Good evening. I'm Daniel Marshall, Senior Manager of Communications and Ownership. I'm joined by Jason Kelly, our Co-Founder and CEO, and our new CFO, Steve Coen. Thanks as always for joining us. We're looking forward to updating you on our progress. As a reminder, during the presentation today, we'll be making forward-looking statements which involve risks and uncertainties. Please refer to our filings with the SEC to learn more about these risks and uncertainties, including our most recent 10-K. Today, in addition to updating you on the quarter results, we're going to provide updates on our path towards adjusted EBITDA breakeven and dive deeper into the new deals and launches in Ginkgo's tools businesses, which continue to establish themselves as critical tools in AI-powered bioengineering. As usual, we'll end with a Q&A session and I'll take questions from analysts, investors, and the public. You can submit those questions to us in advance via X, Ginkgo results, or email investors@ginkgobioworks.com. All right, over to you, Jason. All right, thanks Daniel. We always start with our mission here at Ginkgo, which is to make biology easier to engineer. Our objectives are very similar to what you've heard from me over the last few earnings calls. We're trying to reach adjusted EBITDA by the end, even by the end of 2026 while maintaining a cash margin of safety. I'm going to update on that in just a sec. We're cutting costs while serving our current customers, and then very importantly, we're expanding from an R&D solutions business into the life science tool space. In the strategic section, you're going to hear a lot about that from me today. Before I get to that, I do want to touch on maintaining a cash margin of safety and the cost cutting. You can see our numbers here for the quarter. We're really happy about this. We've been aiming, and I told you this about a year ago, to get to a $250 million annual run rate cost savings by Q3 of 2025. I'm happy to say we hit that target a quarter early. This was a tremendous amount of very painful work by the team at Ginkgo. I want to say thank you to folks and sort of congratulate them on that progress and getting there early. That is very strategically important for us because the earlier we do it, as you can see, we have $474 million in cash and cash equivalents with no bank debt. That's where that margin of safety comes from. Having that large cash position while also getting burn under control means that we don't get pushed into needing to raise in a situation we don't want to or from someone we don't want to. We can be strategic about engaging with capital markets, which is really important. It also means we can start to take our focus from just purely cost cutting, to which we are still going to be cutting costs, but from purely cost cutting to also just really how we want to grow the business into 2026. You're going to hear a bunch from me today on that in the strategic section. Before that, I do want to hand it to Steve to go through the numbers, and I want to say congratulations to Steve, our new CFO. We mentioned this when we announced it, but you know, Steve's been with the company over the last two years. He worked very closely with Mark throughout that time, particularly over the last several months to really shadow and be a part of everything that Mark was doing. It made that transition super smooth and so really delighted. We're very lucky to have Steve in the CFO seat and I'll pass it to him to go through the numbers. Thanks, Jason. I'll start with the cell engineering business. Cell engineering revenue was $39 million in the second quarter of 2025, up 8% compared to the second quarter of 2024. In the second quarter of 2025, we supported a total of 120 revenue generating programs. This represents a 10% increase year over year. Turning to biosecurity, our biosecurity business generated $10 million of revenue in the second quarter of 2025 at a segment gross margin of 18%. As a reminder, segment gross margin excludes stock based compensation. Turning to the next slide, it is important to note that our net loss includes a number of non cash and other non recurring items as detailed more fully in our financial statements. Because of these non cash and other non recurring items, we believe adjusted EBITDA is more indicative of our profitability. A full reconciliation between segment operating loss, adjusted EBITDA, and GAAP loss or GAAP net loss can be found in the appendix. Now that we've completed a year of restructuring, you can see the very substantial cost reductions and improvements in profitability compared to the first quarter of 2024. In the second quarter of 2025, cell engineering R&D expenses decreased 63% from $84 million in the second quarter of 2024 to $31 million in the second quarter of 2025. Cell engineering G&A expense decreased 57% from $33 million in the second quarter of 2024 to $14 million in the second quarter of 2025. These decreases were all driven by our restructuring efforts and the significant improvement in cell engineering segment operating loss in the second quarter of 2025 compared to the same prior year period was due to the previously discussed drivers of improved revenue and reduced operating expenses. Biosecurity segment operating loss was impacted by the timing of programs in the second quarter. Moving further down the page, you'll note that total adjusted EBITDA in the second quarter of 2025 was - $28 million, which was improved from - $99 million in the second quarter of 2024, a 72% improvement. We show adjusted EBITDA at the segment level to show the relative profitability of each. The principal difference between segment operating loss and total adjusted EBITDA in the second quarter relates to the carrying cost of excess lease space, which you can see was $12 million in the second quarter of this year. This cost represents the base rent and other charges relating to lease space which we are not occupying, net of subleasing. This is a cash operating cost that is not related to driving revenue right