasks, and help free up valuable time and resources for higher-level work. Ultimately, we're looking to provide a higher form of decision intelligence, empowering businesses to make smarter, data-driven decisions that streamline operations and help drive profitability. We have already been making a lot of progress. We recently extended our relationship with a global Fortune 500 food company that has been using BigBear.ai simulation tools since 2020. They work with us to extend discrete event simulation modeling to evaluate production of existing lines and also support design, test, and evaluation of potentially new production areas. In support of these solutions, we've integrated resources directly with the company to perform the project management and data collection responsibilities to ensure successful and on-time delivery of set objectives. The simulation solutions that are being created speak to identifying bottlenecks and opportunities for process improvement, while also providing the confidence that any new design or build option is tested thoroughly before any major investments are made. We're enabling similar decision-making in a large diesel engine manufacturer that's looking to allocate capital to phase out old designs and drive extensive design work, capital equipment deployment, and plant modification. Given the capital and resource-intensive nature of this endeavor, extensive verification and validation efforts of the proposed changes must be executed. To unleash their success, we're building a comprehensive discrete event simulation model of their current and future state production systems, enabling scenario analysis and experimentation in a digital twin. As a result, our customer will be able to deploy capital and effect change faster and with greater confidence and success. Our work in health care continues to pay off as we signed a number of new contracts with hospitals, such as the Children's Hospital Colorado and Thomas Jefferson University Hospitals for FutureFlow Rx and MedModel. For Thomas Jefferson, we designed the department-level simulation to support future state operations for observation, extended recovery patients, and to inform long-term staffing needs. This is incredibly important as the staffing crisis in health care continues and as the pressure on hospitals and health systems increases with the aging population needing more care. While it's easy to focus on the headline wins, the foundational work we are doing to ensure our long-term success continues to be a part of the team's focus. During the quarter, we continued our move towards a streamlined approach with a simplified reporting framework and a sustained rigor on cost management. Our work this past quarter focused on improving our operating processes and tightly managing discretionary spending. Cost discipline will remain a priority as it forces rigor and prioritization around decision-making and unlocks growth opportunities by fueling the most impactful areas of our business, while also putting us in a much better position to deliver meaningful shareholder returns over time. With much of our restructuring now behind us, our new operating model is positioned for positive operational cash flows in the back half of 2023. Bigger picture, AI continues to experience an unprecedented wave of excitement as the entire ecosystem of enterprise applications looks for new ways to leverage this disruptive technology. Winners and losers will emerge from this period of rapid maturation, and those with the ability to grow and execute at scale will be well-positioned to take share across various end markets. The industry has received a lot of attention over the last year. And while the race is only getting started, BigBear.ai has a meaningful head start. It is with this head start that we've been able to make strategic hires such as Norm Laudermilch, who will be taking over the role of Chief Operating Officer. Norm has 30 years of technical and executive-level experience and has served in a number of roles, including Chief Operating Officer, Chief Technology Officer, and Chief Information Security Officer. He has experience in both startup and Fortune 50 companies across federal and commercial markets. We are also promoting Greg Goldwater to Chief Growth Officer. As Chief Growth Officer, Greg will continue to develop strategies to drive growth across the entire BigBear.ai business and identify new opportunities that align with our capabilities and our core mission to deliver clarity for the world's most complex decisions. Lastly, many of you have likely heard the recent calls for pausing AI development. My thoughts on this are simple; powerful technology that has the ability to change the world does not come without risk, and pausing is the option that our adversaries would love for us to choose. As an organization that works every day to protect our nation and what it stands for, our role is to leverage these capabilities responsibly and ethically and put them to work where they can make a difference in our national security and in the other environments that we service. That is what we do. And it is why we are the company that our customers call when the hardest problems need to be solved. We have been a leader in providing a higher form of decision intelligence for more than 20 years. We are our customers' North Star in this AI-driven industrial revolution, and we are doing so with a strong foundation to ensure lasting impact for the company and for our shareholders. We have a leaner, more nimble business today, and we will hire and retain those who are here for the mission and can do things that others cannot. We are now stronger and more resilient than we were six months ago, and we are just getting started. With that, I will turn the call over to Julie for a detailed review of our financials.

