Judy Warner (00:01.058) Hi, Phillip. Thanks so much for joining us today. I'm excited to have this conversation and catch up with you at CoFactor. Why don't you start out by introducing yourself, telling us a little bit about your background and then who CoFactor is and what you're looking forward to there. Phillip Gulley (00:17.819) Sure, sure. So I'm Phil and I am the Chief Strategy Officer and one of the founders here at CoFactor. A little bit about me came from sort of an arts and technology background, got into a lot of solutioning around engineering and hardware, ran a lab with my co-founder, Matt, and then fast forward a few years and we're working in manufacturing and we founded CoFactor. And CoFactor is supply chain risk management and traceability. We're a platform that's used as an end-to-end solution. This is part selection, procurement, management of materials, kitting, and this is for critical industries. So we got A &D, medical technology, automotive, robotics. Thrilled to be joining you today and sort of announcing that we actually just closed a round of just shy of $18 million to keep doing what we're doing and to continue to expand our offering for people working in those industries. Judy Warner (01:16.546) Well, congratulations. I heard the news and glad to hear that's gone through. And one thing that's been fun to watch with you and co-factor that, you know, AI and LLMs and the way all of this is going to affect the way we source and buy and just overall the engineering workflow, it's here. It's here to stay. And you guys are sort of leading the charge and Phillip Gulley (01:39.295) Mm-hmm. Judy Warner (01:42.944) you can see the response in the form of the investments that you're getting. So congratulations on another round. So you talked about co-factor as a whole. So let's unpack kind of where you are since the last time I talked with your co-founder, Matt. So let's talk about what does this mean for EE's and people that are in our audience, right? That are designing and sourcing parts, which is you know, can be a really unpleasant part of their job. What does a platform like CoFactor do for them? Phillip Gulley (02:17.865) Totally. So what we have always done and what we are going to keep doing with a lot of pride is helping with sort of the procurement strategy and the management of materials. So that's just like part and parcel. have a ton of really high quality data that we're using AI and aggregating and sort of providing that for our customers so that they can get to really great procurement strategies right away and then manage that procurement process, both in sending POs and managing vendor communication. for their custom components and for commercial off-the-shelf components. And so that's a big sort core value is just, we have what we need? Are we sourcing it from the right places with the right compliance concerns? Sort of the benefits of that for our customers is if they are working in a high compliance industry, are those materials coming from the right country of origin? Are you getting them from authorized distributors? Are you managing that correctly? Judy Warner (03:13.677) Hmm. Phillip Gulley (03:16.757) And then there's the whole AI side from the management of those materials and those communications, which gives you great forward and backwards traceability, which is huge, especially in high compliance, where if you have any issues that can really have a big negative effect. If you can't track back to, was it a vendor that I had a challenge with? Was it an individual stock lot? And so that's where we're really, really seeing some big impacts for our customers is making sure that they get to manufacturing successfully. And then if there is an issue, understanding right away, hey, what is affected, what in the field is affected, what could potentially be affected. And that's taking what could be engineering questions that turn into engineering nightmares that can take up weeks of time and really have negative impact and just turning that into, I know the solution, I know it's affected. So a lot of big impacts for our customers. Judy Warner (04:12.906) What I hear is a lot of visibility and no surprises, which engineers absolutely hate. And as you mentioned, when it comes to mission critical or health critical industries, especially like A and D and automotive, they're both so heavily, the compliance and the traceability are huge in both those industries. So it's interesting to see the way that you guys are leaning into that. So that's sort of where you are today. Phillip Gulley (04:16.636) Exactly. Phillip Gulley (04:36.511) Yeah. Phillip Gulley (04:39.945) Mm-hmm. Judy Warner (04:42.702) What are you guys looking forward to? We're getting towards the end of 2024 here and about to round the corner into the new year. So what's on your roadmap and what are some things that you're hoping to do over the next year? Phillip Gulley (04:54.953) Yeah, totally. So, that value of sort of backwards traceability. And so right now we're really solving the problems from component selection through manufacturing. What we've realized is beyond that point, when you do have systems in the field, continuing to understand that traceability is huge. so thinking about clear to build where those systems are deployed, what's affected so that you can get ahead of MRO moments, right? So