now and can be potentially mitigated through subleasing. Finally, cash burned in the second quarter of 2025 was $38 million, down from $110 million in the second quarter of 2024. This significant decrease in cash burn was a direct result of the restructuring. Now turning to guidance in terms of the outlook for the full year, we are reaffirming our total revenue guidance for 2025 totaling $167- $187 million, with cell engineering revenue to be $117- $137 million and biosecurity revenue expected to be at least $40 million. In conclusion, we're pleased with the substantial improvements in cash burn and cost reductions when looking back over the past year, where we achieved our targeted $250 million run rate cost takeout three months earlier than planned in the third quarter. We will continue to execute against our core objectives while navigating continued uncertainty in the macro environment. With that, I'll hand it back to you, Jason. Thanks, Steve. The three topics we're going to cover today in the deep dive is, one, our continued restructuring and the cost takeouts. In sections two and three, I want to go through automation and data points and our newly launched reagent product, which are really our three big motions into the life science tool space. I'm really excited about this today. Let's dive in. First, I mentioned this already. I'm really excited to see these numbers, that $250 million cost reduction. Getting that done ahead of schedule is very strategically important for the company. The whole reason we've been focusing on this, and the team has put in an absolutely enormous amount of work and pain around this, is we wanted to be able to do this motion of moving into the life science tool space with a margin of safety. In other words, with enough cash in the bank and no bank debts to allow us to not be forced to take money from people we don't want to or raise in circumstances where we weren't happy. Having that large cash balance relative to our cash burn is really a critical piece of putting us in a good position when and if we engage with capital markets. I'm really happy that we're there on that. You can see here our burn rate's getting down to $28 million if you go to the next slide of adjusted EBITDA for this quarter. Again, a testament to the team and strategically important to Ginkgo. Now I want to talk a little bit about our automation and data points offerings, and then we'll talk at the end about reagents. To give you some macro context, and I spoke about this before, Ginkgo's business over the last decade has really been what we call solutions. In other words, selling to the Head of R&D of a large company or the CEO of a small or mid-sized company, and basically being an outsourced research team, Ginkgo scientists using Ginkgo tools to deliver them a research product. That was the solutions business last year. About a year ago, alongside a restructuring in the company, we started to offer Ginkgo's tools and services that we had previously had in house just for our scientists, directly to the scientists at our customers. That has been going really, really well. I want to give a little more context on that. If you go to the next slide, you can see, on the Y axis here we have what I'll say is like our customization and technical risk we're taking for the customer. When that is high, like it is in research solutions, in other words, we'll have a big milestone that will only get paid if we're technically successful. The customer is willing to give us downstream value share, in other words, a share of the future value of their products, either a royalty or success-based milestones like that technical milestone that I mentioned and so on. That's really in exchange for the level of customization and risk we're taking. As we go down that Y axis, we go to the right-hand side of this chart where we're not able to get royalties and downstream value share. That's a downside. The upside is we're selling something much more off the rack, in other words, a more standard scalable product to the customer. If you go to the next slide, what we're seeing here is the solutions business has that big upside. It takes a while to get to it. I think there's a really nice complement here where our tools offerings are able to give us near-term revenue, smaller batches, wider customer set, new opening, new markets. We're going to talk about the reagents. This first kit is a $2,000 kit. Scientists can order it with a credit card, so that is really allowing us to have a faster cycle time going to market. It's a good complement for the solutions business and it's the right time to do it. I'm going to jump in and talk a little bit about our automation offering and then we'll get to our data points which is more traditional CRO and then finally reagents. When I talk to customers about automation I like to show this slide which is that Ginkgo, in addition to selling automation, has been a user and builder of automation over the last decade as we've been doing these solutions partnerships. This is where that solutions business really complements life science tools. We're almost unique among life science tools vendors in really being primarily doing high-end science using our tools over the last decade, which means we have an enormous amount of familiarity with what's out there in the market, what works and what doesn't. We built a lot of our in-house tools to fill gaps in what we couldn't get from vendors on the market today, which is what makes our tools business so exciting. Because when we launch these things, they're immediately stepping into a gap in the market because if it hadn't been a gap, we would have been buying it already from the life science tools companies. If you go to the next slide, this is what I think is the core challenge. If you look across the industry today, when we talk to life science leaders, heads of R&D and so on, the number one thing you're hearing is there is a demand for more output from the same R&D resources. This is a combination of factors. Sort of economic pressure