Filed by Churchill Capital Corp XI pursuant to Rule 425

under the Securities Act of 1933, as amended,

and deemed filed pursuant to Rule 14a-12

under the Securities Exchange Act of 1934, as amended

Subject Company: Churchill Capital Corp XI (File No. 001-43020)

Set forth below is a transcript from a presentation by Agility Robotics, Inc. (“Agility”) in which the proposed business transaction between Churchill Capital Corp XI (“Churchill”) and Agility is discussed.

Thank you, everyone, for joining us today. My name is Anthony Rozmus, and I’m the Head of Investor Relations at Agility. We’re excited to have you join today at our Analyst & Investor Day. We appreciate you taking the time to be with us.

Before we begin, I’d like to review our forward-looking statements. The webcast of this event will be available for replay at agilityrobotics.com/investors where you’ll also be able to find a copy of today’s investor presentation.

Please note that today’s webcast may contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and are based on management’s current expectations.

These may include, without limitation, predictions, expectations, targets or estimates, including regarding our anticipated financial performance, business plans and objectives, future events and developments and actual results that could differ materially from those mentioned.

These forward-looking statements also involve substantial risks and uncertainties, some of which may be outside of our control and that could cause actual results to differ materially from those expressed or implied by such statements. These risks and uncertainties, among others, are discussed in Churchill Capital Corps filings with the SEC.

We encourage you to review these filings for a discussion of these risks, including the publicly available registration statement on Form S-4, which has not yet been declared effective. You should not place undue reliance on these forward-looking statements.

These forward-looking statements are based upon information available to Agility and Churchill Capital Corp 11 today and reflect the current views and expectations of Agility and Churchill Capital Corp 11, and we undertake no obligation to update or revise them for any new information except as required by law.

Actual results could differ materially from those contemplated by these forward-looking statements, including, but not limited to timing of development milestones, potential future customers and revenue, competitive industry outlook. And the timing and completion of our business combination.

Please refer to the presentation accompanying this webcast as well as filings and potential filings by Agility, Churchill or the combined company resulting from the proposed transaction with the SEC, including under the heading risk factors.

Turning to our agenda, here’s how we’ve built the day.

In a few minutes, Peggy will lay out the market opportunity in front of us and where Agility fits in it.

Jonathan will then take you deep into our newest robot, Digit 5 — the tech, the safety architecture, and the physical AI stack underneath it.

We’ll hear directly from Heather Lee, acting president and CEO of AUVSI, on policy and its impact on this industry, and then we’ll open it up for your first round of questions for Peggy and Jonathan.

After that Daniel will walk through our commercial strategy, market momentum and customer engagement, followed by a fireside chat with customers David Kehr and Courtney Baines from Schaeffler.

Jen will cover our operations and manufacturing strategy, and will hear from Nelson Hsieh from Foxconn. Finally, Michael will walk through the financial profile and outlook in more detail.

Then we’ll open the floor one more time for an extended Q&A with the full team.

Please feel free to step out at any point during the presentation or take a brief coffee break as needed.

We’re excited to have you with us today and to share more about the Agility story.

With that, I’d like to turn it over to Peggy Johnson, CEO of Agility.

Overview

Good morning, everyone, and thank you for being here - whether you’re joining us in person or online.

A lot of you have been covering the robotics space for a while now, asking exactly the kind of sharp, skeptical questions this industry needs — so I want to start by saying – we built today around answering those questions.

We’re meeting at a genuinely pivotal moment for robotics.

Two years ago, “humanoid robot” meant a staged demo, dancing or doing backflips. Today, it means a machine clocking real hours on a real production line, for a real customer, doing work that used to be impossible to staff.

That kind of revolutionary transition — from spectacle to shift work — doesn’t happen by accident. It’s the culmination of years of purposeful innovation designed to deliver enterprise value. Agility is at the center of this revolutionary tech, and today we’ll show you exactly why.

For those I haven’t met yet, I’m Peggy Johnson, CEO of Agility. I’m an electrical engineer by training, and if you look at my career, it’s really been one long thread: helping emerging tech find its first real home inside the enterprise.

I spent twenty-five years at Qualcomm, with a front-row seat to the commercialization of the mobile phone — antennas, cell sites, and eventually the semiconductors that scaled the global smartphone industry we have today.

Then in 2014, I received a call from Satya Nadella shortly after he became the CEO of Microsoft. He asked me to lead business development there, across all of their h/w and s/w products, helping to bring early tech to market.

And in 2020, I stepped in as CEO of Magic Leap, where I took a company built for consumers and re-directed it to focus on solving enterprise problems, because that’s where the tech actually had a job to do.

I tell you all of that because it’s why I’m standing here today.

After decades of driving large enterprises to adopt new tech, I’ve learned one thing above everything else: companies don’t buy tech — they buy solutions to their problems.

Let me tell you about Agility. We are headquartered in Salem, Oregon, with teams in Pittsburgh and Fremont, CA and our mission is simple: build robot partners that augment the human workforce.

Digit is the result — the first multi-purpose humanoid that’s actually commercially deployed and working today. Our focus on getting our robots into the operations of paying customers and outside the lab distinguishes us from other humanoid companies.

When I met Jonathan Hurst, our co-founder, and the Agility team 2-½ years ago, what attracted me wasn’t a robot doing a backflip.

This team had already done the unglamorous work of figuring out how to build capable hardware that was actually useful. What they’d found along the way was product market fit. They’d built a solution to an industry-wide problem - solving the growing manual labor gap.

What the company needed was an experienced team to scale this solution. That’s the job I signed up for.

Let me now introduce the people on our leadership team helping to make this vision a reality - you’ll be hearing from many of them today.

Jonathan Hurst is our co-founder and Chief Robot Officer. Everything about Digit’s physical design traces back to Jonathan and his vision for building a truly useful machine.

Michael Beer, our Chief Financial Officer, who many of you know from his time at Citibank or at Energy Vault. Having led similar transactions to Agility’s, he brings us an invaluable depth of financial experience.

Daniel Diez, our Chief Business Officer, leads our commercial engine. He, too, has a successful track record of bringing transformational tech to market and was with me at Magic Leap.

Jen Hunter, our Chief Operating Officer, brings a decade of experience from inside Amazon’s robotics organization and now runs the operations behind scaling our business.

Pras Velagapudi, our Chief Technology Officer, has both a decade in academia and a decade working in the robotics industry, bringing real-world expertise to Digit’s autonomous capabilities and physical AI stack.

Ana Lang, our Chief Legal and People Officer, whose long career of guiding innovative tech companies through complex legal and organizational challenges makes her the perfect person to steer these functions at Agility now.

And finally, Marco Marroquin, our Chief Hardware Officer who has led hardware teams on the frontier of autonomy in roles at Tonal, Lyft, and GoPro.

Together, this team combines more than fifty years of robotics experience and more than eighty years scaling commercial tech into the enterprise.

Lastly, I’d like to highlight the tremendously talented directors joining our public company board - Merline Saintil, Derek Aberle and Pierre Gentin.

The new directors will serve alongside our co-founder Damion Shelton and myself - in addition to representatives from Churchill.

Merline, Derek and Pierre have helped lead some of the world’s most consequential tech businesses and institutions. Their collective experience, together with Damion’s deep roots at Agility, will be instrumental as we work to make humanoid robotics an integral part of the global workforce.

And that’s going to happen - humanoids will transform labor.

The pace of innovation in robotics is moving at an unprecedented rate. Tech that previously only had a home in research labs is now at the center of unlocking real commercial opportunity.

We believe the reason humanoid robotics is having its moment right now, in 2026, and not five years ago or five years from now is due to the evolution of AI — the real world perception, reasoning, and planning has gotten good enough, and fast enough, to give every robotics company real intelligence - almost overnight.

That’s a rising tide lifting every serious company in this category.

But a robot knowing what to do isn’t the same as being able to do it, reliably, thousands of times a day, on a factory floor.

That’s physical AI: the far more complex problem of turning intention into safe, repeatable, physical actions by the robot. That data, by the way, doesn’t exist anywhere yet - there is no vast stored internet of robot movements. It has to be earned, one use case at a time, and Agility has spent years gathering it through real world deployments.

This tech, BTW, isn’t arriving into a market that’s indifferent to it. It’s arriving into a labor market that is genuinely running out of people.

In 2025, there were over 400,000 unfilled manufacturing positions in the United States. On current trends, that number is projected to grow more than four and a half times, to nearly 2 million unfilled jobs by 2033.

This isn’t a cyclical dip that corrects itself — it’s a structural shift. An aging workforce is retiring out of these roles faster than young people are choosing to enter them. At the same time, the U.S. is working to reshore manufacturing capacity.

The opportunity here is to fill those roles businesses struggle to staff today.

The jobs Digit takes on first are the dull, dirty, and dangerous ones — things like repetitive material handling - manual tasks with high injury rates and high turnover.

As Digit steps in, the people who were doing those jobs are able to move into higher-value roles: supervising fleets, maintaining the tech, running the facility. This is additive to the workforce — because the alternative is a continuously understaffed one.

So how big is this labor problem? While TAM estimates range broadly depending on various sources, we believe that the near-term total addressable market for humanoids across manufacturing, distribution and logistics environments in the United States will be approximately $1.25 trillion by 2032.

We sized our near-term addressable market around the three industries where this labor gap is most acute and most immediate: manufacturing, distribution, and logistics.