when you do have that maintenance, those repair moments that you can keep those systems in the field and operational at a maximum capacity and not have these kinds of moments where you go, no, we had an error. We have to recall a system, right? Because that downtime can be huge. And so now we're shifting from like, we're, you know, we're helping you get to manufacturing. Now it's, are actually helping you with keeping those critical systems operational, getting ahead of those challenges. So Judy Warner (05:28.142) Mm-hmm. Judy Warner (05:39.36) Right. Huge. Judy Warner (05:50.274) Yeah. Yeah. Phillip Gulley (05:52.399) really big stuff there on top of, you know, a lot of like AI magic that I'm happy to dive into. Judy Warner (05:58.222) Well, as you said, I've worked a lot over the years with aerospace and defense companies. And as you said, not only are those MRO problems really nasty problems, but the amount of money they cost is staggering. I've heard some of those numbers on some of those systems. So, you know, there's a lot of talk. Phillip Gulley (06:17.769) Huge. Judy Warner (06:27.518) about both obsolescence and then we'll dig into this a little bit later about you know with COVID and hopefully our rearview mirror you know getting insights there and I know that's something our audience cares a lot about and Philip I was talking to someone recently and he was with an assembly company and he says we want to avoid parts that are made with unobtanium. Phillip Gulley (06:37.877) Yeah. Phillip Gulley (06:55.571) Yeah, yeah, very much so. Judy Warner (06:56.462) So, how are you looking at that as well as the traceability part as you move ahead? Phillip Gulley (07:04.181) Yeah. So, life cycle monitoring is huge. And what we've seen in the last few years is, predicting end of life of components used to be pretty reasonable that there are tools that out there that would say, Hey, you've probably got six years on this thing. And manufacturers are starting to shift more than they were previously. so watching those PCNs saying, Hey, we've got a product. Judy Warner (07:19.886) Mm-hmm. Right. Phillip Gulley (07:31.273) that is not recommended for new designs. We're in last time buy, we're in end of life, right? This is huge, hugely important stuff, especially when you're thinking about building out product and sort of scaling that product and qualifying that product for the market. If you're doing that with parts that you can't get in the future that unobtainium, you're really in a bad place. so getting ahead of that is tough. There's a lot of communication that's coming from component manufacturers. Judy Warner (07:53.452) Right. Phillip Gulley (07:59.369) And in really high compliance industries, that might be coming traditionally through a manufacturing partner, but you might be more in batch production, right? And so these kinds of challenges of how am I understanding as an engineering organization, what my challenges are going to be in the near term or in the long term for a more mature product. And so we're doing a lot of work. Like I mentioned that we do a lot of vendor, vendor communication management with AI. Judy Warner (08:05.88) Mm-hmm. Phillip Gulley (08:29.27) We're doing the same for part change notifications. So when we get the product change notification that PCN that lands, we're actively gathering those. We're tracking those. We're alerting our customers so that when you have that obsolescence concern that might pop up, you're way ahead of the game when there's still material on the market when you can last time by that. And then proactively saying, hey, parametrically, we understand a lot about what your product is. Judy Warner (08:36.334) Mm-hmm. Phillip Gulley (08:58.229) how do we use AI in a really deterministic way so that you can work with AI to say, look, I can't have any hallucination, right? I can't have any pretend information about the nature of a part that I'm thinking about putting in my product. And so one, you get those products in hand that you need to keep manufacturing. And then what's that next step? You got to re-spin a design, have to swap out a component. How do you get to a really good solution, a really good part selection with Judy Warner (09:07.095) Yeah. Judy Warner (09:12.845) Yeah. Phillip Gulley (09:26.799) Absolute industry best tools and that is a big data problem. It's AI helping you navigate into the right component and then giving you a really clear understanding of, we've gone from a essentially infinite issue, right? Of like, can't make my thing to, have a few really good options that then I can take as an engineering organization, evaluate and come to a really good solution quickly so that obsolescence isn't a problem now. And it's not a problem in the future. Judy Warner (09:57.496) How do you keep from the trap, how does co-factor lean into making sure that there is no, say, LLM AI hallucinating or maybe they're pulling from a bad data source? Like, what does that look like practically? Phillip Gulley (10:10.068) Yeah. Phillip Gulley (10:14.581) So it's best in class data and it's being really intelligent about how we use those LLMs. So as opposed to, I've got this copilot, it's reaching out into the internet and it's sorting out things and it's trying to figure out what the best solutions are from its knowledge base. We're providing it a really