Judy Warner (00:01.16) Hi, Matthew. Thanks so much for joining us today. I'm excited to share you with our audience and talk a bit about co -factor. Matthew Haber (00:08.888) Thank you for having me, Judy. Judy Warner (00:10.48) Yeah, my pleasure. Well, why don't you start out by giving a brief overview of a little bit of your technical background and then a bit about how you founded CoFactor. Matthew Haber (00:24.694) Yeah. So my co -founder Phil and I have a bit of a non -traditional background if you go back far enough, but more recently ran a product design contract, research and development and engineering services firm, worked with a bunch of customers across automotive and medical devices, consumer electronics. We sold that company, spent some time working with essentially big tech companies on systems integration strategy. And then went off and started a contract manufacturer. we had some some pain points maybe of our own related to our experience getting circuit boards made. And so we started a quick turn contract manufacturer and started building software for that company. ultimately co -factor sort of evolved that of the software and tools and sort of service that we were building on the supply chain management and inventory management side of that contract manufacturer. Judy Warner (01:14.728) Well, I'm going to dig in at the end about your origin story, because I think our audience would love to hear it. It's very interesting and very non -traditional, maybe the most non -traditional I've ever heard, but it's really fun. But let's jump right into what it is exactly that co -factor does and what kind of technology problems you're trying to solve and how that ends up being a benefit to both engineers and the industry. Matthew Haber (01:41.784) Yeah, so cofactors used by contract manufacturers for circuit boards and wire harnesses and electrical engineers and procurement and inventory teams at hardware manufacturers. Most of our customers are in what we would call critical industries. So aerospace and defense, medical device manufacturing, et cetera, building complicated, often regulated products that have a lot of electronic components in them. And our tool is used really to automate everything from a bill of materials through to delivery of those parts to the line with a real eye towards how do you connect the data and the flow of materials between these different functions between engineers and distributors and contract manufacturers. So that overall the outcome is getting to market sooner and building more resilient supply chains. And that really goes back to the beginning. So it's giving tools to engineers that help them get back the portion of their time that they might be spending on. procurement and prototyping related activities and giving them the information they need to select components with kind of a supply chain resilience awareness without having to turn them into procurement professionals, letting them still focus on being engineers, but the design kind of like supply chain friendly products. And then from there, empowering their colleagues in procurement and inventory management to actually go execute on those designs and build them both from unit one through scale in a cost effective, efficient. sort of supply chain safe Judy Warner (03:05.554) Yeah, obviously supply chain resiliency and security became a big deal during and post COVID. it seems like you've come around at just the right time. why don't you break down because you have a really unique model that covers, like you said, procurement, even some sort of distribution and giving that sort of that visibility across multiple domains. So can you unpack that a little bit for our listeners? Matthew Haber (03:39.542) Yeah, maybe let's look at kind of just like an example of how a given customer might use this, right? So the process will start when they're picking components to go in their designs. And so at that point, they might integrate co -factor with their engineering software like Altium or Cadence so that they can view supply chain data while they design. And it's going to go past sort of traditional, you know, the supply chain that you can find online because it's going to be what we call demand aware. So it's going to take information about their organizations approved vendor lists, how much of this product they're planning to make, what are the compliance regimes they need to work within and the traceability requirements they're going to need to have, what manufacturer they're going to use, all these kind of factors. And the system is going to give the engineers the information they need to pick components that are going to meet those requirements without having to dig too deep into the details, right? It's really going to give them this kind of like thumbs up, thumbs down about these parts meet your requirements or they don't. Once they've picked those parts and gotten to build materials, it's going to essentially be handed off virtually. through our platform to procurement teams. That can be procurement teams that work at their company or can be folks who work at their contract manufacturer, if that's how they've constructed their sourcing strategy. At that point, our tool is going to really automate all these kind of like traditionally labor intensive manual error prone processes around taking the hundreds or thousands of parts that go into each design, figuring out which distributor to buy them from at any given time, managing all those sort of quote requests and pricing workflows. generating purchase orders, managing open order status management. And so that's a big one we see as a lot of our customers use long lead time parts where there's quite a bit of finesse involved in getting everything to land on the right day without having lots of materials sitting around, but also understanding like these things might take a while to come in some cases. so software really kind of manages all of that for them. Ultimately the parts show up at their typically contract manufacturer's facility. And at that point, our software is also involved in managing capturing traceability information. certificates of conformity, all that kind of like quality management side of it. So you really have this closed loop so you understand, are we having problems in the field with the parts we picked? Are we complying with our regulatory requirements from the FDA or FAA? And so it allows also all of those kinds of traditionally pretty unpleasant and painful quality management processes to be sort of abstracted away from the team as well and managed for them, where they still have all that kind of visibility they want