Greetings, and welcome to the BigBear.ai Holdings, Inc second quarter 2026 earnings call and webcast. At this time, all participants are in a listen-only mode. A question-and-answer session will follow the formal presentation. As a reminder, this conference is being recorded. It is now my pleasure to introduce your host, Sean Ricker, Chief Financial Officer. Thank you. You may begin. Good afternoon, and thank you all for joining us today for our second quarter 2026 earnings call. I'm Sean Ricker, CFO of BigBear.ai. I'm joined today by our CEO, Kevin McAleenan. Statements made in today's call that are not historical fact are considered forward-looking statements and are made pursuant to the safe harbor provisions of the federal securities laws. Actual results may differ materially from those projected in the forward-looking statements. Please see today's press release and our SEC filings for a description of some of the factors that may cause actual results to differ materially from those in the forward-looking statements. We also have posted tables on our website today that we plan to address during the call to supplement our comments. These tables also include information regarding non-GAAP measures that may be used in today's call. Please access our website at www.bigbear.ai and click on the Investor Relations link to view and follow the charts. Now, I'll hand it over to Kevin. Good afternoon, and thank you, Sean. I'm pleased to report to our investors that BigBear.ai had a strong quarter. First, revenue for the second quarter of 2026 exceeded revenue for the same period in 2025 by 13%, and our gross margin improved by 781 basis points. We are on track to meet our top-line guidance in the range of $135 million-$165 million. A s a leadership team, we are fully focused on following through, hitting our targets, and continuing to earn investor trust. Second, we continue to win new contracts with both existing and new customers in the U.S. and abroad. I'm happy to share that we won more than 20 new contracts with customers in quarter two, with values ranging up to $5 million each. For confidentiality reasons, we can't share the details of many of them, but I'll touch on a few. This follows our announcement in Q1 of a longer-term contract with an intelligence customer with a total contract value of $53 million. Each win proves that customers want specialized AI for complex use cases in secure environments that very few companies have the operational insight to deliver. Customers see that we are focused on the right problems and have the capability to help solve them. As a result, our backlog has grown by 9% since year end, and the pipeline continues to be healthy. Third, thanks to a clear strategy and focused use of our development resources, we have deployed product enhancements and capabilities that are fundamentally changing operators' ability to drive mission performance across a range of use cases, from cargo inspection to generative AI to drone swarm orchestration. I'll describe some of these examples shortly. These three facts, that BigBear.ai is on track to forecast, realizing strong customer wins in multiple categories, and generating traction for product innovation, strengthen my confidence that we are building momentum as a company. We have laid excellent financial foundations, focused our talent on a disciplined strategy, and global market trends are in our favor. If I step back and consider what we thought would be true now when we began resetting BigBear.ai in early 2025, our key underlying assumptions are playing out. Government and business leaders globally are confronted by great power competition and rolling regional conflicts. BigBear.ai was prepared for this shift, thanks to our long-standing work for national security customers and our development of technologies targeted to meet new operational needs. This is the core of our expertise and customer trust. Our roots are deep in mission environments, supporting both domestic and international security. The trend line for increased investment in and focus on enhanced defense and security technologies is set both in the U.S. and among our allies. AI and alternative technologies are fundamental to the reimagined global battlefield and emerging military strategy. Commercial entities, especially those engaged in securing and facilitating trade and travel, urgently need advanced applied AI technologies, particularly for supply chain security. Domestic threat landscapes are far more dynamic as well. Counterterrorism professionals must sprint to stay ahead of threat actors who have access to powerful technologies at low cost. These asymmetric threats make BigBear.ai's technologies and experience ever more relevant to our core customers and of interest to new customers who would not previously have considered security as their priority. Critical infrastructure must be protected. We predicted many of these changes when I led the Department of Homeland Security. Many of the threats we face now, including drone swarms and the potential for autonomous attacks on public events, as well as AI-enabled cyber threats, were detailed in the DHS 2019 Strategic Framework for Countering Terrorism and Targeted Violence