reliable knowledge base. So we're pulling out of data sheets, we're deduplicating, normalizing data and sort of presenting our knowledge base. that is a lot more deterministic. So when we're talking about large language models, they're not just like reaching out and saying, Hey, I read something on the internet, right, which is effectively what that is. And I think that it's a good direction. We're using sort of a limited knowledge base that we know is deterministically accurate. And then one, we're not telling you definitively what you should do, right? Engineers like engineering and they're great at it. And we shouldn't be telling them. Judy Warner (10:44.525) Okay. Judy Warner (11:06.423) Right. Phillip Gulley (11:09.269) how to engineer or what parts to choose. What we should be doing is taking what is a huge body of data, a huge number of potential parts and getting them into a situation where they really understand what are the things I should be considering and then quickly using their incredibly capable brains to make the really intelligent strategic choice. And so we think about it as just start with really good data, use those LLMs to... Judy Warner (11:30.092) Right. Phillip Gulley (11:38.677) get to the really important data for what you're trying to solve, and then hand you that sort of on a plate so you can make a really excellent strategic decision about what you're doing with your products. Judy Warner (11:50.796) I think that's a fear for a lot of engineers is that we'll pull from the internet, you know, and that it will give us bad data. But, but while I've been working on this podcast series, you know, talking about the AI design, engineering revolution, one thing I've been excited to learn about, and it's exactly what you're talking about Phil, is that really companies are, are using, scrubbing the data to produce reliable data analytics and Phillip Gulley (11:59.455) Totally. Judy Warner (12:20.398) So they're not just taking that raw, you know, they're really tuning it and making sure it's accurate and it's tuned for the application before it hits people in our audience. So then it becomes the best, the best, best in class tools. you know, I think you guys really have your work cut out with you working in sort of the, the high end of the market, which is the mission critical. Phillip Gulley (12:24.693) Mm-hmm. Phillip Gulley (12:28.852) Yeah. Judy Warner (12:49.518) places that really everyone is struggling with. So what else do you, are you looking forward to? think we talked before the podcast about things you're leaning into when it comes to not just, mainstream components, but also perhaps some, passives and things like that. What, where are you headed as far as expanding, what can be seen and accessed reliable, reliably on your platform? Phillip Gulley (13:27.177) Definitely. so passives are a great example of something that in a, in a manufacturer's library, it's really easy to take for granted that, you've got, you've got 10 options. And when those end of life challenges pop up or when multi-sourcing challenges pop up, and this gets back to the data, right? Even on the simple components, you can kind of take for granted that like, you know, and my internal part number has 10 options. That's fine. And all of a sudden that boils down to two and then one blips out of existence. then you're like, no, no, no, no. And so how do you, how do you use data to get to a better solution? talking with a customer, this is a really good example was like, it's a passive, right? It's a, it's a resistor, parametrically pretty clear. If you can give me a reliable manufacturer, a reliable distribution channel and give me 30, 40 options on that passive, right? And let me sort of peruse and make sure that that's right. Judy Warner (13:59.653) Right. Phillip Gulley (14:23.935) But how do then you track that information, right? Because, because there is a lot of data out there and it is hard to say, you know, what, what, what, what does risk mean? Is risk the lead time to getting apart is risk a life cycle change is risk, how many places I can buy it from and all of those things are risk. And so taking sort of a library and on the passive side saying, you know, here's a lot of options. So here's, here's a whole menu for you to sort of peruse and approve. And then let's get that back into your library. So that internal part number is really, really resilient, is really strong and then continue to monitor that. So if there's any negative surprises, we can get ahead of them. So when we think about the passive stuff, right? Like there is an opportunity to make some quick wins and really keep a lot of your library much more resilient to supply chain challenges on top of the, Hey, here's the ICs, you know, this is where the engineering brain really comes in and you're really solve the big problems, right? Judy Warner (15:05.176) Yeah. Judy Warner (15:19.959) Mm-hmm. Phillip Gulley (15:22.805) To your point, there's a lot more than just those complicated parts and making sure that your whole library is healthy and that your product line is really ready for manufacturing on demand when it needs to go to the line. That's all part of the very important picture that we're involved with. Judy Warner (15:42.062) Well, you just brought out a point that we hadn't discussed before, but I know will resonate with