These are markets that share the same characteristics. They have large labor pools, very structured and repeatable workflows, and existing fixed infrastructure built around the walkways where their workforce operates.

That last point matters enormously: Digit doesn’t require a customer to redesign their facility to deploy. We fit into the aisles, doorways, and workstations that already exist.

As Digit’s capabilities expand with each new generation — more dexterity, more skills — the addressable footprint expands with it. From bins and tote handling today, toward machine tending, kitting, quality inspection, and then into new verticals altogether including, over time, environments like retail, healthcare and eventually even the home.

We’re sizing this business around the demands of a growing labor gap and we’re building the roadmap to meet those demands.

Now, you will have likely observed there is no shortage of humanoid robots dancing on stages. There is, however, a shortage of humanoid robots on the payroll.

Our currently available robot, Digit 4, is the humanoid with the longest continuous commercial track record in the industry — over two years of live deployment, more than 65,000 hours of real operational time, and work at customer sites like GXO, Schaeffler, and Toyota Motor Manufacturing Canada.

That track record compounds in two ways. First, commercially: it’s why we’ve been able to secure $300 million in multi-year orders for Digit 5, subject to the satisfaction of certain contractual milestones, product features and specifications. We anticipate Digit 5 will be available to early adopters in the first half of 2027 and generally available by the end of 2027.

Second, technically: every one of those 65,000-plus hours of Digit 4 work generates operational data that no competitor with just months of deployment has access to.

That data becomes a flywheel — it improves our physical AI, which unlocks new skills, which unlocks new workflows and new customers.

That generates more deployments and more data. We believe this real world data flywheel is very difficult to shortcut, and it is the core of our advantage.

We’ve also made a deliberate choice to govern in-house the parts of this business that can be the hardest to control: we design and assemble Digit ourselves, at RoboFab, our own purpose-built facility in Salem, Oregon, with capacity to scale to 10,000 units a year.

Our approach to the tech, to customer deployments, and to the supporting infrastructure is why some of the most important strategic players in this ecosystem have backed us along the way — such as NVIDIA, Amazon, SoftBank, Schaeffler, ABICO Group, and Foxconn — who is anchoring our PIPE.

It’s worth being precise about what we’re actually building, because Agility is not a single product company.

At the center is Digit — our general-purpose humanoid, and today’s Digit 4 is the version that’s been earning its reputation in the field for over two years.

In the first part of 2027, we plan to make our next generation robot, Digit 5, available for early access. We believe that commercial availability of Digit 5 will be a true product inflection point, and not just a product iteration. I’ll go into why in just a bit.

Around the robot sits Agility Arc, our cloud fleet-management platform. Arc is what lets a customer run multiple Digits as a coordinated fleet - connecting into their existing warehouse management systems, tracking metrics like uptime and throughput, and giving us the operational visibility we need across every deployment.

We also provide the services layer our customers need to run this in live production — deployment, maintenance, and ongoing support, whether a customer adopts Digit through our Robots-as-a-Service model or purchases it outright.

We see a real revenue opportunity beyond just Digit sales through licensing of our proprietary hardware tech into the broader robotics industry. We’ve spent a decade building that tech and it’s valuable well beyond our own robot. We plan to capture that value as a new, high-margin revenue stream over time.

This is why we believe now is the right time to go public — not just because the market is demanding humanoid solutions, but because our technology and operations are ready to support that demand, and we’re bringing a large, growing order book with us.

OK, let’s talk about our new robot, Digit 5

Every humanoid in this industry, including our own Digit 4, has been boxed inside a fenced work cell — today’s safety standards were written for machines that don’t dynamically balance and move about on their own, so this is a new category of risk the existing frameworks weren’t built to underwrite.

Digit 5 is our first humanoid designed to work near people.

At general availability, Digit 5 will combine AI-based human detection, safety cues, and an independent safety controller that can stop or power the robot down before any human contact.

Digit 5 will also deliver on the hardware upgrades customers have asked for: more payload, an ultra-fast charging battery and swappable hands to equip Digit 5 with the flexibility to take on more kinds of work.

Here’s why that matters: once a robot can be trusted to move through a facility full of people, every new skill it learns adds value across the whole operation, not just one fenced off task.

That’s what turns Digit from a robot that does one thing well into a platform that can absorb a customer’s entire workflow — and why Digit 5 will be an inflection point for fulfilling labor gaps.

That’s the opportunity, and it’s why we believe Agility’s Digit 5 will capture it.

None of it works, though, without the tech underneath actually delivering real value. There’s no one better to take you through that than the person who’s spent his career on exactly this problem.

Please join me in welcoming Agility’s co-founder and Chief Robot Officer, Jonathan Hurst.

Technology & Digit 5 Overview

Thank you, Peggy. Good morning, everyone.

Peggy just walked you through why this market exists and why we think Agility is built to win it.

My job for the next few minutes is to go one level deeper — into the robot itself, the AI underneath it, and the safety architecture that we believe is the gating factor for this entire industry.

My career-long mission has been to build machines that interact with the physical world the way humans and animals do, differently from the rigid position control of historical robots and automation. For a long time, that was a basic science problem, and it lived at a university lab.

Through my graduate work at Carnegie Mellon and later as a professor at Oregon State, we made real progress on the core science of dynamic balance and physical interaction. But at some point, the blockers stopped being scientific and started being about finding applications, creating a product, and building an engineering organization — things universities aren’t built to do.

That’s when we founded Agility.

We’ve brought four of our robots: Cassie, and three generations of Digit. Each one marks a distinct stage in how we got here.

The first was an R&D era, built around our first robot, Cassie.

This is where we solved core engineering problems like our first cycloidal actuator design – technology that gave us force control and exceptional durability even with repeated ground impacts during walking and running that nothing else on the market could match.

We sold Cassie to research programs at Berkeley, Michigan, Caltech, Georgia Tech, and others, as the only bipedal robot on the market capable of biomechanically relevant movement.

And, this is when we began our investigations into what is now called physical AI, before it was popular. You can see that Cassie moves like a thing alive, in these early experiments.

The second stage was proof of concept. This is Digit 3, and this is the platform we used to test hundreds of potential use cases to find where this technology actually creates value.

That’s how we landed on tote and bin handling as our beachhead — structured enough to automate, but different enough at every customer site that single-purpose automation can’t solve it.

That work led directly to our third stage with Digit 4: Commercial deployment. Our first commercial deployment with GXO is the first time a humanoid robot has worked in a customer’s workflow getting paid for it.

This is the exact platform that’s still out there at companies like GXO, Schaeffler, and Toyota, racking up the operational hours you’ve heard about this morning.

Now I want to make an important point about why we are building a humanoid robot. We did not set out to build a machine that looks like a person. We build robots that can do many things in human spaces - and in designing the hardware, we started from first principles of physics and engineering — we’re building out of motors and metal, not muscle and bone — and let the design follow the requirements.

It ends up looking humanoid because the requirements point that way.

To work in aisles, doorways, and narrow human spaces while lifting something off a shelf two meters up, the robot has to be tall and narrow rather than wide and squat — which means it can’t be statically stable, it has to actively balance, the way we do on two legs.

You might think we can balance on wheels - and we can. But if you’ve ever been pushed while standing on a Segway versus standing on your own two feet, you know which one recovers better — and that intuition holds up under the physics.

Legs are the right solution for dynamic balance.

An upright torso lets it lean and balance in the direction it’s moving, and gives us room to mount arms, sensors, batteries, and compute up high, where they need to be to see and reach a human workspace, and still be able to turn in place.

Two arms — rather than one large one — let it lift bigger objects, like totes and bins, and reposition things in-hand by swapping between them. It’s a core advantage for this form, the ability to move very large objects relative to the size of the robot.

And once you have two arms, two legs, and an upright torso, people expect a face — somewhere to read what the robot is about to do, the same cues you’d read off a coworker, communicated on human terms. We built just enough expression into Digit’s head to meet that expectation, without chasing realism into the uncanny valley.

And that brings us to our newest robot, Digit 5, and the fourth stage we’re in now: scaling.

The single biggest blocker standing between where we are today and thousands of robots deployed across hundreds of facilities - or even homes - is not intelligence, and it’s not dexterity.

It’s not the ability to walk up stairs or fold a fitted sheet.

It’s safety.

Digit 5 is purposely designed to safely operate in close proximity to people. But this has been a major engineering effort, because

Digit is a genuinely new class of machine: As a humanoid robot it’s dynamically stable, which means, unlike a stationary robot arm, it can fall.

That is a category of risk the existing regulatory and insurance frameworks have not anticipated. Until it’s addressed, every humanoid — regardless of how capable it is — has to operate inside a fenced work cell, requiring installed infrastructure, and disconnected from the rest of the facility and the people in it.

Creating a cooperatively safe humanoid robot is a holistic, bottom-to-top design exercise — it touches nearly every system on the machine, influencing the shape of the limbs and the body, requiring dedicated computing and sensor arrays, providing hard requirements for the entire electrical system. We’ve spent years inventing the strategies, building the engineering best practices, and working with partners like NVIDIA to bring a solution forward.

Digit 4 became the first humanoid to pass a field evaluation from an OSHA-recognized, independent testing lab — on an active customer production line.

Digit 5 builds directly on that work and, when generally available, will be the first humanoid robot capable of safely operating in close proximity to people.