in the industry over the last three or four years with interest rates up. It's also competition from biotech companies in China, where you're seeing lower cost labor, sort of lower cost infrastructure and so on, creating pressure on the research infrastructure here in the United States and in Europe and others. How do you solve that problem? Part of the issue from my standpoint is the majority, the overwhelming majority, 95%+ of the research work done in the sciences and in commercial biotech and agriculture is done at the lab bench. That picture on the left is basically what every lab bench looks like if you go into any one of these companies. Right? There's pipettes at the bench. I did my PhD in bioengineering. That's five years of picking up one of those pipettes and moving liquids around, working by hand at the bench, buying things from the Thermo Fisher catalog, reagents. It's very variable. You can do almost anything you want, but you do it at low throughput. As you do more of it, it does not get cheaper. It's not like making cars or making semiconductor chips. Whereas you do more, the cost falls per unit. As you do more research, it's just as expensive as the last unit as you do more because it's being done by hand. The obvious thing, like if you're a tech person, is like, just automate it, right? If we automate it, like semiconductors and automobiles, you'll get a much lower cost per unit operation in the lab. This is even more acute because you're seeing demand around AI for these large data sets. I'll point out we are not the only ones thinking this way. Like, let's automate it, right? President Trump put this out just last week, winning the race, America's AI Action Plan. I would really recommend you read this document. It's great. It's very focused on the actual things to do in order for the United States to make strategic choices in AI. One of the categories is invest in AI-enabled science. You should read the doc, but I'll just call out one specific part where it says, you know, through NSF and DOE and so on and other federal partners, there should be an investment in automated cloud-enabled labs. What they're saying there with cloud-enabled is think like a data center, right? When we say cloud computing, we think of a big data center that can do lots of different stuff and it's accessible and gets cheaper with scale and improves with technology. Can we make the lab bench more like the data center cloud? That's the provocation from this sort of AI action plan. I think we can. If you go to the next slide, I'll show you why it's been hard historically in the industry. On the Y axis here, and this is going to be my automation nerd out slides, so bear with me. On the Y axis here is a term of art in automation called mix. A low mix environment is like an automobile plant, all right? You're making the same car over and over again. It's a low mix of output. A high mix of output is like a fine chef at a restaurant, all right? Lots of different orders coming in from the menu, variations. People are requesting all kinds of stuff. You have a common set of tools, but you use it in very different ways to produce different highness of outputs. That chef is very analogous to the scientists at the lab bench today. Very analogous, all right? They have a common set of tools, common set of equipment on those benches. They're using their hands and they're doing a very high mix of work. They are very well served by Thermo Fisher, Danaher, and a long tail of equipment and reagent vendors over the last 50 years that are selling them all kinds of stuff to work at that bench. It actually works pretty good. It just doesn't scale. It really does not get cheaper with scale. That's what we're seeing with the increasing price for new drug discovery and everything else. On the other hand, on the low mix side, more like an auto plant and a high throughput on the X axis, we have what we call automation work cells. I'll show you a picture of one in a second. These are where automation has been used in life sciences today. Things like high throughput screening and compound management. Places where, you know, diagnostics where you're doing the same protocol over and over and over again. Their automation does work great in the lab. There are companies like Thermo Fisher and HighRes Biosolutions that'll sell you these customized work cells. The trouble is they just do those one or two protocols. They don't have anywhere near the flexibility of the bench. The question is, can we get to high mix, high throughput, or at least like medium mix, medium throughput, something that's closer to the bench but sees a scale economic? That's what we're trying to achieve with Ginkgo Automation, and we believe is possible with our reconfigurable automation carts, our racks, and our software on top of them. I'm going to talk a little bit more about that. To give you some context, on the slide here, you can see a picture of—go to the next slide—a work cell. This is that traditional low mix, high throughput automation work cell. This is actually one that we got built for Ginkgo. Those two white towers in the middle are robotic arms. They can pick up a plate and move it to all the various benchtop lab equipment that's jammed into that thing. You see everything kind of stuck in there and on top of each other and everything else. If it's not obvious, that is a very custom object. It is not standardized. It is built just for you. It has a relatively low return on investment because the entire value of that work cell has to be justified by the one or two lab protocols that it's able to conduct. That means that, back to my comment earlier, 95% of the lab work is happening at the bench, and less than 5% is happening on work cells like this because it's only the most repeatable work that can justify that return on investment. If you go to the next slide, this is our solution to that: the reconfigurable automation cart. This is technology invented at Ginkgo. We've been building this up over the last 10 years. In this box, basically, is