engineers is the value of a healthy library. know, huge, right? And they can get really messy and all of that. And that you, your platform can help keep that library really clean instead of them having to do that manually or yeah, that's a, that's a big win. Phillip Gulley (15:51.221) It's huge. It's huge. Yeah. Phillip Gulley (16:04.905) Yeah, yeah, definitely. mean that. Phillip Gulley (16:10.493) Yeah. Well, we're squeezing a lot of types of data together. So you have, you have the parts library, you have sort of the internal part numbers, you have the engineering data, then you have sort of public data, right? Which is these PCNs, there's parametric understandings of what the parts do. There's supply chain data. And there's also manufacturing data, right? There's the manufacturer themselves, that contract manufacturer. And so what are all the needs there? Cause you might, you might know that you have parts that are in your library, they're available. but Judy Warner (16:29.324) Right. Phillip Gulley (16:38.609) Is the attrition model of your manufacturer, are they going to have loss? And you realize, well, we had this in stock and all of sudden you're short and you're not sure why. it's because somewhere in here, there's a piece of data that wasn't considered. And so we're trying to really build that sort of full stack end to end understanding of what the requirement is for manufacturing. Is your data internally healthy? Are you leveraging that best in class public data? And how do you like move that all around, keep systems of record accurate, right? There's a lot of moving parts in there, a lot of little things that can get dropped. We are sort of connecting and maintaining sort of that process and that level of stability, reliability for our customers. Judy Warner (17:24.686) It sounds too good to be true, honestly, but I know it's not and I've been tracking your progress. When I first spoke with Matthew, Matt and Matthew, I had them on the podcast. One thing I was really impressed by because I have some experience on the contract manufacturing side of the business is how much granularity you guys are looking at the data for example, if there's a part that you know, Phillip Gulley (17:43.594) Yeah. Judy Warner (17:53.592) comes out with a funny reel that consistently you're gonna lose a few parts on the front end, like you know that. And you can give that kind of insight and like they say, the devil's in the details and that you guys are looking at all of these aspects of this issue with that much granularity is very exciting. Phillip Gulley (17:59.935) Yeah. Yeah. Phillip Gulley (18:16.501) Yeah, well, we came from manufacturing, you know, like we ran a line for a year and that's a weird move for something that's like, I'm a risk management and data and da da da. And you go, well, how did you start off with a line? You go, well, you got to start where you start. And so that reality of us sitting there going like, man, some of these parts fall off. if you don't know that, you don't know that. And so having been on the engineering side, sort of helping design and get products to market. Judy Warner (18:20.523) Yeah. Judy Warner (18:36.63) Right. Judy Warner (18:40.768) Exactly. Phillip Gulley (18:46.037) having been on the manufacturing side, like, my God, we bought a real of 500 to make 400 product, but she's a lot of those resistors popped off, right? Like that sort of all of that reality, unless you've done it, it's not inherent knowledge. And so you got to grab it all. You got to grab all of those different points of data and understandings to have a successful outcome. Judy Warner (18:56.022) Right. Judy Warner (19:06.381) Mm-hmm. Judy Warner (19:10.338) Well, what I hear is that you've done the work and you have all the scars to prove it, which is what I say about myself. what I know about bare boards and assembly shops is because I've walked through plating operation and board shops with high heels on, know, for years or, and when you, you know, when you run out of parts or you have to call customers, you learn fast or you can't deliver something. You know, all that school of hard knocks really adds to the depth of granularity, which is going to bring huge value for your customers. And a lot of people are trying to do this in a different way, but I'm thinking you guys are on the right path because you have the scars to prove it. Phillip Gulley (19:58.931) Yeah, we think it's a very boring business model. We're like, why don't we just be all the most boring stuff that happens between docs? Judy Warner (20:06.57) Yeah, but you guys know how much that would have meant to you, both as engineers and a CM, right? And I think it's worth mentioning. Let's talk about how your platform is made available because it touches the engineer who's sourcing the part. It touches the buyer at that company. It also touches the CM. And then somewhere in there, there's you know, field failures. I mean, there's a lot of parts. Phillip Gulley (20:10.762) Yeah. Great. Judy Warner (20:35.138) that you're touching. So how do you go to market? And for our audience sake, you know, give us some case studies of what that looks like so we can wrap our heads around that. Phillip Gulley (20:35.315) Yeah. Phillip Gulley (20:47.669) Yeah, it's challenging, Judy. We are a strange company. I say this all the time, that one of