Digit 5 will combine AI-based human detection that continuously distinguishes a person from, say, a statue of a person and tracks how someone is approaching.

It will provide safety cues so people around the robot can intuitively understand what it’s about to do and it’s built with certifiably safe motion control, so the robot can slow, stop, set its payload down, or power off before a person could physically make contact with it.

Of course, as with any responsible AI-based technology, you don’t let the guardrails down right away. It is not all-or-nothing. It is a gradual improvement of safety features with deployed proof points.

Autonomous vehicle companies didn’t go straight from a research vehicle to a driverless one — they used safety drivers for years, collecting exactly the data needed to earn full autonomy safely, over increasingly complex environments, one validated step at a time.

That’s how we think about cooperative safety. It’s our first step towards working side-by-side with humans, and the mechanism by which we collect the data to responsibly expand what Digit is trusted to do next.

It’s the unlock that matters most for customers: once a robot can be trusted to move through a facility full of people, every new skill it learns adds value across an entire operation.

That’s what turns Digit from a robot that does one thing well into a platform that can absorb full facility workflows.

We’re also not building every layer of that safety stack alone. Agility is the first company to build NVIDIA’s new Halos for Robotics into its safety system, integrating NVIDIA’s IGX Thor compute and Halos Core software into Digit’s human-detection system, and we’re using NVIDIA’s own accredited inspection lab to prepare for third-party safety certification. That gets us a validated, industry-grade safety foundation underneath our own system.

Along with cooperative safety, our early deployments gave us more insight into customer requirements to scale this technology. These are requirements that apply not just to Digit, they apply to any humanoid if it is to be successful in industrial settings.

The robot must have a battery that allows it to work across a factory’s 3 shifts a day, and do so reliably.

On Digit 4, that answer was gated by roughly a two-to-one run-to-charge ratio — for every two hours of work, the robot needed about an hour on the charger. Across two or three shifts a day, that’s real downtime, and real coordination overhead for a facility trying to run continuously.

We looked hard at swappable batteries as the fix, and passed — the same way cell phones and electric vehicles largely did. Swapping means extra mechanical complexity, a human or another machine in the loop, and spare packs to inventory and maintain as a hazardous material.

Digit 5 will solve the problem with a new fast-charge battery system, a 90-minute runtime pack that recharges in under nine minutes. That gives us a ten-to-one work-to-charge ratio, which works out to more than 20 hours of productive work in a 24-hour day.

It’s a good example of what I’d call an unglamorous upgrade that moves deployments to scale.

Digit must be able to lift heavy loads over and over again, up to the amount that’s recommended in OSHA-regulated facilities.

Our cycloidal actuators match the strength needed while also achieving 95 to 96 percent efficiency, which gives us force control that nothing else on the market matches for this use case. And Ten years in, they are essentially indestructible — We have observed no meaningful wear even in this punishing application.

Digit must be cost effective to the point where it becomes economically compelling to customers compared to a fully-burdened labor cost.

We’re on a path that ensures the necessary performance, while being on the path to low-cost manufacturing, with common processes like machining and casting aluminum, thermoforming and injection-molding plastics, and shaping and bonding sheet metal. There is no exotic manufacturing technology needed for Digit.

Finally, it needs to offer the flexibility of general purpose automation.

Our function-first humanoid form helps with this, because it can do so many of the workflows that were designed around humans; but we also have the advantage of changing hands for different tasks.

Our tool-change system makes it easy to use our in-house manipulators that can lift 50-pound bins — something nothing off the shelf can do — while still swapping to different tooling for other tasks, like machine tending, and kitting and sequencing.

Of course, AI unlocks the generality of our hardware. New AI approaches to robot behavior and control means that it can learn new skills with less engineering development time, and be deployed across a facility to perform work where it’s needed most.

When people talk about AI in robotics right now, they’re usually talking about one thing: semantic AI. That’s perception and reasoning — the same family of models behind tools like Google’s Gemini or Anthropic’s Claude — and it lets Digit see what’s in an environment and understand it.

That layer has gotten extraordinarily capable extraordinarily fast, because it’s trained on the entire internet. It’s a rising tide, and it lifts every serious robotics company, including us.

But there is no internet-scale dataset for how to control the motors of a bipedal robot. That data doesn’t exist anywhere — it has to be created. That’s physical AI: the layer that turns intention into safe, repeatable, physical action. It’s the harder problem, it’s far more specific to our hardware, and it’s the one Agility creates and owns in-house.

We build that layer in two steps. First, learning from demonstration — teleoperation, motion capture, even computer animation — gives the robot a strong starting point for a skill: how to grasp this, how to walk over there.

Then reinforcement learning in simulation lets the robot practice and refine that behavior on its own, because Digit’s body doesn’t move exactly like a person’s, so it has to find its own version of the movement.

Over time, this extends into reinforcement learning in the real world, across fleets of robots, all coordinated and fed back through our fleet platform, Arc.

That’s the flywheel Peggy mentioned: every deployed hour generates data that allows us to improve the physical AI. The quality of the data matters - the robot must learn from relevant experience, which can only be gained on the job. That flywheel compounds, and it’s very hard to shortcut by starting later.

Because we are focusing on the quality of data for relevant use cases, it also means we don’t need to make the enormous compute bets some of our competitors are making, with no guarantee it gets them to a working robot any faster. We think that makes us both more data-efficient and more capital-efficient.

We have so far been discussing individual robots - but to deploy thousands, they must coordinate together. Arc is our cloud fleet-management platform — the layer you don’t see, but that does a lot of the work.

It coordinates robots across a facility, integrates with the other automation already running there, and gives us real-time health and diagnostics on every unit.

It’s also core to our data collection: every one of those signals feeds the same physical AI flywheel I just described.

Over time, we see Arc as a meaningful product in its own right, not just plumbing underneath the robot.

This brings me back to one more point about safety. I’ve walked you through safety, the hardware upgrades, the physical AI, and Arc on purpose, in that order, because safety isn’t a separate topic from any of it.

You can’t bolt safety onto a humanoid at the end, or layer it on top of a finished machine — it has to be built into the hardware, the AI, and the fleet software all the way through.

One more thing before I hand this off. Digit 5 is a platform that is designed to be upgraded. With every generation, we will retire subsystems for better ones: actuators, batteries, manipulators, sensors.

That continuous upgrade path is how Digit stays useful for years in the field, and it’s how we get to whatever comes next.

Zoom out far enough, and the destination isn’t a warehouse — it’s robots that will be genuinely part of everyday life: helping in homes, working in stores, moving a package the last few feet from an autonomous delivery vehicle to your door.

That big picture is Agility’s vision, and we believe Digit 5 is simply the next real step toward it.

This is an incredibly exciting time for the field of robotics — our continued technology breakthroughs and commercial success depends on policy keeping pace with what we’re building, and on the people writing our laws being part of this conversation from the start.

So I want to hand things over for a different kind of discussion. Please join me in welcoming Heather Lee, Acting President and CEO of the Association for Uncrewed Vehicle Systems International, or AUVSI, who’ll join Peggy for a conversation on the policy landscape shaping this industry

Policy Q&A with AUVSI’s Heather Lee

It’s a pleasure to welcome you, Heather. Thank you for joining us.

AUVSI is the world’s largest trade association representing the uncrewed systems, robotics, and autonomous technologies industry, and has become the voice in Washington on the policies that will shape the future of robotics and autonomy. More recently, the organization has broadened that leadership across advanced robotics and physical AI, bringing together industry and policymakers around issues ranging from national competitiveness and supply-chain security to federal procurement, workforce development, and the need for a coordinated national robotics strategy.

Heather is the Acting President & CEO. At AUVSI, she has held senior strategy and operational leadership roles and today oversees engagement, industry development, strategic programs, meetings, finance, and administration. She brings a particularly interesting perspective to this conversation, as prior to AUVSI she spent nearly two decades at CTIA, the trade association representing the U.S. wireless industry.

Heather has been at the center of much of AUVSI’s ongoing work, and I’m delighted to have her with us today to talk about where robotics policy is headed and what it means for the industry.

Heather, we are excited to have you join us today.

Question 1: The Policy Landscape

AUVSI has been at the forefront of the robotics policy discussion, and from Agility’s perspective, that conversation has evolved remarkably quickly over just the past year.

Can you give us a sense of what has changed and walk us through some of the key robotics initiatives that Congress and the Administration are working on right now?

Question 2: U.S.-China Competition

One of the forces clearly shaping this discussion is the geopolitical and economic competition between the United States and China. We’re increasingly seeing robotics discussed not simply as an emerging technology, but in the context of supply-chain security, domestic manufacturing, economic competitiveness, and national security.

How significant has the U.S.-China dynamic become in shaping robotics policy, and do you expect it to remain a major catalyst?

Question 3: Federal Procurement and National Security

AUVSI was instrumental in encouraging policymakers to use federal procurement to help build and scale the domestic drone industry, especially with DoW’s Drone Dominance program. And just last week, I was selected to be part of DoW’s Project Meridian, which was stood up to support the development of a study to address the Future of Warfare, including adjustments or transformations in DoW’s approach to warfare to maximize U.S. warfighting advantage over time.

Do you see similar procurement opportunities emerging for advanced robotics? And specifically, do you think we’ll see the federal government, and perhaps the national security community in particular, begin using procurement more deliberately to accelerate the adoption and scaling of American-made robotic systems?