a piece of lab equipment. You can see an orange centrifuge there inside the box in the cartoon. There's a robotic arm and there's a piece of MagnaMotion track. What this track does is allows you to deliver a plate, a 96 or 384 well plate, to that robotic arm. The robotic arm picks up the plate, puts it onto the piece of lab equipment. We have—I'll show you in a minute. Now, 50U + lab equipment, integrated, puts it on the equipment, and the software tells the equipment, run your experiment. When it's done, the arm picks up the plate and puts it onto the track. What's great about this is once that custom piece of equipment is inside this box and we integrate directly with the equipment, our software, it's now basically like a standard unit. If you go to the next slide, you can see we can stitch these together. We put unit, unit, unit, and we've now connected three pieces of lab equipment all into one setup. We can move the plates among those equipment on that magnetic track. With the arms, we can deliver the samples to the equipment. It all just works if it's on that integrated setup. We have now, you know, like I said, 50U+ pieces of equipment, they're not all shown here integrated into these setups. We're adding more every day. If a customer wants a new piece of bench equipment inside our setup, we do that at our cost and then have it integrated in the future for future customers. You can put together many of these. Here is a picture of our lab if you go to the next slide. Here in Boston, and again, unique among automation vendors, we use our own automation in BSL-2 labs. This is a 20U+. Inside it, you have all these different pieces of equipment. You can again run protocols that connect any piece of equipment to any other piece of equipment in that setup. If you go to the next slide, this modularity is really exciting. Customers are loving it. This is just off at a few vendor trade shows. I really like the picture up in the top right. Recursion had an event at JP Morgan. They invited us to come, and we actually set our rack system up on like a five cart system in an afternoon and had it running for the cocktail party. The ability to quickly build the system and then, very importantly, expand the system is unique to our hardware. If you're building that, you know, kind of Rube Goldberg machine with the arms in the middle and everything else, that is a custom job that takes a long time to do. It's again built one off for the customer. With this, we can really print these carts and it allows customers to quickly scale their infrastructure. If you go to the next slide, we have a great existence proof of this, which is our setup that we've been using at Ginkgo Bioworks to do research work for customers over the last several years. You can see here, highlighted in blue, a number of pieces of equipment that were originally put on our setup for next gen sequencing prep of samples. Having all those on that setup allows a sample to get prepared and go on to our sequencers. That was the original investment. That was the ROI. We were going to do tons of next gen sequencing. That justified it. Very importantly, our scientists came along and, go to the next slide, they requested a protein quantification assay. It's a HiBiT assay from, made by a company called Promega. They wanted to run this at high throughput instead of at the bench. We developed a protocol that would be, you know, 7,600 samples in six hours. Like a very, you know, high throughput protocol. If you look and we want to now add this to the racks on the next slide, we were able to reuse. Now the blue on here are our machines from the NGS protocol that are relevant to the HiBiT protocol. We don't need to buy those again, they're already on the setup. In fact, in order to add this HiBiT protocol, we only had to add the Ferrostar. That one pink highlighted piece of equipment at the top was added in order to enable a whole new protocol. That's the ROI, right? We had to just add one piece of equipment and all this existing investment and these things, these warp cells and things can cost $1 million+ when you make them the one half and you can't expand it. By adding just one cart to this, we're able to have it do a whole other protocol. Importantly, as you add enough carts, it costs no more to do more protocols. It's just software changes because you have enough equipment in one big setup in order to make that possible. If you go to the next slide, what I'm really excited about, I think this is the direction that the U.S. government is headed with these cloud-enabled labs. This is the direction that I think heads of R&D absolutely have to have on their radar if they're looking to reduce research costs, which is to have many, many, many pieces of equipment all in one big setup that can basically do whatever protocol you want in the future. This is a setup we just announced a week ago that we had nearly complete for Pacific Northwest National Labs. It's an 18 piece of equipment setup. What's really amazing about this, if you go to the next slide, is all of our sort of arms and tracks are inside of anaerobic chambers for this system. This is an environment that humans can't go in. You know, it's air free, so it's really difficult. You see those arm things. Normally people are doing experiments with their hands in glove boxes and all this crazy stuff. Instead, here, those arms are really just to service the equipment that you see on this setup. All the samples that are going to move among the equipment are going to run through our automation. If you go to the next slide, we believe this is the largest automated anaerobic system in the world. Really excited about Department of Energy investing in this. I think it's exactly what the President is looking for in the next slide in these sort of cloud-enabled labs initiatives. I think you will see more of this. I'm really excited about this. I think Ginkgo Bioworks' technology is perfect for this. By the way, I think 18 instruments in one setup is going to be looked at as small in the future. Really, we