Thank you, Mandy. Before I dive into the financials, I'd like to address the consolidation of our legacy Cyber & Engineering and Analytics segment into one reportable segment beginning this quarter. As Mandy discussed, we continue to reorganize the business to drive improved operational efficiencies. And as part of the leadership announcements we've made today, we're moving into a more functional structure that will ensure we go to market, develop products and solutions, and drive delivery execution as one team. Segment changes were implemented as of Q1 2023, and historical data in the new segment is available as a consolidated view. Now let's turn to our first-quarter results. Revenue for the quarter was $42.2 million, up 16% year-over-year and compared to $36.4 million in the first quarter of 2022. This is primarily driven by growth with our Army customer through contracts such as Global Force Information Management, or GFIM Phase 2, and other key programs. As we have stated in the past, I do want to reemphasize that our revenue can be lumpy and can fluctuate meaningfully depending on the quarter in which contracts are awarded, milestones achieved, or contracts completed. Total gross margin was 24% in the quarter, a 300 basis point decrease from 27% in Q1 2022, driven by additional cost on the GFIM Phase 2 program, which completes in the second quarter of 2023. We're performing well on this program but continue to invest in critical capabilities to maintain our strong position as we move towards the production contract. We are in active discussions to continue this important work through GAAP funding until the production contract can be funded with 2024 government fiscal year funding. Backlog was $197 million at the end of the first quarter, which is down 10% or $22 million compared to the fourth quarter of 2022. This was driven by the removal of Virgin Orbit from our backlog due to the uncertainty from their recent bankruptcy announcement. Now turning to expenses. For Q1, operating expenses were $22.2 million, which includes R&D expense of $1.1 million and SG&A expenses of $20.4 million. On a year-over-year basis, total operating expenses were lower by 15% this year in Q1. As a reminder, we began to ramp up indirect hiring in late Q1 last year, with hiring hitting a peak in Q2 2022 before declining substantially through the rest of the year. We will continue to be disciplined in our expense management and focus on implementing scalable processes, operating rigor, and driving overall efficiency across our business. Net loss was $26.2 million in the quarter versus $18.8 million in Q1 of 2022. Net loss of $26.2 million for the first quarter of 2023 includes $10.6 million of noncash expense related to the change in fair value of PIPE warrants that were issued in January 2023, $3.8 million of equity-based compensation, and $0.8 million related to restructuring charges. Net loss for the quarter of 2022 was $18.8 million. Adjusted EBITDA was a loss of $3.8 million in Q1 2023, compared to adjusted EBITDA loss of $2.5 million in the fourth quarter and $3.9 million in the third quarter of last year. Q1 adjusted EBITDA was impacted by a one-time bad debt reserve booked against receivables owed by Virgin Orbit, who announced bankruptcy in April. In addition to the gross margin compression from investments in the quarter on key programs such as GFIM Phase 2. In review of the balance sheet, at the end of the first quarter, we had cash and cash equivalents of approximately $21.8 million. This increase was due to the PIPE transaction that we completed in January. We continue to focus on lowering our cash burn in the second half of 2023 to get to positive operational cash flow, which excludes nonrecurring and nonoperational items such as interest payments, transaction fees, and tax payments for stock vesting. In addition to lowering our cash burn, the $500 million shelf registration that we filed in April will allow us to more easily access capital markets moving forward in support of organic and inorganic growth at this pivotal time in the AI industry landscape. Now turning to our financial outlook. Today, we are reaffirming our guidance of expected 2023 revenue in the range of $155 million to $170 million. We continue to expect adjusted EBITDA to be single-digit negative adjusted EBITDA in millions for 2023. As Mandy previously stated, 2023 continues to be a foundational year for us as we build out our operational rigor and enhance our go-to-market capabilities, but we are thrilled with the progress we've seen so far. We're very excited about our new strategic partnership with L3Harris to deliver AI/ML capabilities to their unmanned surface vessels as well as emerging opportunities as we expand our core and adjacent markets. We will continue to be disciplined in cost management, and we will make targeted investments to accelerate our position as an industry leader in AI. I will now turn to Mandy for final remarks before we turn to Q&A.