Question 4: Bipartisanship and the Next Congress

Finally, we have a mid-term election approaching, and there is naturally a lot of discussion about what the political landscape in DC could look like next year, including the possibility of a divided government.

From where you sit, how durable is the bipartisan consensus around robotics? Regardless of which party controls Congress, is there enough alignment around the economic and national-security importance of robotics for this agenda to continue moving forward?

Closing

Heather, thank you. This is clearly an important moment for the robotics industry, and I think your comments underscore both the opportunity in front of us and the importance of industry and government working together as this technology moves toward much broader adoption.

For our first Q&A session today, let’s focus on the topics just presented by Peggy and Jonathan.

We have a few handheld microphones in the room so if you have a question, please raise your hand and I’ll call on you. Then, one of our team members will hand you the mic.

Remember to introduce yourself and your company, and please limit yourself to one question and a short followup if needed.

Thank you Peggy and Jonathan. We’ll have the full leadership team available at the end of the day. Next up I’d like to introduce Daniel Diez, Agility’s Chief Business Officer.

Commercial Momentum and Customer Engagement

My job is to help you understand how our strategy is being executed on the ground. I’m going to talk about who is actually deploying Digit today, what they’re using it for, and how that translates into the orders and pipeline behind the numbers you’ll see later from Michael.

We have deliberately chosen a core use case and three verticals as our beachhead markets: manufacturing, distribution, and logistics.

We’ve chosen these industries because they share some critical traits.

As you heard from Peggy earlier, they have large labor pools, are under constant hiring pressure, and the cost of labor is increasing, thanks to inflation and a tightening labor market.

Automation, and humanoids specifically, can offer relief for the expanding labor gap and can help increase productivity as established economies look to increase onshore manufacturing.

These industries are also built around facilities with structured environments that let us repeat common tasks from deployments across customers and verticals without reinventing the robot’s skills every time.

They also provide an environment where cooperatively safe robots can operate outside of safety fences or walled off workcells.

And critically, these are facilities already built for people to work in, so we’re not asking a customer to redesign their operation around us, like you might see with other forms of automation.

And so it is an incredible opportunity in the near term for us to deploy humanoids in these facilities to take on these tasks that have been difficult to recruit for.

Let me spend a few minutes on our commercial traction, because this is the part of the story that I think separates Agility from a lot of what you’re seeing in this industry right now.

Today, we have deployment commitments across nine customer facilities, and more than 65,000 hours of real operational time with Digit 4 on the clock.

As we sit here today Digit is running in environments where safety can’t slip and downtime isn’t an option.

And we’ve had recent wins with global leaders in new manufacturing and consumer brands as well, expanding our footprint beyond where we started.

When you ask customers why they chose to expand with us instead of just running a pilot, it comes down to five things: safety, accuracy, uptime, throughput, and ROI.

Let me put some numbers behind a couple of those.

At GXO’s facility near Atlanta, Digit 4 has handled more than 100,000 totes at roughly 98 percent accuracy.

At Schaeffler’s Cheraw, South Carolina facility, Digit has been moving totes of automotive bearing components onto a line for washing — handling well over a million pounds of material in the process.

Every one of those deployments comes back to the same pitch, and it’s not a technology pitch — it’s an economic one.

Our agreement with customers is that the job gets done according to the success metrics we set when we enter into a commercial agreement. Digit is there to work.

Customers can adopt Digit one of two ways. Under Robots-as-a-Service - or Raas - they pay a price set at a discount to their own fully burdened human labor rate.

That means the ROI conversation isn’t hypothetical or five years out — the customer sees value from day one of operation, because the economics beat a labor cost they’re already paying, for work they often can’t find people to do in the first place.

Under our ownership model, the customer purchases Digit 5 outright, and on that path we deliver a breakeven ROI in just 1.1 years.

In either model, Digit becomes more economically compelling as more skills are learned. The robot provides relief from turnover, the tax of new employee training, and loss of efficiency when shifts go unstaffed.

The unit economics should improve even more when customers deploy Digit over 3 shifts of operation, something Digit 5 has been designed to do.

Either path has the potential to deliver real, measurable savings against a customer’s existing labor spend, and that’s deliberate — we’ve built our pricing on conservative assumptions, so this case is designed to hold up even before you factor in the cost curve Jen will walk you through, or any of the pricing optimization we expect as customers experience the value themselves.

That economic case is only half the picture — the other half is why this business model compounds in our favor as well as the customer’s.

RaaS and ownership aren’t just two ways to price a sale; they’re two different revenue profiles.

Under our current, deliberately conservative assumptions, a single Digit deployment generates on the order of $500,000 of cumulative revenue to Agility over its five-year useful life under RaaS — recognized steadily, in a highly recurring pattern, over that whole life.

Under ownership, a single deployment generates roughly $400,000 over the same five years, but the profile is different: a larger portion of that revenue lands upfront at the time of sale, with recurring software and service revenue building on top of it from there.

Today, we anticipate that the majority of our $300 million in committed Digit 5 orders will be structured as RaaS (contingent on meeting certain contractual and technology milestones), and that’s not an accident — it’s the lowest-friction way for a customer early in their automation journey to say yes, because it reduces their upfront capital requirement and de-risks the decision.

But RaaS is at least as attractive to us as it is to the customer: it builds a recurring revenue stream, a growing installed base of robots in the field, and — because a customer’s operations come to depend on that robot being there every shift — very strong retention.

Over time, as humanoids become a normal line item in a customer’s capital planning process rather than an investment on new technology, we expect a natural migration toward ownership, which brings a larger upfront revenue recognition while we retain the recurring Arc and services attached on top.

Here’s how that becomes a flywheel rather than just a sales model.

Every RaaS dollar will also deliver valuable data — because every deployed hour under contract is an hour of real operational data flowing back through Arc, improving our physical AI, and unlocking the next skill or workflow we can sell into that same customer’s site, or the next one like it.

At the same time, a growing, recurring revenue base funds the manufacturing scale that drives our bill-of-materials down — Jen will share the details on this next.

Lower unit cost expands our margin, which we believe could exceed 70 percent as the business matures, and margin expansion funds faster deployment, further cost reduction, and a more aggressive commercial motion — which brings in the next round of customers and the next round of recurring revenue. Recurring revenue funds the data and cost curve, and the data and cost curve fund the next round of recurring revenue.

That loop is the flywheel, and it’s why we think this model gets more efficient, not less, as it scales — the opposite of most industrial hardware businesses.

We move customers through this with our Customer Acceleration Program: a proof of technology, an onsite proof of concept, and a three-month pilot under our RaaS model.

We’re selective about who we admit into that program — many of the enterprise customers that we engage with have use cases that can support at least 50 robots, which on our RaaS model works out to a minimum opportunity of $25 million over the robot’s five-year useful life, 50 units times $100,000 a year times five years. That scale matters, because it means we’re spending our own time and engineering effort on opportunities that can actually move the needle.

Customers can then scale that same engagement into broader RaaS deployment as Digit 5 becomes more widely available by the end of 2027.

And when a customer actually signs one of these commitments, it tells you something beyond the dollar figure: it means we’ve earned buy-in not just from their tech and R&D teams, but from the business units actually running the operation — because by that point, there’s already proven value on the floor, not just a promising pilot result on paper. I

t’s built for one specific kind of customer: one that can point to a real labor shortage and has the appetite to scale a humanoid deployment in the near term.

This is exactly the kind of proof that gave one of our most experienced Digit 4 customers the confidence to commit to $300 million in Digit 5 orders. That’s a three-year Robots-as-a-Service agreement covering 1,000 Digit 5 robots.

This customer has been running Digit in a live production environment for years now, handling real material-handling work, shift after shift. When a customer with that much hands-on experience with Digit decides to go deeper, that’s a stronger signal that there’s a real market for Digit to scale production work.

Their decision to expand is informed by what they’ve already seen Digit do on their own production floor, and they see Digit 5’s new safety capabilities — the ability to work in closer proximity to people — as the unlock for taking humanoid robotics further across their operations. Under this agreement, this customer plans to expand Digit 5 across multiple facilities, moving beyond material handling into a broader set of workflows.

What you should take away from this announcement isn’t just the number, although $300 million is a meaningful one. It’s that one of our most experienced customers — the one with the most real-world hours on Digit anywhere in the world and arguably one of the most experienced deploying all humanoids— chose to expand with Agility. That’s exactly the kind of proof point this business should be judged on.

We announced a new partnership with FORT Robotics last week to further enhance Digit 5’s safety infrastructure, and I’d like to go into more details as it matters commercially as much as it does technically.

We’re jointly developing a solution that will extend our cooperative-safety approach beyond the robot itself and connect Digit 5’s planned onboard safety architecture to an offboard system that provides off-robot human detection and a stop-command infrastructure in the facility around it.

In practice, that will give customers a second, independent layer of protection, and continuity of safety coverage as a deployment grows from one robot to a fleet. With every added layer Digit 5’s safety system becomes more resilient — so the robot can be trusted in a more diverse set of environments.

Why does this belong in a commercial update and not just a technical one?

Because in nearly every sales conversation we have, the safety question is the long pole in the tent — it’s what a customer’s Environment, Health, and Safety and insurance teams need answered before they’ll sign anything.