and have become very real today. Additionally, the global travel and tourism industry is projected to reach an all-time high in 2026, accounting for 9.9% of global GDP, which represents 3.2% growth. In global trade, structural changes have led to increased investment in technology by companies and countries who must adapt to far more complex regulatory regimes. Compounding shocks and the challenges of capacity and security have all driven broad reprioritization towards solving long-standing border management challenges with new technologies, including redesigning immigration systems. These issues sit at the heart of political agendas in both the developed and developing world. BigBear.ai builds and deploys technology to address each of these macro themes, which often converge. Capital in the private as well as public markets is increasingly invested in businesses with the experience to build, acquire, and deploy defense and security technologies that will fundamentally change the world we live in, making nations stronger, safer, and more prosperous. That's why, as we enter the second half of 2026, we are increasing our pace to meet these opportunities. My full focus is on two objectives—d elivering top-line revenue growth and accelerating our hunt for accretive M&A targets that offer catalytic technologies with clear potential for rapid deployment at scale. I'm confident that we can do this because, as you will see from the examples that follow, we have now fully integrated both acquisitions we executed in the last six months, Ask Sage and CargoSeer. These teams are now very much part of the day-to-day of the business and are performing well. While we will be deliberate about deploying our available cash reserves to acquire new targets, given the dynamic opportunities and very large addressable markets we are focused on, we believe this is time to be aggressive. The BigBear.ai leadership team is ambitious and driving forward. My confidence in our ability to move fast rests on the simple fact that most companies today are searching to find their place in a world being redesigned by AI. BigBear.ai does not face that problem. Applied AI is at the very core of our value proposition and growth strategy, and the operators we serve understand and are hungry to use AI where their use cases are real and urgent. To bring this to life, let me move now to three operational use cases for our technology. Each represents a recent enhancement and is underpinned by an example of business that we have won with an active customer. The first is illustrated by a significant win in the last week for CargoSeer in El Salvador. We signed a five-year commercial deployment agreement with a strategic regional Customs expert following a successful 12-month pilot. This is the first deployment of CargoSeer in Central America, bringing cargo X-ray imagery, import and export documents, and structured trade data into a single workflow. It helps El Salvador Customs officials detect contraband, collect the correct duties, and keep legitimate trade moving. Let's now look at the general application for CargoSeer. The operational challenges facing Customs officers all over the world, including the increasing tension between growing trade volumes and increasing smuggling threats, are substantial. The Customs officer inspecting a shipment must evaluate rapidly, assessing an X-ray image, a Customs declaration, and other trade data to judge whether the cargo is legitimate, often with little more than a pen, a clipboard, and pages of manifest data. An anomaly may signal a concealed contraband, a misclassified commodity, or a trafficked human being, while legitimate shipments need to keep moving. The stakes are high. An error can cost the country significant revenue, put lives at risk through drug or human trafficking, or choke legitimate trade. That is a visibility, speed, and volume problem that CargoSeer solves. Just as a doctor reads an X-ray alongside patient history to diagnose, CargoSeer analyzes the cargo scan alongside the entire data package, powered by AI and driven by computer vision. The automated image analysis tool compares the image against the declaration and trade data and flags anomalies with the speed and explainability the officer needs to complete an inspection. Why is this so valuable, and why does it scale? Global merchandise trade runs roughly $26 trillion per year. As a former port director early in my career at LAX, I can attest that it's a major operational challenge to balance protecting national security, collecting revenue, and keeping legitimate trade moving with downward pressure on costs and staff. This is true in every port of entry and border crossing in the world, thousands of them, each facing overwhelming volume with limited staff and resources. CargoSeer is configured to each country's own data and the officer's inspection workflow, and its models can be updated as trade patterns and risks change. The technologies we are deploying in El Salvador are garnering interest from Customs agencies around the world seeking to refine their operating models. The second product enhancement and use case is generative AI in disconnected environments. Last quarter, I shared that NASA