should have 100, 200 instruments all in one big setup that allows you to ultimately submit protocols to do anything you could do at the bench. Ultimately, we're not there yet. There's a lot of technology between here and there, but that's really the dream here, to be able to have that same level of flexibility or something near it, but with the scale economic of automation. That is absolutely essential if we're going to have AI-enabled science. Without question, it's just not going to happen at the lab bench. One more thing on this, the software side. I'm not going to be able to dig in today, but I'm excited to tell you more about it in the future. I will just say for customers that are tuning in, Ginkgo 's has been doing lab-in-the-loop AI-enabled science, having reasoning models interacting with this robotics, really, really cool stuff. We'd love to share it with you. We have the whole, both obviously the hardware I spoke a lot about today, but importantly the software stack, the modern APIs, cloud-based software, everything that makes that all really feasible. MCP servers accessing all this equipment. If you're really ahead of AI, looking to bring that into your biotech company, you should give us a call both for the hardware and the software layer. Okay, so that's much I want to say about automation, but I really see that as being extremely strategic for Ginkgo going into 2026. As we've gotten our cost more under control, you're going to hear me go more in this direction, right? It's going to be more about what can we invest in for growth in the future. One of those big areas is going to be automation and AI. All right, beyond that, I want to talk about our push into the CRO services market. We call those Ginkgo Data Points. We have a number of different services now: perturbation, response, profiling, specialized high throughput screening, antibody developability, which I've talked about before. We just launched our small molecule developability or ADME service. You know, you can do, you know, lots of different things with these services. They are available, just to be clear, there's no royalty, there's no milestone. It's just like engaging with a CRO, like a WuXi or whoever, fee for service basis. You own all the IP and data as the customer. We're able to do this at very large scale because of our automation expertise. One of the things I'm really excited about, we announced this in the press release of the ADME service, is if you have a quote from another vendor in the CRO space, like for example, you know, Chinese vendor, and you want to onshore that back here to the United States, just send us the quote, we're happy to meet it. That goes for ADME, but generally you should send us the quote anyway. We're happy to see it across any of our services and meet vendors. Please do keep that in mind if you're looking at Data Points. This is why I'm excited about Data Points in the long run. I think it is exciting to go after the traditional CRO market. I think there's good business there. It's also not that high throughput. A lot of what places like WuXi have done is basically gotten cheaper hands at the bench and then offered that as a service. That buys us, you know, whatever, 40% cost reduction on the big problem of reducing R&D and getting scalability. It kind of runs out because it's just not getting cheaper. I think across the board, if we want to be cheaper, the answer is automation. Ginkgo's been doing this work really in an automated fashion and that allows some unique offerings to customers. I'll just highlight this funnel here where this is traditional drug discovery. You're going to identify its targets, then you're going to run some high throughput screen, maybe on a robotic setup, maybe in some sort of pooled assay in the lab. Either way, you're going to screen a bunch of lab work to pick a few hits and then you're going to take those hits into a much more expensive series of experiments in order to validate if they're good drugs. All right? It's those set of more expensive experiments that we've been focusing on trying to make high throughput on our automation at Ginkgo Bioworks and offer as a service through Ginkgo Data Points. What's exciting about that, for example, say antibody developability, you find these binders, which you can do at high throughput really cheap, but then you get to developability and it's expensive. Is it soluble, is it immunogenic? These are things that you have to do these more expensive experiments. You only try them on your top hits and you kind of cross your fingers. What we are able to do with our throughput is let you apply those developability assays back much earlier in your hit finding so that you look at a much wider range of potential candidates against not just whether they bind, but also are they developable. If you generate enough of this data, maybe we can even have computational models and AI that can predict developability. That's where we're seeing a lot of excitement. That's kind of our niche to get off the ground in the CRO space. This is, you know, the DPMTA, the design, predict, make, test, analyze cycle in pharmaceuticals. We're really focusing on scaling up that test step for these high complexity assays. I think that's something we're very, very good at at Ginkgo Bioworks. You should expect us to launch more products. This is just that ADME profiling service kind of start to finish project scoping, chemical libraries, so on. I will highlight we're using Echo MS, Echo Mass spec to do that sort of high quality but also high throughput asking. That's what allows us to get costs that can really compete with doing it with low cost labor overseas. All right, last but not least, I want to talk about reagents. I'm super excited about this. I'm always excited when I see Ginkgo Bioworks move into a new market area because if we do pick up traction there, they sort of like a lot of clear vistas in front of you to get into. This is our first reagent product. Just to understand kind of the theory here, again, over the last