A formalized, independently built safety architecture, that is backed by a company trusted across warehousing, manufacturing, and defense, will shorten that conversation. It’s a direct input into how fast we will be able to move deployments from pilot to scale.

Put together, this is what our commercial pipeline looks like after Digit 5’s planned launch in 2027: more than $300 million in committed, multi-year customer orders for Digit 5 subject to the satisfaction of certain contractual milestones, product features and specifications, structured under our RaaS model with a qualified with a potential commercial pipeline that’s a multiple of that figure.

And as Digit 5’s safety architecture matures with partners like NVIDIA and FORT, we expect that pipeline to convert faster.

Q&A with Schaeffler

Our next two guests come from a company that knows humanoids from both sides: it builds the parts that go into them, and it puts them to work.

Schaeffler is a German motion technology company with 80 years of history, around 110,000 employees and more than 250 locations in 55 countries.

It is one of the world’s largest family-owned companies, and its bearings, actuators and drive systems are in vehicles and industrial machinery around the world. Schaeffler is now applying that manufacturing expertise to humanoid robotics, and estimates that its portfolio can cover roughly half the bill of materials of a typical humanoid.

Schaeffler is also our investor and our customer. In 2024 the company invested in Agility and agreed to begin deploying Digit for use across its global plant network, and Digit is now at work in Schaeffler’s plant in Cheraw, South Carolina.

Dave Kehr is President of Humanoid Robotics at Schaeffler, where he leads the development and industrialization of motion technology for the humanoid sector, drawing on more than two decades in automotive engineering and manufacturing.

Courtney Baines is an advanced production technology engineer and Schaeffler’s subject matter expert on Agility, working directly on how Digit is used in its plants.

Between them, they can tell you what it takes to scale the humanoid supply chain and what it takes to run a humanoid on a factory floor. Please join me in welcoming Dave Kehr and Courtney Baines.

David: Schaeffler has been one of the earliest companies anywhere willing to put a humanoid on a live production line. What’s your vision for the role humanoids will play across your operations long-term, and why did Schaeffler want to be out in front of that, rather than waiting to see how it played out for someone else?

Courtney: You have real experience deploying Digit. Take us back to the beginning — what led Schaeffler to bring Digit into your Cheraw, South Carolina facility, and what gave you the confidence to deploy Digit into a real part of the operation?

Courtney: As you think about expanding humanoid robotics further across your operations, what actually has to be true — on the technology side, on safety, and in terms of the operational metrics you track — to scale the technology?

David: Schaeffler’s spent decades as a leader in motion technology and bearing systems. How are you thinking about Schaeffler’s own role as a supplier into this emerging humanoid market, not just as a customer of the finished robot?

David: Given everything Schaeffler already knows about motion technology, what do you think you’re uniquely positioned to bring to this industry as it matures?

Thank you David and Courtney for that conversation. I’ll leave it there on the commercial side. Now let’s go behind the curtain a bit, into how we actually build and support all of this at scale. Please join me in welcoming our Chief Operating Officer, Jennifer Hunter.

Thanks, Daniel, and thank you to David and Courtney for that conversation — it’s one thing to hear us describe demand, it’s another to hear it from the customer’s side.

My job is to answer the question that naturally follows all of that: can we actually build enough product, fast enough, to keep up with market demand?

I spent a decade inside Amazon’s operations organization before joining Agility, and if there’s one lesson that experience left me with, it’s that the hardest part of robotics at scale is rarely the robot — it’s everything around it. So let’s walk through what we’ve built.

RoboFab is the foundation. It’s the world’s first purpose-built humanoid assembly facility, located in Salem, Oregon. We stood it up in 2023, designed from day one to produce humanoid robots rather than retrofitting an existing production facility. RoboFab uses a modular architecture that lets us scale output as demand grows, with the ability to support production of up to 10,000 robots annually without a large incremental capital outlay.

One detail I’d point to: many of our engineers sit on the factory floor, next to the people building the robots, not in a separate building. That creates a tight feedback loop between design, manufacturing, and what we’re learning from deployed fleets, and it’s a meaningful reason we’ve been able to iterate as fast as we have.

We don’t manufacture or design all of our components ourselves, and we don’t outsource everything either — we’ve been deliberate about where we add inherent value and differentiation. We design and produce the systems that are hardest to replicate and matter most to performance in house, starting with our actuators, which represent the largest portion of Digit’s bill of materials and are the single biggest driver of the cost curve.

For components that are more standardized we lean on manufacturing partners who can bring scale we’d otherwise spend years building ourselves. This approach gives us control over the parts of the product that actually differentiate us, while keeping the business capital-efficient as we grow.

On the supply side, we have developed a Supply Chain roadmap which optimizes for quality, lead times, and cost- sourcing domestically wherever feasible. That’s a deliberate choice — it gives us tighter quality control and a supply chain that’s far less exposed to the geopolitical uncertainty this industry is watching closely right now.

A critical question we get is whether our product quality holds up as volume ramps — and the honest answer is that we treat this as an engineering discipline, not an afterthought. This begins upstream with our strategic suppliers- we qualify, audit and provide real time feedback to those partners to ensure every inbound component meets our requirements from both a specification and quality perspective. In addition, every Digit unit we produce goes through rigorous and standardized testing before it leaves RoboFab, and because our engineering and manufacturing teams sit side by side, issues get caught and corrected at the design level, not just remediated on the line.

Our discipline around Quality and Reliability also extends to each of our customer sites. In order to further minimize down time for our customers- we service our customer units with the support of third party field service partnerships as a first line of defense, allowing us to minimize customer downtime and scale quickly across all of our deployments.

The design of Digit easily facilitates this as we design our product in a way that allows for quick repair in the field- snapping on and off our field replaceable units such as arms and legs. Because Arc gives us live health and diagnostic data on every robot, a lot of that turnaround starts before a technician ever reaches the site.

For any issues which require further remediation, we currently have a service center located in our RoboFab facility and will be standing up a second service center in our Pittsburgh facility. Our current service center turnaround time on a deployed unit is under five days, and we’re actively working that down to under three.

Now let’s get into the bill of materials and cost structure, because this is where operations turns into a financial story. Over the past 10 years, we have designed and built products Made for Work. It is that experience that has allowed us to drive Digit 4’s bill of materials down to roughly $125,000 per unit, and we’re running that same playbook on Digit 5 right now. It is the plan that delivers a clear path toward a bill of material which costs approximately $30,000 per Digit at volumes of 10k/annually.

I want to be direct about something: this cost curve isn’t a spreadsheet exercise, and it isn’t riding on one single lever either. There are really three different mechanisms driving it- engineering redesigns, supply chain initiatives with strategic partners, and finally. pure volume based discounts.

It’s worth discussing each of these areas separately, so you can see why we’re confident about addressing each.The first is the piece we control directly. Since we have developed and own the design which is core to our dynamic stability and payload capacity, we also own the ability to redesign those components to drive cost down.

Today, our actuators are the main driver of this category and are among the biggest drivers of Digit’s bill of materials, comprising roughly 25% of the overall cost of Digit.

Our plan to reduce costs here comes from design iteration, better manufacturing processes, and the learning we’ve built up over years of producing that system ourselves at RoboFab — real time on the floor, not a forecast.

The second area for enabling cost reductions is a different lever entirely: Supply Chain Initiatives. These are applicable across all components including the more standardized subsystems like cameras, sensors, and PCBs.

It is these components that we have begun developing strategic partnerships to enable cost reductions through scale that we don’t have to build ourselves. Bringing in manufacturers with existing global supplier relationships and precision manufacturing scale gets us better pricing and shorter lead times faster than years of building that same capability in-house.

The third area of cost reductions will come through growth as volume scales and we can benefit from volume based tier discounting. This will deliver roughly 20% of our projected cost down as we move into annual volumes of 1k and then beyond towards 10k.

Putting these three levers together — what we control ourselves, and what we get from scaled manufacturing partners and volume based discounts — are the basis for a clear path to a bill of materials from $150k at Digit 5 commercial launch to a target of $30k at commodity level costs. It’s not one bet on engineering alone; it’s engineering on the piece that differentiates us, and partnership on the piece that doesn’t need to.

The attractive economics we’ve discussed are only meaningful if you have the infrastructure required to scale production and support customers. We believe that this is one of Agility’s most important competitive advantages.

Over the past decade, we have invested in building not only a robot, but the broader platform that is required to deploy humanoids at commercial scale. That includes RoboFab, Arc, our software platform for deployment and fleet management, a predominantly domestic supply chain, and ownership of many of the highest value components and subsystems within Digit.

That’s the operational engine behind everything you’ve heard today.

I’d like to now bring on our next guest who represents a company that has backed Agility for years.

Foxconn is the world’s largest contract electronics manufacturer. Founded in Taiwan in 1974, it builds hardware at enormous scale for many of the best-known names in technology. Foxconn is also a long-time investor in Agility, and this year it led the internal PIPE in our business combination with Churchill Capital Corp XI.

Robotics is now central to where Foxconn is going: the company has named it one of the three emerging industries in its long-term strategy, alongside electric vehicles and digital health.

When the company that knows more than almost anyone about manufacturing at scale chooses to invest in a company like Agility, it says something about where it sees humanoids heading and the path to get there.

Nelson Hsieh is a Director in Foxconn’s Central Strategic Investment Department, where he works on the group’s strategic investments. He brings more than 15 years of experience in investment and fund management.

