Thank you for joining the BigBear.ai First Quarter Conference Call. This call is being recorded. At this time, all participants are in a listen-only mode, a question and answer session will follow the presentation. If anyone should require operator assistance during the conference, please press star zero on your telephone keypad to reach a live operator. I will now turn the call over to Shane Karp, Vice President, Marketing and Communications. Please go ahead, Mr. Karp. Good afternoon, everyone. Welcome to BigBear.ai's 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. 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 chains 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 surface 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 systems 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 concepts Task Force 59 has worked tirelessly to develop. 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 Tradewinds 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 Tradewinds 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 8 years. 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 Tradewinds 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. We're not just winning at the federal level and in defense. The pandemic and subsequent disruptions demonstrated the dramatic impact of uncertainties on supply chains and established 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 seek to identify 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 affect change faster and with greater confidence in success. Our work in healthcare 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 a 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 healthcare 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. While the race is only getting going, 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. Pausing is the option that our adversaries would love for us to choose. As an organization who 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 and engineering and analytics segments into one reportable segment beginning this quarter. As Mandy discussed, we continue to reorganize the business to drive improved operational efficiencies. 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 complete. Total gross margin was 24% in the quarter, a 300 basis point decrease from 27% in Q1 2022, driven by additional costs 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 gap 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 fourth quarter of 2022. This is 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 non-cash 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 second half of 2023 to get to positive operational cash flow, which excludes non-recurring and non-operational 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 revenues in the range of $155 million-$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. 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 in 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. We continue to be proud of the focus and the agility of the BigBear.ai team to collaborate and innovate in changing times. Operator, we are ready for questions. Thank you. Thank you. If you have a question, please press star one on your telephone keypad at this time. If at any time your question has been answered, you can remove yourself from the queue by pressing one. Again, ladies and gentlemen, if you have a question or comment, please press star one on your telephone keypad. One moment while we poll for questions. Our first question comes from Mike Latimore. Please go ahead. Great. All right, great. Thank you. Yeah. Super results. Very nice to see and congrats on the new partnership there. Thank you, Mike. Thanks, Mike. Yeah. I guess just starting with that autonomous vessel program partnership, can you just provide a little more color there? You know, maybe start with the type of revenues you would see, you know, the software, professional services, data. You know, could we sort of simplistically say you get a certain amount of revenue per vessel shift? Or maybe just characterize, you know, that kind of opportunity a little more. Absolutely happy to. 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 vessels. 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. 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. I think it's fair to assume that it's really on 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? Yeah, definitely. Clearly the forecast for these autonomous vessels is for a pretty steep curve here, right? That's right. It's, I think, you know, 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. Very good. On the GFIM you mentioned, I think you said that the Phase 2 concludes this quarter, and then you might get some gap funding until the production phase. Is that what you said? Yeah. We are doing really well, in terms of the U.S. Army's Global Force Information Management program. That is the one where we're sole source for Phase 2. Mm-hmm. You know, as we talked about previously, while the final contract winner for phase three has not yet been announced, we are really well positioned, you know, 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. We're expecting a more normal margin profile associated with this project as it moves into production. It sounds like with that extension, you would continue to do work and see revenue. That's correct, yes. The next phase of the contract is obviously, you know, 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. Just last on the consolidation of the reporting segments. Is it fair to say that, you know, a lot of the projects you're working on basically are using the resources from Analytics and Cyber and just sort of makes sense to kind of have it as one now? Maybe can you just touch on that and how much crossover there actually is? Yeah. I mean, basically, Mike, we are instead of continuing to. Focus on these two different segments. What 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 gonna help us just to streamline the way we deliver our services to our customers as well as just operationally much more efficient. It's really just the 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, so that's good. We like that. Anything we can do. Yeah. Yeah. All right. Thanks very much. Best of luck. Thanks, Mike. Thanks, Mike. Our next question comes from Louie DiPalma of William Blair. Please go ahead, sir. Mandy and Julie, good afternoon. Hi, Louie. Good afternoon. Hi, congrats on the partnership with L3Harris. Thank you very much. Thank you. 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. Did you actually give out the number of vessels that are planned for the initial phase? We did not because, I mean, frankly, the plan is that we will scale together. Our role in the partnership is to supply L3Harris with its computer vision, predictive analytics, and related AI applications to improve the manned-unmanned teaming that's on the water. How we're looking at it is that as additional vessels are built and are released and begin to operate, that our software will be running on that. 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. 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 current intent to be able to support and service both. Great. 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, like, their space systems and their, like, tactical communication systems and, you know, 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. You know, 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, you know, be a great partner in that so that we earn that right together. Thanks. For Julie, I think you referenced the upfront costs associated with the Phase 2 of the GFIM contract. 