decade Ginkgo Bioworks has been a big, big consumer of life science tools. We have bought various services, we have bought a ton of equipment like those custom work cells I mentioned, and we bought a lot of reagents. Where we can get something great on the market, we'll use it. What we found is there are certain gaps in areas that were important, maybe very important to us for our cell engineering that weren't widely available or the products weren't really up to our level that we needed on the market. In those areas over the last decade, we developed our own stuff. We just never sold it to anyone because it was part of our solutions offering and we kind of wanted to keep it proprietary. What's really fun here in R&D is we're getting to launch a bunch of these, what had previously been in-house assets at Ginkgo. In fact, we had Ginkgo employees who left, went to other companies and were like, hey, will you just like give me that, you know, reagent or thing we used to have at Ginkgo, because I want it. We heard that enough times that we decided we might as well try to sell it. This is our first product, the cell-free protein synthesis kit. Cell-free protein synthesis is basically instead of, if you want to produce a lot of protein, taking your gene of interest and moving it into a live cell like an E. coli or a yeast, and then growing that live cell, producing the protein and extracting it, instead, you start with the live cells like the E. coli, you grow a bunch up, you pop them open, you lyse them, you take the contents out, you make that into your reagent, then you add the DNA straight to that reagent mix and it's got all the components of the cell. It's just not alive, and so it'll make protein. Now there's some downsides that the cell keeps everything in a little, you know, small container, so it has like a high density, which is helpful for production, but now this extra step of growing the cells and everything else. For a number of applications, cell-free really does stand out, and we had a lot of those applications, I think. We have, you know, our product here has twice the yields for half the cost compared to market leaders for certain protein constructs. You can get, you know, $2,000, you can get a 10 mL kit, which is a great offer on the market today. In fact, we launched this just last week. We've already got some early sales, which makes me very excited. Importantly, we also had a free sample. We have, you know, over 100 people have requested samples. What I think is, just I wanted to highlight, was a large fraction of that was actually in the academic research market. This is a market that Ginkgo has basically never sold anything to until selling a kit recently because we haven't had anything to offer. They're obviously not going to outsource research to us. That's really like all they do for a living. Our solutions business never made sense. We had a certain scale of CRO services with Ginkgo Data Points that were really pointed at the commercial market. I'm pretty excited to see this. I think the academic research market has been a huge market for life science tools. Companies like the sequencing companies and companies like Thermo Fisher. Us being able to get into that market here with reagents is very exciting. That was kind of what I wanted to walk through. Again, big takeaways. We're coming in a quarter early on that cost takeout target. That's very strategically important. We've done that with a good amount of cash and margin of safety still in the bank. That $474 million in cash equivalents and no bank debt sets us up very well to look to the future. We are doing that. You will see and hear more from us on the life science tools space. I shared some of that today, but expect Ginkgo to really be focused on growing into 2026 from here on out. Super excited to hear your questions and thanks very much for your time. Great. Thanks, Jason. As usual, I'll start with a question from the public and remind the analysts on the line that if they'd like to ask a question to please raise their hands on Zoom and I'll call on you and open up your line. Thanks, everyone. All right, getting started. We'll start with a question from x.com. I confess I'm not sure how to pronounce it, so I'll read the whole username out for you. Yetiny 471. This question is about automation. Could you please share whether Ginkgo Automation is expected to become a primary driver of the company's revenue? May I ask if Ginkgo is considering acquiring additional companies in the near future? Could you elaborate on the strategic significance of Ginkgo RNA Solutions for the company? Sure, I can take that one. Yeah, it's good to get a question about automation. Obviously, I spent a lot of time about this on the earnings call. I do think automation is going to be a huge part of our future business. I tried to convey this idea that what we're really trying to solve for with our technology is general purpose automation. The market for general purpose automation, we think ultimately is something like the market for the lab bench. The lab bench has been the general purpose, kind of like platform for doing laboratory work. There's obviously lots of ways to sell things into the lab bench and free agents, consumables, benchtop equipment, services, so on. The real question is, are we able technologically to make automation as general as the lab bench or even somewhere along that arc? If so, then yeah, it'll be the majority of our business in the future if we could pull that off. The lab bench has been such a huge market in the life science tool space. That's what we're going to see. I'm certainly optimistic that we could pull that off, but yes, absolutely, like automation writ large when it is that generic, absolutely would be. I think ultimately that the majority of the revenue of the company would flow through something like that automated benchmark. Yes, about acquisitions also, we don't have anything immediately planned. It's a tough market for life science right now, life science tools in particular as well. There