Nelson can speak to why Foxconn invested, why it chose to lead, and how one of the world’s great manufacturers thinks about the future of humanoid robots. Please join me in welcoming Nelson Hsieh.

Welcome Nelson it’s great to have you here today.

How is Foxconn thinking about its role in the humanoid robotics space?

A practical view from the factory floor: Foxconn builds about 40% of the world’s consumer electronics, operates more than 240 campuses in 24 countries and employs around 900,000 people at peak season. That gives it a practical view of where humanoids can add value, especially in repetitive physical work, and what it takes to move from a demo to a dependable production tool.

A strategic priority: Robotics is one of the three industries in Foxconn’s 3+3+3 strategy. The focus is on addressing repetitive physical work and improving the sustainability of manufacturing operations.

Deploy, build and partner: Foxconn deploys automation in its own operations, builds complex products at scale, and works with partners because no single company will define the humanoid robotics market.

Pragmatic, task-led deployment: Foxconn has publicly demonstrated a wheeled, dual-arm industrial robot for tasks including pick-and-place, collaborative assembly and force-controlled screw fastening. Its view is that wheels and legs will coexist, with the appropriate form factor determined by the task and operating environment.

Physical AI and FoxBrain: FoxBrain is Foxconn’s in-house large language model with reasoning capabilities. Together with embodied AI, vision, force control and digital twins, it supports the evolution toward more adaptive physical systems. A model alone is not a robot; value comes when intelligence is embedded in a safe, real operating system.

People and scale: The objective is to redeploy people to higher-value work, not replace them. Foxconn’s role is to help the ecosystem bridge the difficult transition from a capable robot to a scalable, dependable product through manufacturing discipline, system integration and operational experience.

Why are you betting on Agility as demonstrated by your participation in our PIPE?

Strategic, not opportunistic: Robotics is a core Foxconn strategic priority. We evaluate humanoid opportunities through the lens of an operator and manufacturer: which companies are ready to scale, and where can industrial discipline help accelerate that path?

- Three tests for scale readiness: Foxconn’s evaluation centers on three questions: Is there sustained customer adoption beyond a pilot? Can the robot work safely alongside people? And is there a credible path to building it at volume?

- Commercial validation: Agility has publicly disclosed Digit deployments with Schaeffler, GXO, Toyota Motor Manufacturing Canada and Mercado Libre, with commitments across nine customer facilities and more than 65,000 operating hours. It has also disclosed more than $300 million of multi-year contracted Digit 5 orders and a pipeline of more than 30 customers.

- Safety and manufacturing readiness: Digit 5 is designed as a cooperatively safe humanoid. Agility’s RoboFab facility in Oregon was designed for production of up to 10,000 units per year, providing a tangible foundation for scaling in the United States.

- Shared conviction: The announced transaction includes continued participation by many existing shareholders, as well as management and early investors—an important signal of alignment around Agility’s next stage of growth.

- Why Foxconn is participating: Foxconn believes the market will be led by companies that can deploy safely in real operating environments and build reliably at volume. Based on Agility’s publicly disclosed customer traction, operating experience and production foundation, we believe it is among the companies leading that transition.

Given your rapid expansion in AI server racks—growing them to represent 50% of revenue in less than 24 months—which elements of that strategy apply to scaling manufacturing for humanoid robots, and where do those parallels end?

- Proven scale-up experience: Foxconn expects AI rack shipments to more than double this year, with Vera Rubin racks entering mass production in the third quarter. The lesson is that scaling requires design, supply chain, testing and production ramp to come together—not simply more capacity.

- End-to-end systems discipline: Foxconn’s AI strength is integrating complete systems—racks, high-speed networking, power and cooling—and building them consistently at volume. That systems discipline is relevant to Robotics.

- A shared industrial foundation: AI racks and humanoid robots are different products, but they draw on overlapping capabilities in power electronics, precision machining, cabling and connectors, controls and electronics Assembly.

- Test earlier, learn faster: Foxconn is applying robotics, digital twins and simulation to plan production lines, develop robot skills and refine them on site—helping make deployment more repeatable.

- The parallel has limits: AI rack scale-up is a useful industrialization playbook, but humanoids have their own requirements for autonomy, safety and reliable operation in changing real-world environments.

- Conclusion: Scaling AI racks does not make humanoids easy. It gives Foxconn a proven way to take complex systems from prototype to dependable volume production—and that is where it can help the robotics industry scale.

Based on Foxconn’s experience deploying automation and early humanoid systems in operational environments, what are the most important operational priorities for a product team to address before ramping robot production at scale?

Start from real operations: Foxconn has used mobile robots, automated systems and digital twins in its own operations for years, and has publicly discussed deploying humanoid and collaborative robots in its US operations. Humanoids add a new combination: a robot built for spaces designed for people, with software that can learn from demonstration. The key question is what it takes to make a promising demonstration work every day on the factory floor.

Reliability in day-to-day operations: The key question is whether a robot can perform consistently across shifts and normal operating variation—not simply complete a task successfully in a controlled demonstration.

Fit with the existing workflow: Robots need to work within how materials move, tasks are handed off, quality is checked and exceptions are managed. Scaling is much easier when the operation does not need to be redesigned around the robot.

Simple service and recovery: At scale, the operating team needs a clear and practical way to understand what happened, bring a robot back into service and know when to escalate. The model cannot depend on a specialist being present for every issue.

Clear ownership and workforce adoption: Employees need to understand what the robot is responsible for, what to do when it stops and how it changes their roles. Adoption is strongest when the robot removes repetitive work and enables people to focus on higher-value tasks.

Conclusion: Technical capability is essential, but the real measure of readiness is whether the robot can become a predictable, trusted part of the operating system—not simply an impressive machine on its own.

Given tightening export controls on AI compute and robotics components, what’s the realistic risk to the manufacturing geographic mix and are you positioned to support the rapid growth in the United States?

Position for policy; do not predict it: Foxconn does not forecast policy or speculate on individual regulations. The practical issue is how policy can affect component flows, customer sourcing and the economics of manufacturing locations.

Resilience is more than moving factories: A resilient manufacturing network requires qualified components, engineering support, production capacity and logistics in the same region as the customer—ready quickly enough to keep the program moving.

Three risks to manage: The key considerations are component availability, customer localization requirements and overreliance on a single manufacturing location or supply source.

US capability is being built: Foxconn has publicly announced R&D and manufacturing build-out across Texas, Wisconsin, Ohio and California in response to US localization needs.

An operating foundation in the United States: Foxconn is building NVIDIA AI server racks in Houston as part of a benchmark AI smart-factory effort. This means the US footprint and operating capability are already being developed, rather than starting from scratch as demand for robotics components grows.

Conclusion: Export controls may accelerate localization, but qualified supply, cost, capability and execution remain the fundamentals. Foxconn believes it is positioned to support US growth because the footprint and operating capability are already being built.

Close: Thank you, Nelson, for that conversation. Now, I’ll hand it to our Chief Financial Officer, Michael Beer, who’ll connect all of this — the commercial momentum, the manufacturing discipline — to the financial picture.

Thank you, Jen/Nelson—and thank you to all the analysts and investors joining us today.

I spent over a decade in your seat as an analyst at Bear Stearns, Wolfe Research and Citi, covering public companies across the global logistics, mobility and infrastructure landscape.

I have also scaled dynamic, innovative technology companies and served as a public company CFO.

Drawing on that experience, my objective today is to tie together what you’ve heard, help you understand the economics of a Digit deployment as well as our value proposition longer-term, and explain how we intend to measure success.

I’ll focus on four key takeaways I want you to leave here with:

Proven Demand: we have validated customer traction with commercial engagements today based upon a proprietary design, built for scale - $300M in committed customer orders subject to the achievement of certain milestones, and real deployments

Healthy Growth Outlook: We articulated how our robust pipeline and growing demand picture will translate into future business wins through our turnkey offering, combining Digit - embodied AI and Arc

Anticipated Expanding Economics: we have attractive deployment economics with multiple levers to expand margins as we add skills and drive down costs; and

Capital Efficient Growth: built on investments we have already made with access to an advantaged costs of capital to support future deployments.

Let’s start with demand and the scale of the opportunity. Peggy outlined our near-term opportunity in manufacturing, distribution, and logistics—industries where the labor gap is acute.

There are over 400,000 unfilled manufacturing jobs today, with nearly 2 million potentially unfilled by 2033. That is a structural shift, compounded by changes in an aging labor force, re-shoring, rising transportation costs, and trade and immigration policies.

Further, the humanoid form factor is perfectly suited for those functions and in facilities initially designed for human labor over decades.

In the US alone, there is over 20bn square feet of industrial space, much of which is over 40 years old and yet to benefit from the upgrades and capital investment of a brand new facility. In more modern facilities, we also expect Digit to work alongside other forms of automation – not an either or. The broader market opportunity is estimated to approach $1 trillion by 2032.

Our opportunity expands as Digit learns new skills and addresses more of the work customers need done. And because the value of that work is linked to labor costs, we believe our offering provides a natural hedge against labor-rate inflation.

We bring real experience to that opportunity: more than 65,000 operational hours, with approximately 98% accuracy at Schaeffler and GXO. That experience helps us understand what customers require and what it takes to deliver consistently.