Thank you, Julie. I'm extremely excited about the pipeline ahead and our ability to deliver as we move forward. Our cost-cutting initiatives have been challenging, but we continue to be proud of the focus and agility of BigBear.ai to collaborate and innovate in changing times. Operator, we are ready for questions. Thank you.

And our first question comes from Mike Latimore.

Super results, very nice to see, and congrats on the new partnership there. Yes, I guess just starting with that autonomous vessel program partnership, can you just provide a little more color there? Maybe start with the type of revenues you would see, the software, professional services data. Could we sort of simplistically say you get a certain amount of revenue per vessel shift? Or maybe just characterize that kind of opportunity a little more.

Absolutely happy to. So as we articulated in our joint press release, one of the things that we're really excited about in this is that it's a comprehensive teaming agreement that allows us to deliver AI for their autonomous surface vessels. Now what this means for us, right, and where we've been working is our current projects have been focused on the Office of Naval Research doing operational demonstrations with the integrated solution, right, which is our capabilities running on L3Harris' autonomous surface vessel. And at the conclusion of the exercise, our intent at that point is to kind of gain a deeper understanding of not only the progress that we've made, but how we really look to scale it. So I think the short answer, Mike, is that we're still in the early days of figuring out how with this embedded capability, we bring it and kind of go faster, right, from an execution standpoint in terms of delivering more to the customer, but I think it's fair to assume that it's really at a per vessel basis, right? Because as the vessel base grows, we will deploy more of our instances, and we will see growth from that. Does that answer your question?

Yes, that's fine. And clearly, the forecast for these autonomous vessels is for a pretty steep curve here, right? That's right. It's, I think, one of the most dynamic and rapidly growing parts of our industry, and we feel really privileged to be able to partner with such a great organization like L3Harris. Great. And then on the GFIM, you mentioned I think you said that the Phase 2 concludes this quarter, and then you might get some GAAP funding until the production phase. Is that what you said?

Yes. So we are doing really well in terms of the U.S. Army's Global Force Information Management program, and that is the one where we're sole force for Phase 2. And as we talked about previously, while the final contract winner for Phase 2 has not yet set now, we are really well-positioned following that work, continuing our delivery and our relationship with the customer. We are anticipating a six-month extension to the current phase of GFIM to complete some added functionality before moving to the production contract. And we're expecting a more normal margin profile associated with this project as it moves into production.

Okay. So it sounds like with that extension you would continue to do work and see revenue.

That's correct, yes. And then the next phase of the contract is obviously being finalized by the U.S. Army, but it's our intent to continue to work and progress so that when it's time to go to production, we're as ready as possible.

Very good. That sounds good. And then just last on the consolidation of the reporting segments. Is it fair to say that a lot of the projects you're working on basically are using the resources from analytics and cyber, just sort of makes sense to kind of have it as one now? And maybe can you just touch on that and how much crossover there actually is?

Yes. I mean basically, Mike, we are instead of continuing to focus on these two segments we recognize is in order to streamline and really focus. And part of this is the announcements we've made today with Greg and with Norm joining the team. We are thinking that we're much more functionally organized. And this is really going to help us just to streamline the way we deliver our services to our customers as well as just operationally much more efficient. So it's really just a combination of those two, and it just allows us to be much more efficient in how we're thinking about the business.

Great. It makes my modeling a little easier too.

We like that.

Anything we can do.

Congrats on the partnership with L3Harris. We're incredibly proud. You may have mentioned this in the prepared remarks, but what is the scale of the L3Harris partnership in terms of the number of unmanned vessels that you will be deployed on? I think in the answer to the previous question, you suggested that you'd be paid based upon the number of vessels, but did you actually give out the number of vessels that are planned for the initial phase?

We did not provide that number because, frankly, the plan is to scale together. Our role in the partnership is to supply L3Harris with its computer vision, predictive analytics, and related AI applications to enhance the unmanned teaming that operates on the water. We're approaching this by ensuring that as more vessels are constructed, launched, and begin operations, our software will be integrated into those vessels.