are things kind of popping up on the market all the time. If something was a really great fit and a good opportunity, you might see us do it, but nothing immediately planned. The last thing was RNA Solutions. Is that right, Daniel? Yeah, RNA Solutions, yes. We announced, I didn't talk about this on the earnings call. We announced a product called RNA Solutions. Best way to think about this is taking some of our expertise in the solutions phase. A solution project again is a customer outsources a whole, usually like a six month, a three year R&D partnership. Our scientists are doing the work, using all the tools available at Ginkgo Bioworks to deliver ultimately a scientific result to the customer. Maybe it's a better drug candidate or a new agricultural product, whatever. As part of that we have a whole bunch of kind of capabilities in there and some of them, like I was mentioning, we can turn into a reagent, some of them are turning into hardware products and some of them we can turn into services. With Ginkgo Data Points we're doing that in a few specific areas. RNA Solutions is an example of us offering a service like that, radiating out of our work, doing RNA discovery. You might remember had partnerships with places like Pfizer and others doing that. That's just us turning that into a kind of off the shelf service. I'm excited to see that. I think there's more things like that in the solutions business like Ginkgo. Expect to see more things like that. Cool. Thanks, Jason. For our callers, you can just raise your hand and I'll open your line. I have another email question which I can get to in the meantime while we're waiting. This is from Brendan with TD Cowen. There are two questions. Yeah, I know there's like a whole bunch of earnings calls today. We had some folks tell us that they were not going to be able to make it. We apologize for scheduling it on top of everyone else. We'll try to do better next quarter. Go ahead. Be great to hear from you. For sure. Yeah. Okay, the first question is, could you provide some more color into your ADME data generation software? Are you planning to develop any of your own models on the generated ADME data as a separate build out for customers? How does the meter-based pricing work in terms of licensing over the course of a contract's lifetime? Are you pushing the service to any partners that house their own rack systems? Okay, maybe I'll go in reverse order and then maybe you'll give me that first one again. That would help me out. On the rack systems, one of the things I'm excited about is having us demonstrating capabilities through our service offerings on the rack hardware at Ginkgo in Boston. If a customer wanted to have that infrastructure in house, and there can be a lot of reasons for that, maybe they want to apply the technology against a cell line that's very proprietary, that they don't like to have leave the building or whatever. There's lots of reasons. You can imagine it, we would have kind of proven that technology out on the rack modular automation hardware. The great thing about that hardware is I can then just install those systems at your site and the protocols should run the same as they run for me. This is the advantage of Ginkgo having a bio lab where we run our own automation and we do these hybrid services. It does mean that we can actually kind of lift and shift those services right onto your premises if you want them. I think there's an opportunity for us to do work as a service, show people it's valuable, install racks that do that work so that we have that business in the future with a customer. As far as we're concerned, whatever makes the most sense for our biopharma, bioag, industrial biotech customers, if they want to do it in house or through services is fine with us. I think you will see that crossover between automation and Data Points in the future. The meter beat, the key, the idea is very simple. There's a lot of vibes, I would say, around, hey, we need to have these CRO services in China because they're so cheap, and if you take them away we want to have these cheap services, and we just want to try to take that off the table and offer CRO services that cost the same thing. Now there's not really an excuse to not have it onshore in the United States. That's the whole point with the meter beat, to really send that signal to the industry that there will be providers here in the United States that can match prices with WuXi and other CROs overseas. The first question, sorry, the ADME one, Daniel. Yeah, the first question was whether we were planning to develop any of our own models on the generated ADME data as a separate build out. Yeah. You are seeing folks working on this problem as a few startups right now. There are like a liver tox one and some others. The basic idea, if you are going to generate all this data, like the ADME data, a lot of it is around the developability of a small molecule. Could you then turn that data set into an AI model that is then just available as a model to customers that they can include in their design of drugs in the first place? I mean, I think it's a great idea. I think it's tough, like the business model for that has not really been worked out well in the biopharma space. The sort of history of software, there have been places here and there, sorry, I'm just spacing on the name, but there is a well-known drug modeling company that has made an okay business out of this. It's generally been tough via a pure play software type service. I think it is an add-on we could add. The primary activity, the thing we think customers do have a willingness to pay for, is generating data. If it's data for their proprietary molecules, for their libraries and whatnot, that's data they need, and if we can generate that data for them more efficiently or at a scale they can't do in house, then it's data they'll pay for. We like that just as a business model. I do think there's an opportunity as those big data sets get produced, whether we do them with partners or in house, that you could