It also informed our recently announced next generation product, Digit 5, by truly incorporating the key requirements our customers demand for real-world deployments, designed to address a binding constraint on humanoid deployments - working cooperatively alongside people.

To bring new customers into that process, we established the Customer Acceleration Program in late 2025. It provides a structured path to validate performance, integration, and economics before expanding. Customers pay approximately $500,000 to participate—a meaningful commercial commitment, and we are getting paid for this work.

We have signed four new CAP customers and are engaged with more than 30 prospective customers through active commercial discussions.

The $300 million in committed Digit 5 orders demonstrates how that translates into demand. That commitment relates to 1,000 robots under three-year RaaS contracts. It represents potential multi-year value, realized as contractual milestones are met and robots are deployed.

With the recent announcement of Digit 5 and the subsequent rollout next year, our goal is to end 2027 with a potential customer pipeline of up to 100 customers and up to 25 committed customer facility deployments. Meanwhile, we believe our committed orders will commensurately increase to reflect our goals.

From there, we have five growth levers:

Over time, our skills roadmap moves from material handling into component handling, precision operations, and more complex autonomous tasks. Each new skill can expand the opportunity within customers we already serve.

Those levers reinforce each other: more skills create more applications within a facility, and validated applications create opportunities to expand across facilities.

And as you can imagine, satisfying an unmet need or labor gap for a role with a fully burdened labor rate of $40/hr is more valuable to a customer than one at $30/hr…

…assuming they can find a person for that role in the first place.

Now let’s turn to what we earn on those deployments.

As Daniel discussed, customers are currently leaning toward our Robot-as-a-Service offering, particularly for initial deployments because it reduces upfront friction and more closely resembles the ongoing cost of labor, so I’ll use that model to illustrate the economics.

We are looking at an assumed five-year useful life for Digit. These are product-level economics, including deployment and ongoing support, but excluding corporate R&D and SG&A.

Under RaaS, we receive annual subscription payments and an approximate $25,000 deployment fee. Over five years, those payments generate approximately $500,000 in illustrative cumulative revenue per robot – or $100,000 per year on average.

For the customer, the annual subscription represents a significant savings to their fully burdened labor costs, particularly when you factor in our ability to operate for three shifts per day. And the customer also receives access to our Arc fleet management tool and maintenance services.

Assuming a full-time fully burdened labor rate of $30/hr, this would equate to roughly $180,000 per year in total costs the customer would otherwise incur…

…and that’s without the impact of sick days, lunch breaks or other variables and viability that could eat into productivity.

Our costs include the upfront bill of materials, approximately $15,000 to deploy the robot, and approximately $15,000 annually to deliver software and maintenance. At a launch bill of materials of roughly $150,000, that is approximately $240,000 in cumulative costs against $500,000 in revenue—an approximately 50% product margin over the useful life.

We recover our initial bill of materials investment in approximately one and a half years. Specifically, that payback measure is the time until RaaS subscription receipts exceed the robot’s bill of materials. Deployment and ongoing service costs are captured in the lifetime margin calculation.

As we execute down the cost curve Jen described, both margins and capital recovery improve.

At approximately 1,000 units of annual production, illustrative RaaS margins reach approximately 70%, with payback below one year. At approximately 10,000 units, margins reach approximately 75%, with payback below six months.

That progression assumes no pricing upside. It reflects engineering, manufacturing, and supply-chain improvements, alongside higher volumes. Lower costs increase what we earn on each deployment and reduce the time required to recover our initial robot investment.

On that basis, 2,500 deployed robots represent approximately $250 million in annual revenue potential, and 10,000 represent approximately $1 billion. These are illustrative installed-base scenarios, with no deployment date attached. Actual annual revenue depends on deployment timing and contract terms.

For customers purchasing Digit as a capital asset, ownership brings more revenue forward (approximately 65% in year 1 assuming a 5 year useful life/deployment) and more than covers our bill of materials at the time of sale. We retain recurring software and maintenance revenue, with illustrative five-year product margins of approximately 40% at launch, increasing toward 70% at scale.

Pricing provides an additional opportunity under either model. We offer savings against fully burdened labor costs while helping fill jobs customers struggle to staff. That allows us to tailor pricing to the value delivered.

As Digit gains skills and addresses higher-wage work, we believe our pricing opportunity increases. Greater utilization strengthens the customer’s economics further. Neither opportunity is required to achieve the cost-driven margin progression shown here.

That brings us to capital efficiency.

We have already invested in the infrastructure required to scale: RoboFab, supporting up to 10,000 robots annually; ownership of Digit’s highest-value systems; a predominantly domestic supply base; and Arc for deployment and fleet management.

We also have a deep, proprietary pool of physical AI data earned through years of real-world deployments. Our commercial arrangements provide access to operating data across both RaaS and customer-owned deployments. Each deployment therefore contributes to the data, service knowledge and workflow experience that can improve reliability, accelerate the development of new skills and make subsequent deployments more efficient.

While are proudly focused on executing with real, paying customers.

All the capital we are raising is intended for deployment-related activity: building robots, putting them to work, supporting them, and advancing the engineering and software that expands their capabilities.

We are well capitalized today. Going public gives us substantial resources to accelerate that activity. It does not change our discipline around corporate costs.

Our illustrative model assumes approximately $60 million in SG&A in 2026, growing approximately 20% annually through 2028, and approximately $115 million in R&D, growing approximately 15% annually.

Longer term, those assumptions are approximately 10% and 15% of revenue, respectively. The platform and organization we have built should support a substantially larger deployment base, allowing revenue to grow faster than operating expenses over time.

Our infrastructure capital expenditure assumption is approximately $8 million total through 2028 and approximately 0.5% of revenue longer term. Funding robots deployed under RaaS is a separate requirement.

These are illustrative model assumptions but provide a framework for understanding how we intend to manage spending as we scale.

Briefly, on the transaction.

We are going public in partnership with Churchill Capital XI, which trades under CCXI. Churchill is a proven sponsor that has helped bring critical technology companies, including Oklo and Infleqtion, to the public markets.

We expect over $620 million in gross proceeds from our deSPAC transaction including more than $420 million from Churchill’s cash in trust and a $200 million common stock PIPE, secured before announcement, anchored by Foxconn, and priced at our $2.5 billion transaction valuation.

Agility and Churchill have filed a publicly available registration statement on Form S-4 with the SEC, which has not yet been declared effective. We plan to close this quarter, subject to customary closing conditions, and trade on Nasdaq under AGLT.

Finally, how should you measure our progress?

The model starts with units: bookings become backlog, and backlog converts into deployments as product, site, and workflow readiness allow. Customer readiness can be as important as manufacturing capacity in determining that timing.

For RaaS, revenue depends on active robots and the portion of the period they operate. Ownership brings upfront hardware revenue followed by recurring software and services. The mix affects revenue timing, margins, and cash requirements.

Our disclosures will focus on product milestones, bookings and backlog, conversion into deployments, and expansion across customer facilities. Active installed units, adoption mix, recurring revenue per active robot, and costs to serve will help connect that commercial progress to financial performance.

We look forward to seeing many of you at CES and continuing the conversation through our business updates and results calls.

With that, I’ll turn it back to Peggy for closing remarks.

Thank you, Michael — and thanks to the rest of the Agility team who spoke today: Jonathan, Daniel and Jen, along with our partners who joined us.

I said at the start of the day that you would leave with a clear answer to these questions: why Agility? And why now? Let me bring that together in one place.

You heard from Jonathan why this is happening now — physical AI has finally caught up to the real world, and Agility is the company that spent a decade earning the harder half of that problem.

You heard why Digit 5’s safety architecture won’t just be a feature. It’s the unlock that lets us work in closer proximity to people, and why that is a fundamental requirement to scale humanoids.

You heard it made real by the people building alongside us. Customers doubling down after years of hands-on experience with Digit. And you heard from Jen and Michael why the economics behind all of it aren’t a forecast. They’re already underway.

None of that happens without the policy environment keeping pace, which is exactly why we wanted that conversation in this room today, not off to the side of it.

So here’s the simple version: this is a business already generating revenue, already deployed in the field with commitments from customers who’ve already seen it work — asking to raise growth capital against demand we have already won. We think that’s a rare thing to find this early in a category like ours, and we’re glad you spent the afternoon with us learning more about Agility.

We’ve got time now for one more round of questions — anything we didn’t cover, or didn’t cover well enough. Let’s get into it.

Thank you Peggy. While we bring some chairs on stage for our final Q&A, I’d like to mention that Pras Velagapudi, Agility’s Chief Technology Officer, will join us.

As before, we have a few handheld microphones in the room so if you have a question, please raise your hand and I’ll call on you. Then, one of our team members will hand you the mic.

Please remember to introduce yourself and your company, and please limit yourself to one question and a short followup if needed.

That wraps up today’s Agility Investor and Analyst Day. I’d like to thank everyone here for coming and to those of you joining us online.

We’ll be in touch with many of you soon as we expect the transaction to close later this year, subject to customary closing conditions, throughout this fall at investor conferences, and again in the new year with our presence at CES.

Thank you for joining us and have a great rest of your day.

****

About Churchill Capital Corp XI (Nasdaq: CCXI)

Churchill is a blank check company formed for the purpose of effecting a merger, amalgamation, share exchange, asset acquisition, share purchase, reorganization or similar business combination with one or more businesses. It may pursue an initial business combination target in any business or industry.