the biggest challenges that we have is it's easy to get lost in the sauce of what we offer. That you can be talking to a buyer and they get excited and they're like, let me get an engineer on the phone. And then you're like, actually operations might be into this. then it's had the production. And all of a sudden you're like, how did we get here? And I think the main thing is that... Phillip Gulley (21:15.177) We are thinking about this in a pretty full stack way. And that might seem really opinionated. That might seem like we're kind of like demanding how a procurement team might operate or how an engineering team might make products with part selections, et cetera. I think what we have done is we've built an end-to-end solution so that we can solve problems really actively for our customers. if you think about, or if I think about certain customers that we have that are in automotive, Judy Warner (21:18.455) Okay. Phillip Gulley (21:45.415) their concerns are really about making sure that that NPI process is squeaky clean and that the parts that they're selecting are resilient, right? Because what might be 200 PCBAs today needs to be 20,000 in the future. And so their use case is really about analyzing risk long-term, understanding those implications, and then automating that new product introduction phase, right? Judy Warner (22:00.974) Mm-hmm. Phillip Gulley (22:13.671) A great use case. have other customers who are in med tech and they want to dramatically reduce their risk. They're going to market, they're at scale and they really want those critical components physically managed and then shipped to their CMs so that that CM can fill out the bill of materials and they can keep delivering to the market at really high volumes. That's also a great use case. and you know, you, you look around and you go, okay, well, what does it mean? When you do have engineers, have procurement, you have production, you have CMs, right? We absolutely have customers where this is a collaborative environment, the source of truth for the bill of materials, so that when changes come in, everyone's aware of it. There are a lot of use cases in here. And so like the word platform, very carefully chosen because we are not a point solution. We're really stitching together. Judy Warner (22:55.064) Mm-hmm. Judy Warner (23:08.973) Right. Phillip Gulley (23:11.241) where you need or could benefit from that sort of automation, right? And so, so whether it's a procurement team who just wants visibility, what's running late, let me put my eyes on that. Let me resolve those problems. But the other thousand lines that are running fine, just keep that locked in. I want documentation, but I don't want to think about it, right? So many ways that we do this, that it can be really challenging to figure out, you know, Judy Warner (23:33.304) Right. Phillip Gulley (23:39.315) Where does it fit? But I think the easiest way to think about it is wherever we fit, we're reducing risk and we're trying to be a system of action that supports your systems of record. And so when you're thinking about traceability, when you're thinking about procurement, we're not here to tell you how to do your job. We're here to let you be more strategic and keep you from having to sort of like dig in and say, man, it's like, look, Judy Warner (24:01.976) Right. Phillip Gulley (24:07.401) We didn't manage those POs correctly and now a vendor cut us off because we can't get payment out. Like that shouldn't be your problem inside of an organization. It's, and it's all over the place. is admittedly all over the place, but, complex problems sometimes need complex solutions. Judy Warner (24:15.277) Right. Judy Warner (24:23.71) Right. Well, I'll let you close with a story that I think Matt told me that I really liked as a CEM aerospace and defense professional about what it can look like when you do have a field failure and what that traceability looks like instead of weeks and weeks and weeks of Phillip Gulley (24:39.605) Mm-hmm. Judy Warner (24:48.856) playing whack-a-mole and try to find out where the data is. It's in a physical folder, it's digital, and who touched it last. So why don't you close with that story? Because I know I need to let you go soon. Phillip Gulley (25:00.645) Sure. Yeah, so we had a customer. We had been working with them for a couple years and they were scaling as an organization brought in just top notch supply chain management came from an organization that is renowned for their management of supply. I mean, really like an incredibly skilled person who when we when I first spoke to them, they said, you know, this isn't necessarily the thing that I would have chosen. Judy Warner (25:20.974) Mm. Phillip Gulley (25:30.485) I don't know if I would have chosen co-factor, but the founder did. so here we are. Fast forward a few weeks and they had an error and that error was unclear to them what had happened. They weren't sure if it was a counterfeit issue or if it was a failure of a component. So, you know, we get a panic call. Hey, we don't know what happened here, but you guys are helping support our supply chain. We need to get this resolved right away. In the system, we were able to track the materials that were procured, what facilities they had moved through, what facilities they had landed in, and then the transformation of those into serialized