develop models. One thing I will say is we do release data sets. We do these data drops where we'll post. We actually put them up on Hugging Face now, so you can go to Hugging Face and Google for Ginkgo's data sets. We have antibody developability, we have functional genomics terabyte-size data sets. If you're tuning in from a customer again on the AI side or high throughput biology, you should go download those data sets. It'll let you see the kind of data that we make from the Ginkgo Data Points service in a nice clean format, and you can play around with it. If you like it, then you can just order more for your specific areas of interest. I think you'll see us do data drops, and then maybe depending on the market over time, we could do models. We are also happy to enable other people that want to do models. If they want to generate a huge data set and make an awesome AI model and then sell that model, we are here for it. I think there'll be an ecosystem in the market. Cool. There was one more question from TD Cowen and that was about biosecurity. On the lowered biosecurity guide, are you seeing any areas that are particularly exposed to geopolitical pullback or tension? Are there any end markets that are seeing particular exposure as well? Yeah, sorry, I meant to mention this in my talk. As Steve Cohen had mentioned and shown in the numbers, we've gone from a $50 million+ to a $40 million+ on biosecurity, brought that down. This is basically because in bio we've always tried to guide to like what we had in the bank as much as possible. We try to be conservative about it. We're still like it's based on the international side is the short answer to this question. We're seeing certain contracts that we were hoping to have in place by now not be in place. I don't think they're not like totally off the table. At this point I just wanted to be more conservative because that had been kind of the attitude we take in with the markets on biosecurity. Whether that's like a macro trend or an anecdote, not totally clear. I think we are certainly seeing a lot more focus in the U.S. on like defense technology and I think biodefense, and this is like the companies like the Andurils and the Palantirs of the world. I think there's like little question that there should be sort of like a biodefense prime. Right. Like that's the thing that should exist in the market, how that gets built and what are the first types of contracts and so on I think are still like open questions, but I think the biosecurity business is well positioned to lean into that. We have to kind of just see the market as it develops. Cool. Thanks, Jason. All right, any questions? I have another one from online if you'd like for me to go that direction. Yeah, sure, go ahead. We'll do one more, and if no one else is there, it's the earnings day. Go ahead. Yeah. This question is from sleep90501 on x.com regarding your target of adjusted EBITDA profitability next year. Could you walk us through the key levers you're focused on to bridge the gap from today? Specifically, where do you see the most significant impact coming from? Is it increased foundry automation, AI-driven efficiencies, or disciplined SG&A management? Steve, do you want to touch on that? Yeah, I can start it. Maybe you speak to maybe some friends. Jason, if you just level set what we just accomplished in four quarters, we've succeeded in taking $250 million out of our cost run rate and we have effectively six quarters to go before we get to our target goal. Just looking at what we've done last four quarters, that's going to roll forward positively for the next six. In addition to that, we still have some cost leverage to take out. We need to be strategic about that. It's not as company-wide and holistic as we just accomplished, but there's absolutely more opportunities in the cost side and then we have to drive revenue and a lot of the drivers of revenue are what we've been talking about all along. We need to see, you know, solutions, contributions from tools and we really see, you know, a lot of what Jason talked about is going to roll in, in some, in some successful way in revenue. That said, our biggest risk and opportunity still remains the sublease situation that we have. We have a significant amount of unutilized, underutilized rent space, lease space. You've seen that we've taken out of the segment adjusted EBITDA the unused space because we're not using it to contribute revenue right now. The most important element of that is we've succeeded in doing what we said we were going to do. We were going to shrink our footprint as far as our work level, revenue, production level. We've done that successfully and we're out marketing. The tough side and the risk side is the fact that the Boston market and the other markets around are just soft at this moment. We're continuing to focus on that. Jason, I don't know if you have any views on revenue drivers. No, I mean, I think the big one is it's a continued shift in the tools. I think we'll watch how fast we can get to pick up on the automation in particular and Data Points. It could be very swingy. We're seeing a lot of interest because of the AI work in beginning to automate labs. I do think we have the sort of best technology in the market for that. If you're really talking about general purpose lab automation and connecting it to AI reasoning models and this lab-in-the-loop concept and all these types of things, I really think we're well ahead on that. We'll see. That would be the one that's the most swingy where we could really get ahead on things. It is a new area for us. I don't want to overstate it, but I'd say that's the place where I see the most upside potential on revenue in 2026. Cool. Thanks, Jason. All right. Not seeing any other questions right now. I know folks are on other calls as well, so just a reminder that you can always reach us at investors@ginkgobioworks.com and we'll get back to you as soon as we can. I want to thank everyone for tuning in today. Yeah, appreciate it, Daniel. Thanks for the questions.