is now a customer of our generative AI platform, Ask Sage. One of the wins we're particularly proud of in Q2 is with Naval Air Systems Command, NAVAIR, which provides full lifecycle support for all aircraft, weapons, and airborne systems used by the U.S. Navy and Marine Corps. I cannot detail the specific application of our technology, but its rapid software deployment and agentic coding capabilities are part of the use case. For customers who use our core cloud platform, two weeks ago, we expanded our offering for the entire Department of War and customers in other departments, including new air-gapped local hardware for deployments up to the top-secret level. This is a big step forward for the operator. Let me explain. Imagine an intelligence analyst in a secure facility comparing reports, searching mission data, and preparing an assessment for a commander. The information cannot leave that environment, and sometimes internet connection is removed by design. The analyst still needs the latest AI tools to organize and evaluate data, but generative AI models are typically accessed through the cloud. When an external network is unavailable or prohibited, that access disappears. Our new local device, announced two weeks ago, changes that. About the size of a hardcover book and highly portable, it brings the core capabilities of BigBear.ai's platform into locally- connected or fully air-gapped environments that are physically isolated from all unsecured networks. It is model agnostic and multimodal. The analyst can use a range of frontier AI models and process text, images, video, and more. When a connection is available, teams draw on the broad catalog of cloud-hosted models. When air-gapped, models hosted locally keep the platform running with no external network. This use case scales because our military and commercial customers can't afford service interruptions from patchy connectivity or security compromises. The operator uses the same BigBear.ai generative AI platform across connected and disconnected environments instead of adopting a separate platform for each condition. Teams retain control over where their models run, and the device can reach missions that cloud-only AI cannot serve. This expansion addresses two customer pain points, access and predictability, and directly supports the Department of War's AI acceleration strategy. We've also added new delivery options to help customers manage the cost. Customers can buy tokens through BigBear.ai or bring their own models and tokens if they have preferential pricing from Frontier Labs, and they can also white label our platform. All of these features are intended to offer maximum flexibility to our customers. The third product enhancement and use case centers on offensive and defensive drone warfare. Recently, in a series of military exercises, our ConductorOS software enabled a single soldier in the field to command multiple drones from multiple vendors running different models to clear an objective against notional enemy forces in a simulated degraded communications environment. Let's look more deeply at that use case. Today, a commander overseeing a mixed fleet of drones, sensors, and mission software from different companies must operate systems that aren't often connected and can't share data, manually moving information between them to make it relevant while piecing together a changing mission across separate interfaces. The result is that massive data volume becomes a serious cognitive burden. ConductorOS gives those systems a common way to connect and coordinate. Like a conductor leading an orchestra, it unites a mixed fleet of hardware and software through an open vendor-neutral architecture. It lets sensors and manned and autonomous platforms from different vendors share data, model, and inferences. Its reach extends beyond drone fleets, cross-sensor networks, a wide array of autonomous systems, including air defense missiles and communications interfaces. It is particularly powerful for drones, which have rapidly become integral to the modern battle space and are not yet operating autonomously across multiple manufacturers at scale. The case for scaling is clear. Soon, one operator will control large multi-vendor fleets rather than needing one operator per drone. In Ukraine, drone manufacturers have grown from seven private companies at the start of Russia's full-scale invasion to nearly 500 today, producing millions of units a year. In the 2027 defense budget request, the United States government called for more than $70 billion for drones and counter-drone systems. It's the largest ever investment in the technology. Part of this is a $54.6 billion request for an autonomous warfare unit. Today, there are more than 400 drone companies in the U.S., and BigBear.ai is positioned to help them become operationally viable at scale. One further example beyond the drone application, at the U.S. Army's Jailbreak event in Fort Carson in May, ConductorOS integrated a sensor and missile system that had never been able to communicate, showing the sensor could pass location data on an incoming target directly to the missile system for a kinetic strike. ConductorOS earned jailbroken status, meaning it had the