product. And we could identify exactly where the pain point was, which was there had been a swap of a component at a previous manufacturer that basically led to wrong part accepted as the right part. Judy Warner (26:18.339) Wow. Phillip Gulley (26:27.313) Now that's annoying for sure. Nobody likes that story, but understanding what happened right away allows you to really understand where in that tiered supply chain, there was a challenge in that tiered manufacturing process. There was a challenge and understand, these are the units that are affected. It wasn't a counterfeit issue, which is huge, right? That you don't have compromised fundamental hardware. And so that's a, that's a moment that, Judy Warner (26:47.714) Right. Phillip Gulley (26:55.337) we were really happy that we could support that customer and get to a resolution immediately because that's the kind of thing where you go, don't know what happened here. That can halt all your production. That can sit you on weeks of calling up different vendors and saying, I need to see the documentation and the materials that you received and where are those CFCs and who do we buy it from? And all of that just lives natively inside of co-factor that lets you get that backwards traceability that is Judy Warner (27:07.468) You bet. Judy Warner (27:12.856) Mm-hmm. Phillip Gulley (27:24.637) hugely important for when those errors do happen. Judy Warner (27:28.298) and within hours, not weeks, without it going on hold, which I'm sure they were. So I bet you made a believer out of that person that said they weren't choosing CoFactor. Phillip Gulley (27:30.93) Exactly. Yeah. Phillip Gulley (27:40.665) It was really nice to get on a follow-up call and have a, you know what? You guys are pretty okay. Judy Warner (27:45.934) Well, that's good. You went them over. well, any last thoughts before I let you go? Is there anything we missed that's coming up on your roadmap that I might've not asked you about, Phil? Phillip Gulley (27:50.793) Yeah. Phillip Gulley (28:01.525) Yeah, I think I can slip this. think I can say one more thing. We've been really proud to solve a lot of problems in electronics. And we had customers that if you think about a very electronics heavy product, sometimes you go, you know, 80 % of my problem is electronics, the other 20 % is everything else. And having two systems of sort of record for electronics and everything, not electronic, Judy Warner (28:06.06) Okay. Judy Warner (28:11.618) Mm-hmm. Phillip Gulley (28:31.145) That's a, solving 80 % of the problem solves none of the whole problem. Right. And so we're expanding into a sort of all categories for direct spend. And that's been really huge giving sort of one place where, you know, we're already taking a lot of commercial off the shelf data. Now we're taking quotes, we're sending out quotes, we're getting back offers from custom components, mechanical components, aggregating that data. And so, Judy Warner (28:36.461) Right. Judy Warner (28:57.815) Okay. Phillip Gulley (29:00.841) We're really thrilled that we have customers today who are using us for all of their direct spend and those products that they're putting in the world were entirely managed through co-factor. And so that's a really exciting thing that allows us to keep helping those critical industries in a more complete way. Judy Warner (29:19.274) Mm-hmm. Yeah, from a systems level. You know, that's amazing. Well, I'm glad I asked you for that last little nugget because that's a big one. And if I'm not mistaken, one that's not offered, or at least not in the way that is cohesive. So I think there's a big win for you there. Phillip Gulley (29:23.473) Exactly, Yeah. Yeah. Phillip Gulley (29:31.326) Yeah. Phillip Gulley (29:42.835) Yeah, yeah. Well, the weirdness of being end to end and just going like, I guess that probably should be the whole system. That's kind of seems obvious in retrospect, but you you got to get there somehow. Judy Warner (29:50.424) Yeah. Judy Warner (29:55.096) Phil, the 90s, we've been talking about, gotta get out of silos. But what's been super fun to me is watching you, all of you that are much younger than me, all these entrepreneurial kids that grew up on software and, you know, they're digital natives watching the breakthroughs that you're making for the industry. So a big congratulations from me and congratulations on your latest. round of funding and I hopefully will see you guys at DesignCon and hope you'll come back in Q1 and tell us more about what you're up to and what you're adding on to your amazing platform. Phillip Gulley (30:27.095) absolutely. Phillip Gulley (30:34.993) We will be thrilled to Judy as we always are. Judy Warner (30:38.434) Well, thanks for joining me today. Thank you. So for our audience, I hope you really enjoyed this and I hope you appreciate that I've brought you Phil and the co-factor team to talk about the interesting work they're doing that is leveraging AI and LLMs and so much more to make your workflow just so much easier. And I encourage you to go, I've put their website in the show notes, go do. Phillip Gulley (30:41.023) Thank you, Judy. Judy Warner (31:04.482) Go check in with them there, contact them if this sounds like something of interest and just check it out. We will see you next week. Until then, remember to always stay connected to the ecosystem.