Additional Information About the Proposed Transaction and Where to Find It

The proposed transaction will be submitted to shareholders of Churchill for their consideration. Churchill and Agility Robotics have jointly filed an initial registration statement on Form S-4 with the Securities and Exchange Commission (“SEC”) on September 9, 2026 (File No. 333-298781) (as amended from time to time, the “Registration Statement”), which includes preliminary and definitive proxy statements/prospectus to be distributed to Churchill’s shareholders in connection with Churchill’s solicitation of proxies for the vote by Churchill’s shareholders in connection with the proposed transaction and other matters described in the Registration Statement, as well as the prospectus relating to the offer of the securities to be issued to Company stockholders in connection with the completion of the proposed transaction. After the Registration Statement has been declared effective, a definitive proxy statement/prospectus and other relevant documents will be mailed to Churchill shareholders as of the record date established for voting on the proposed transaction. Before making any voting or investment decision, Churchill and Company stockholders and other interested persons are advised to read the preliminary proxy statement/prospectus and any amendments thereto and, once available, the definitive proxy statement/prospectus, as well as other documents filed with the SEC by Churchill in connection with the proposed transaction, as these documents will contain important information about Churchill, Agility and the proposed transaction. Shareholders may obtain a copy of the preliminary or definitive proxy statement/prospectus, as well as other documents filed by Churchill with the SEC, without charge, at the SEC’s website located at www.sec.gov or by directing a written request to Churchill Capital Corp XI, 640 Fifth Avenue, 14th Floor, New York, NY 10019.

Forward-Looking Statements

This communication includes “forward-looking statements” within the meaning of the federal securities laws. Forward-looking statements may be identified by the use of words such as “estimate,” “plan,” “project,” “forecast,” “intend,” “will,” “expect,” “anticipate,” “believe,” “seek,” “target,” “continue,” “could,” “may,” “might,” “possible,” “potential,” “predict,” “should,” “would” or similar expressions that predict or indicate future events or trends or that are not statements of historical matters, but the absence of these words does not mean that a statement is not forward-looking. We have based these forward-looking statements on current expectations and projections about future events. These statements include statements relating to, without limitation: hosting of the Analyst Day and its anticipated timing, location, program content and format, including the expected program highlights, presentations, live question-and-answer sessions, webcast, presentation slides and replay; Agility’s expectations regarding Digit 5, including its engineering for cooperatively safe work at scale, its product roadmap, software and autonomy roadmap and the role of Physical AI, and the use of real-world customer deployments and customer feedback to inform its development; Agility’s technology roadmap, commercial strategy, commercial momentum, market opportunity and plans to scale humanoid robotics across industrial applications, including plans for scaling deployments and manufacturing; Agility’s operating model, long-term financial profile and priorities as it scales; Agility’s plans to become a public company through the proposed business combination with Churchill Capital Corp XI; and the expected availability of the Analyst Day webcast, presentation slides and replay. These forward-looking statements are provided for illustrative purposes only and are not intended to serve as, and must not be relied on as, a guarantee, an assurance, a prediction or a definitive statement of fact or probability. Actual events and circumstances are difficult or impossible to predict and will differ from assumptions, many of which are beyond the control of Agility and Churchill.

These forward-looking statements are subject to known and unknown risks, uncertainties and assumptions that may cause Churchill’s actual results, levels of activity, performance or achievements to be materially different from any future results, levels of activity, performance or achievements expressed or implied by such statements. Such risks and uncertainties include: that Agility is pursuing an emerging technology, faces significant technical challenges and may not achieve commercialization or market acceptance; Agility’s historical net losses and limited operating history; Agility’s expectations regarding future financial performance, capital requirements and unit economics; Agility’s use and reporting of business and operational metrics; Agility’s competitive landscape; Agility’s dependence on members of its senior management and its ability to attract and retain qualified personnel; the potential need for additional future financing; the capital requirements of Agility’s business plans; Agility’s ability to manage growth and expand its operations; potential future acquisitions or investments in companies, products, services or technologies; Agility’s reliance on strategic partners and other third parties; Agility’s reliance on global supply chains and the risk that disruptions, tariffs, or trade restrictions could delay production, increase costs, and limit Agility’s ability to fulfill customer orders; Agility’s ability to maintain, protect and defend its intellectual property rights; risks associated with privacy, data protection or cybersecurity incidents and related regulations; risks associated with product liability, workplace safety regulations and potential injuries arising from the deployment of humanoid robots alongside human workers; the use, rate of adoption and regulation of artificial intelligence and machine learning; the evolving regulatory landscape for AI technologies across multiple jurisdictions and the risk that failure to comply with new or changing AI laws could result in enforcement actions, fines or restrictions on Agility’s ability to develop or deploy its products; uncertainty or changes with respect to laws and regulations; uncertainty or changes with respect to taxes, trade conditions and the macroeconomic environment; the combined company’s ability to maintain internal control over financial reporting and operate a public company; the risk that the proposed transaction may not be completed in a timely manner or at all, which may adversely affect the price of Churchill’s securities; the failure by the parties to satisfy the conditions to consummation of the proposed transaction, including the approval of Churchill’s shareholders; the possibility that required regulatory approvals for the proposed transaction are delayed or are not obtained, which could adversely affect the combined company or the expected benefits of the proposed transaction; the risk that shareholders of Churchill could elect to have their shares redeemed, leaving the combined company with insufficient cash to execute its business plans; the level of redemptions of Churchill’s public shareholders; the ability of Agility to grow and manage growth, maintain relationships with customers and retain its management and key employees; costs related to the proposed transaction; the occurrence of any event, change or other circumstance that could give rise to the termination of the business combination agreement; the outcome of any legal proceedings or government investigations that may be commenced against Agility or Churchill; failure to realize the anticipated benefits of the proposed transaction; Agility’s estimates of expenses and profitability; the evolution of the markets in which Agility competes; the ability of Churchill or the combined company to issue equity or equity-linked securities in connection with the proposed transaction or in the future; and other factors described in Churchill’s filings with the SEC. Additional information concerning these and other factors that may impact such forward-looking statements can be found in filings and potential filings by Agility, Churchill or the combined company resulting from the proposed transaction with the SEC, including under the heading “Risk Factors.” If any of these risks materialize or assumptions prove incorrect, actual results could differ materially from the results implied by these forward-looking statements. In addition, these statements reflect the expectations, plans and forecasts of Agility’s and Churchill’s management as of the date of this communication; subsequent events and developments may cause their assessments to change. While Agility and Churchill may elect to update these forward-looking statements at some point in the future, they specifically disclaim any obligation to do so. Accordingly, undue reliance should not be placed upon these statements.

In addition, statements that “we believe” and similar statements reflect Churchill’s beliefs and opinions on the relevant subject. These statements are based upon information available to us as of the date of this communication, and while we believe such information forms a reasonable basis for such statements, such information may be limited or incomplete, and Churchill’s statements should not be read to indicate that we have conducted an exhaustive inquiry into, or review of, all potentially available relevant information. These statements are inherently uncertain and investors are cautioned not to unduly rely upon these statements.

An investment in Churchill is not an investment in any of Churchill’s founders’ or sponsors’ past investments, companies or affiliated funds. The historical results of those investments are not indicative of future performance of Churchill, which may differ materially from the performance of Churchill’s founders’ or sponsors’ past investments.

Participants in the Solicitation

Churchill, Agility and certain of their respective directors, executive officers and other members of management and employees may, under SEC rules, be deemed to be participants in the solicitation of proxies from Churchill’s shareholders in connection with the proposed transaction. Information regarding the persons who may, under SEC rules, be deemed participants in the solicitation of Churchill’s shareholders in connection with the proposed transaction will be set forth in the proxy statement/prospectus when it is filed by Churchill with the SEC. You can find more information about Churchill’s directors and executive officers in Churchill’s final prospectus related to its initial public offering filed with the SEC on December 16, 2025 and in the Annual Reports on Form 10-K filed by Churchill with the SEC. Additional information regarding the participants in the proxy solicitation and a description of their direct and indirect interests will be included in the proxy statement/prospectus when it becomes available. Shareholders, potential investors and other interested persons should read the proxy statement/prospectus carefully when it becomes available before making any voting or investment decisions. You may obtain free copies of these documents from the sources described above.

No Offer or Solicitation

This communication does not constitute an offer to sell or the solicitation of an offer to buy any securities, or a solicitation of any vote or approval, nor shall there be any sale of securities in any jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such jurisdiction. This communication is not, and under no circumstances is to be construed as, a prospectus, an advertisement or a public offering of the securities described herein in the United States or any other jurisdiction. No offer of securities shall be made except by means of a prospectus meeting the requirements of Section 10 of the Securities Act of 1933, as amended, or exemptions therefrom. INVESTMENT IN ANY SECURITIES DESCRIBED HEREIN HAS NOT BEEN APPROVED BY THE SEC OR ANY OTHER REGULATORY AUTHORITY NOR HAS ANY AUTHORITY PASSED UPON OR ENDORSED THE MERITS OF THE OFFERING OR THE ACCURACY OR ADEQUACY OF THE INFORMATION CONTAINED HEREIN. ANY REPRESENTATION TO THE CONTRARY IS A CRIMINAL OFFENSE.

Media:

Michael Oldenburg

media@agilityrobotics.com

Investors:

Anthony Rozmus

investor-relations@agilityrobotics.com