Okay. So will it be focused more on new vessels versus the existing fleet? Or will it be a combination of both?

No, it's a combination of both, and that's a great question. So there is obviously a go-forward market associated with new unmanned surface vessels that are built, but there's also a market associated with retrofitting existing vessels that are on the water and our intent to be able to support and service both.

Great. And somewhat on the same topic, L3Harris, they're obviously a huge contractor and they do a lot more than just these unmanned vessels in which it seems that there are like many more partnership opportunities for you. Is there the potential that your data analytics platform can also work with their space systems and their tactical communication systems and their cameras that are deployed on aerial drones? Are you in discussions for any of those other opportunities?

It's a great question. I think something that's important to note as a part of our relationship with L3Harris is that we have had a relationship with L3Harris for a long time. We're already in many ways an integrated partner. We work in a variety of different parts of their business. This particular strategic partnership is focused on the maritime use cases for autonomous surface vessels. I would love to say in the future. And I think as we continue to be successful together in market, I have no doubt that additional market opportunities will open up, and it's our job to be a great partner in that so that we are in that race together.

And for Julie, I think you referenced the upfront costs associated with the Phase 2 of the GFIM contract, because you're incurring these upfront costs, is the margin profile for the production contract expected to be more attractive than the margin profile for GFIM Phase 2?

Yes, absolutely. That is part of how the federal government is structuring some of their contracts now. As we transition from Phase 1, which involves an upfront investment, to Phase 2, which will also include some investment and hopefully some profitability, we are demonstrating our capabilities and ensuring that everything is functioning as it should. As we move into production, we expect the margins to improve significantly. We look forward to the time when we can demonstrate that capability and enter production. To clarify, we anticipate this will happen late this year based on the timing we are hearing. We hope it will be sooner, but we understand that they will continue to support us with GAAP lending until then. Therefore, we do not expect this to occur until later in the year, aligned with FY '24 funding.

Great. And in terms of your end markets, there's been a lot of focus on the macro economy and the recession, but you seem to indicate that your software is gaining traction for supply chain use cases. And you mentioned how your software is deployed in different hospitals. Are you continuing to see growth even in this difficult macroeconomic environment from your commercial customer base?

It's a great question. And I think the short answer is, yes; the longer answer is that our software capabilities in the commercial side, right, the core area where we're seeing a lot of growth is related to our discrete event simulation capabilities. And if you think about what those are and the purpose that they serve, they really sit in the critical path from an operational decision-making standpoint. And so if you're an organization that's dealing with the macroeconomic pressures that we've been talking about and you're looking for opportunities to be able to deploy capital as efficiently as possible to be able to scale and optimize the work that you do, either from a manufacturing standpoint or a distribution standpoint or even how you're running your warehouses, our tools fit right into that. And as a lot of companies are going through the process of figuring out how to deal with shifts in demand as well as continued shifts in technology, right, in the evolution of their products, we fit into the modeling capabilities around that because that's our core, right? We do digital twin; we do simulation scenarios for that type of planning. So we do continue to see that part of our business grow, particularly when paired not only with the product side but also with the services side associated with the subject matter expertise that we bring to a lot of those use cases, right? Like we talked about previously, hospitals and health systems, life sciences, manufacturing, big shipyards; that's what we know how to do.

And our next question is from Param Singh of Oppenheimer.

This is Param Singh speaking for Ittai Kidron. There's been considerable discussion about generative AI in recent months, and we've observed various developments in the public domain. I would like to understand, Mandy, how this influences what BigBear is currently offering. What initiatives are you pursuing, and do they benefit your commercial and government sectors, considering much of this seems to have become commoditized?

Sure. I mean, I think as we talked a little bit about on the last earnings call, right, large language models and these capabilities have been in use, right, by ourselves as well as others for a while. I think what's really extraordinary about what's happening today is that we're seeing the scaled implementation and availability of them in a really democratized fashion. We're still very early days in how this type of technology is going to be used in the broader consumer community. But from an application to the industries that we service, right, focused on defense, intel, complex manufacturing, and industrial, we absolutely leverage those types of models as a part of our portfolio of offerings and the services that we deliver and we'll continue to do so.