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. I mean, you know, that is part of the overall, you know, OTA structure of the way the federal government is now doing some of their contracting. As we move forward from a Phase 1, which is a, you know, basically an investment upfront to a Phase 2, which is, you know, some investment as well as, you know, hopefully some profitability, you're proving out your capabilities. You're making sure that things are working correctly. Then as you move into production, that's when you would expect the margin to significantly get better. We are looking forward to that day when we can prove out that capability and we move into the production. That is, just to be clear on that, Louie, you know, we would expect that to be very late this year based on the timing that we're currently hearing. I mean, we're hoping sooner, but we know that they're gonna continue to support us with gap funding until that can happen. That probably will not happen until later in the year. It's FY 2024 funding. Great. In terms of your end markets, there's been a lot of focus on the macroeconomy 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, like, 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. If you think about what those are, right, and the purpose that they serve, they really sit in the critical path from an operational decision-making standpoint. 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. 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, and the evolution of their products, we fit into the modeling capabilities around that because that's our core, right. We do digital twins, we do simulation scenarios for that type of planning. 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, you know, big shipyards. That's what we know how to do. Fantastic. Thanks, Julie. Thanks, Mandy. Very welcome. Thanks, Louie. Our next question is from Param Singh of Oppenheimer. Please go ahead. Yeah. Hi. Thank you for taking my question. This is Param Singh on behalf of [Ittai Kidron]. So, you know, firstly, there's been a lot of talk in the last few months on generative AI and then you've seen a lot of things in the public domain. I wanted to get a sense from you, Mandy. How does that figure into what BigBear is offering today? What are you working on, whether it helps your commercial side, your government side of the business because now it seems a lot of this is, selling commoditize. 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, 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 maybe just diving into that, some of the things that have been beneficial, you just mentioned digital twins that have been very machine learning type model. And now we're seeing things that are based on transformer model. So it seems to be a bit of leagfrog here. I want to get a sense just broader in terms of technology, what is your view of transformer models getting adopted in domain-specific region? I mean I would imagine you talked about discreet events within manufacturing and health care, that would be the next step, right? I believe they are not an implementation today, but how do you view that in like two to five years? Yes. It's a fair question. I think you have to break a part 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 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. No, thank you so much. Maybe you could help me just tie this just into, you know, what you're seeing on the commercial revenue side. Obviously, that used to be an area of growth for BigBear, but now, you know, you've also combined your analytics division into C&A. Is there a shift in the way you view your commercial business? Or should we also view that as an optionality going forward and something that would be, you know, more than 10% at some point in the next few years? As I mentioned previously, we're continuing to see our commercial business grow, just as we're seeing our broader federal business grow. You know, I continue to believe that both of those sides of our portfolio are going to be successful. You know, as we cross that threshold, we will certainly, you know, begin to talk about them in that way. Got it. I would imagine the gross margin profile of that business would be closer towards software than towards services point that you see within your defense contracts. Would that be a right assumption? I think what's important to remember is that at the end of the day, we're a technology-led solutions organization. The products that we offer, the software capabilities that we offer, in most cases are highly tailored to very complex environments, right? You know, the industrial community, we bring services along with those because the subject matter expertise is so specific. I would say we'll probably be in the realm of other tech-led services providers. No, that's helpful, Mandy. Thank you. you know, maybe looking at your full year revenue guide, and you had a pretty solid quarter. It just seems that it's gonna be flat for the rest of the year, right? It's pretty standard across the board for the remaining [3 Qs]. you know, given all the contracts and the relationships that you talked about today, you know, the addition, the L3 relationship, you know, the progression with GFIM and potentially, you know, something from the [IDIQ] contract coming into play, why wouldn't we see revenue improve through the rest of the year? I was gonna say, just as a reminder, we mentioned this in our statement earlier, you know, because of the nature of the work that we do, our revenue can be lumpy. It's based on when contracts start, it's based on milestones, it's based on when some contracts are completing. I would be, just I'd advise you to make sure you're thinking about, you know, that overall structure of our type of business. I mean, I think that'll smooth out over time as we become more mature and get larger. As of right now, it's pretty lumpy. You know, we're just really looking at our profile in terms of what we have as ability to as of now and as of today and what we see down the pike. You know, we just wanna make sure that we're providing the right guidance based on what we're seeing. As those things come up, you know, we'll assess them and decide if that's the right time to make a change. Right now, this is our guidance. No, that's fair. Thank you so much for the clarity. Maybe one last question. You know, I've seen the shelf registration. The takeaway, should it be that you would need maybe one other round of funding before you get to cash flow positive? Is that the takeaway from it? It's just something to keep on the back burner as a safety net? Well, no, I would say, you know, in terms of our liquidity and our cash flow forecast, I mean, we are saying that we believe that with our restructuring efforts that we've done so far and with our cost structure that we have in place based on our profile, that we expect to be cash flow positive in the back half of the year on an operational basis and non-recurring. What I mean by that being, if you look at our true operations, our recurring operations, and take out, you know, I'll say interest payments and things like tax payments on investing, truly recurring operations, we expect to be positive. You know, that said, we did do the shelf to allow us to have access to those capital markets so that we can go much more easily, you know, look at opportunities, whether that's through inorganic growth or through just overall operations and accelerating our pace, that we can go to the capital markets if we need to. Right now we're saying, as we stand today with our liquidity profile, we feel okay about the back half of the year being cash flow positive from an operational perspective. Really helpful. Thank you so much. I'll get back in the line. Thank you. Thank you. Thank you. 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.