approved interfaces and documentation needed for other systems to connect through it and operate as part of a broader interoperable network. This proves ConductorOS is on the leading edge of turning legacy system integration into a productized, repeatable capability. For operators deploying mixed fleets from multiple vendors, the need only grows as more autonomous platforms emerge. In each of these three use cases, we've advanced our technology, won new assignments, and tackled operational problems that very few companies have the experience to understand, let alone address. I'll now turn it over to Sean to go to a deeper level on our financials. Thanks, Kevin. Let's jump into our operating results for the second quarter. Revenue for the second quarter of 2026 was $36.7 million, an increase of 13% year-over-year as a result of performance from GenAI platforms and products. Gross margin was 32.8% in the second quarter of 2026, an increase of 781 basis points as compared to the second quarter of 2025. The expansion in gross margins was driven by a higher mix of revenue from GenAI platforms and products versus the comparable period. Our net loss for the second quarter of 2026 was $25.7 million as compared to a net loss of $228.6 million in the comparable period. The decrease in the net loss was primarily related to non-cash fair value changes in derivatives and a non-cash goodwill impairment charge in the second quarter of 2025 that was not repeated in the second quarter of 2026. Adjusted EBITDA for the second quarter of 2026 was - $11.6 million versus - $8.5 million in the comparable period. The decrease in Adjusted EBITDA was primarily driven by increased investment in sales and go-to-market capabilities and in research and development, both of which were partially offset by expanded gross margins, as previously mentioned. Turning to the balance sheet, our balance sheet remained strong. We finished the second quarter with total cash and investments of $410 million, which we're using to invest in new capabilities and to seek accretive M&A that can accelerate our growth strategy. We ended the second quarter with $270 million in backlogs, an increase of about $22 million from where we started the year. As Kevin mentioned, we've seen contract wins across our portfolio, which reflects the dedicated focus and execution of our team in support of our customers and their missions. Before I turn it back to Kevin for closing remarks, I wanted to share an update relating to our execution rigor. In July, we passed a significant milestone. We officially achieved Cybersecurity Maturity Model Certification, or CMMC, Level 2, well ahead of schedule. This is a rigorous U.S. federal cybersecurity standard that proves we have the advanced security controls required to protect Controlled Unclassified Information. Achieving this means we have successfully verified our defenses against sophisticated cyber threats. The Department of War shared recently that it's reviewing the standard to lower the barrier to entry for smaller companies, but the threats that drove the CMMC Level 2 requirements are still here, and this certification is valuable to all our customers and also strengthens trust with international partners. The security practices it validates demonstrate a gold-standard commitment to data privacy and infrastructure security. This is just one example of how we are, through our focus on executional rigor, maturing BigBear.ai for future growth and expansion. Now, I'll turn it back to Kevin. Thank you, Sean. For the benefit of our new investors and as a reminder to loyal shareholders, I'll underscore that BigBear.ai is investing in our strengths as a specialized defense and security technology company delivering mission-ready AI. We are focused on two core markets that are growing, national security and trade and travel, as we've outlined, and we bring together three capabilities that make us different. Deep mission understanding, an expert command of applied AI, and a unique combination of scale and agility vital for adapting and delivering as mission needs shift. Everything you heard today is evidence of that strategy in action. The accelerate program I talked about in Q1 is working. We have a realigned structure, clear growth plans, and the resources we need to grow BigBear.ai into a powerhouse. To close, I believe that as attention moves away from legacy technology to the AI capabilities where implementation is vital, not a promise for the future, BigBear.ai is positioned to win. We operate equally well as a new defense and security technology prime or as a partner to the traditional primes because we have deep customer trust and the size to deliver complex solutions or provide our targeted products and expertise within a larger contract. That flexibility puts us in a highly advantageous position. During what will be an extended transitional period for big, complex legacy businesses who need to pivot, BigBear.ai is the ideal partner, as we have already proven. I look forward to updating our shareholders on our next quarterly earnings call in November. Thank you for your interest in BigBear.ai. Thank you. This does conclude today's conference. We thank you for your participation.