So diving into that, some beneficial developments include digital twins and machine learning models. We're now witnessing advancements based on transformer models, suggesting a leap forward. I would like to understand your perspective on the adoption of transformer models in specific domains. Considering areas like discrete events in manufacturing and healthcare, that seems to be the logical next step. While these models are not currently implemented, how do you see their adoption evolving over the next two to five years?

Yes. It's a fair question. I think you have to break apart the use cases. And I think your point on verticalization is important because there are going to be certain environments that we are going to see the applicability of these types of models be earlier, right, just as a result of whether it's a regulatory environment or a security environment; they may be better-suited, right, for early adoption in those use cases. I think your point about discrete event simulation is excellent because we do see a lot of use cases emerging around things like predictive maintenance, right, being able to do further optimization as a derivative of running past scenarios and being able to really lean into the infinite compute that we can tap into today. So yes, it is there a transformation happening under our feet? Unquestionably. Are we starting to, I think, wrap our arms around the multi-threaded implications of it? Also, yes. We're seeing a lot of announcements to the market in terms of being able to put these types of interfaces in front of traditionally kind of engineering-focused experiences. Most of the markets that kind of we service and fit in tend to be highly technical and tend to require a little bit more, right, hands-on in terms of the data science and the role of the engineer. But do I see opportunities for efficiency and scale? Yes, right. We're continuing to make investments in those.

Great. So maybe you could help me just tie this into what you're seeing on the commercial revenue side. Obviously, that used to be an area of growth for BigBear. But now you've also combined your Analytics division into C&A. So is there a shift in the way where you view your commercial business? Or should we also view that as an optionality going forward and something that would be more than 10% at some point in the next few years?

We are continuing to see growth in our commercial business alongside the growth in our broader federal business. I believe that both aspects of our portfolio will be successful. As we reach that milestone, we will certainly begin to discuss them in that context.

I imagine that the gross margin profile of that business would be more similar to software than to the services you see in your defense contracts. Would that be accurate?

I think what's important to remember is that at the end of the day, we're a technology-led solutions organization. So the products that we offer, the software capabilities that we offer in most cases are highly tailored to very complex environments, right? The industrial community, we bring services along with those because the subject matter expertise is so specific. So I would say we'll probably be in the realm of other tech-led services providers.

That's helpful, Mandy. Looking at your full year revenue guidance, you had a solid quarter, but it seems like it will be flat for the rest of the year. This appears to be consistent across the remaining three quarters. Considering the contracts and relationships you mentioned today, like the LCV relationship and the progress with GFIM, as well as the potential from the IDIT contract, why wouldn't we see revenue improve for the rest of the year?

Yes. I want to remind you that, as we mentioned earlier, the nature of our work means our revenue can be inconsistent. It depends on when contracts begin, milestones are reached, and when some contracts conclude. So, I advise you to consider the overall structure of our business. I believe this will stabilize over time as we mature and grow, but for now, it remains inconsistent. We are currently focused on our situation and what we foresee in the future. We aim to provide accurate guidance based on our observations. As new developments arise, we will evaluate them and determine if it's the right moment to adjust our guidance. But at this point, this is our guidance.

That's fair. And then maybe one last question, the shelf registration. The takeaway should be that you would need maybe one other round of funding before you get to cash flow positive, is that the takeaway from it? Or it's just something to keep on the back burner as a safety net?

I would say that in terms of our liquidity and cash flow forecast, we believe our restructuring efforts and current cost structure will enable us to be cash flow positive in the latter half of the year on an operational basis, excluding nonrecurring items. This means that when we focus on our core operations and exclude interest and tax payments, we expect to see positive performance. We initiated the shelf registration to give us access to capital markets, allowing us to explore opportunities, whether for inorganic growth or to enhance our overall operations. This ensures we can access capital markets if needed. However, at this moment, considering our liquidity position, we are confident about achieving cash flow positivity in the second half of the year from an operational standpoint.

There are no further questions at this time. This concludes the conference call. We thank you for your participation. You may disconnect your lines at this time, and have a great day.