to drill down as deeply as they need to. Matthew Haber (06:07.502) and because it's all this, what we call a closed loop, the initial data that the engineers are interacting with is always being kind of like recalibrated and updated by what's happening later. Right. So that can be inputs for their own team. If their demand plan changes, that's going to change what the engineering considerations are. If all of a sudden, rather than making 5 ,000 units next year of your product, you're making a hundred thousand units that might have some implications like component selection. And that's going to be flowed up to the engineers, as it happens, but also. what's happening in the broader world, right? So if a given set of distributors are giving component manufacturer, all of a sudden is having kind of on time delivery problems. That's something that we're going to know because our system is tracking all of that data all the way through the kind of execution. And all of our customers then benefit from kind of that ever evolving and sort of progressively more accurate set of information around, you know, how these different suppliers are Judy Warner (07:00.828) I have many questions because there's so much to impact there. But I want to keep an eye to our engineering audience. I worked, I think I shared when we met that I worked for a couple of years for a Mill Arrow CM out of the Baltimore area, selling on the West Coast. And when you say the saying, the devil's in the details, I had no idea until I worked there how many. Matthew Haber (07:02.956) Yeah, lockdown back. Judy Warner (07:30.704) idiosyncrasy like details there are and things like having parts sit on the shelf, like how that can kill margins that are already slim. And there's just so many moving pieces, but a couple, I wrote myself a couple of notes here that I want to ask you about that. So first of all, early on, you said that your software integrates with EDA companies like Altium and Cadence. So is that done like through an API or so? So yeah, how does that functionally plug in or integrate with those EDA tools? Matthew Haber (08:08.028) Yeah, that's typically right. So Altium is a great example. We have a long partnership with them at this point. And so they have their Altium 365 product, which is their cloud product that is sort of a companion to the desktop app, right? They would now describe this kind of a broader ecosystem. And so in that case, that's right. So they have APIs for that. We integrate with those. so if customers that use Altium 365 and use Cofactor can link those together, and then we can push data into the 365 environment, we can pull the BOM data out of 365 so that they can also then go into Cofactor and see data. And Cadence has a similar cloud platform. It's similar. Judy Warner (08:44.904) which is so great because they don't have to leave the tool, right? And they don't have to mess with spreadsheets and all of that. can, to have that integration, you know, is an industry trend. And so that's very cool to see that it's available inside ED tools that engineers are already in, right? So, and you mentioned also, like if a distributor is starting to run late Matthew Haber (08:49.762) That's exactly right. Judy Warner (09:13.99) or say a part gets flagged for end of life, how do you gather that data and then sort of suck it up into co -factors so it notifies the procurement or engineers, right? Matthew Haber (09:25.361) Yeah, great question. Yeah, so there's a couple of kind of ways. One would be the customer data, right? So a distributor running late on a part that you've ordered. We're going to pull that from some distributors via their APIs, but a lot of distributors don't have order status APIs. And so for those, there's what we call like an AI email inbox. So essentially we'll hook into our users email inboxes, or they can use one that our system provides. And all the emails that are coming from distributors, our system will analyze the contents of the email, the contents of PDF and spreadsheet attachments, those emails, extract the relevant data and link it up to the rest of their data set. And so it's this sort of AI powered email assistant essentially that runs in the background. It's really specifically designed for these kinds of suppliers and documents. There's a lot of uniquely challenging qualities of the documents electronic component suppliers provide. And so there's some very like sort of specialized technology there to make it work for these kinds of like specific documents. And then the other side of it is like public documents, right? So product change notifications, like an end of life notification is a great example of that. Those we often collect directly from the component manufacturers or from the distributors ourselves. So we have integrations and relationships with hundreds of distributors, with a lot of component manufacturers. where we go and get that ourselves. So it's not necessarily incumbent upon our customer to be getting those emails at all. In the case of something like an end of life notification, we generally speaking try to go off and make sure we're proactively collecting those, extracting all that data, analyzing those, and then putting those into our data set of hundreds of millions of components. Judy Warner (11:04.872) This is very exciting and only a tiny bit creepy that you can look into people's emails. But I mean, these are the kind of enablers, right? And it sounds like you guys are out there, I saw it on the front end, using very specific parts of AI, right? To track permissioned looks into that data all the way into people's inbox. Matthew Haber (11:28.374) Yeah, that's exactly right. And so I think it is worth noting, like, you know, our customers are largely in aerospace and defense and other regulated industries. This is all done in a ITAR compliant way. There's a, this is another reason why you often can't apply some of the more general purpose, you know, invoice processing tools or things like that, that are out there. Those are not permissible from kind of a data security export control perspective. And so, you know, I The way we approach these kinds of things like the email inbox, it's really heavily controlled by the user. What data is exposed to the ConeFactor platform? Then even the data that is exposed is processed in a government compliant cloud region. There's a lot of data security around how all of that works because a lot of our customers are building things that you can't just send to OpenAI and have that be Judy Warner (12:22.082) Right. Yeah. I figured, I figured if I asked you, you would have an answer because you've been so meticulous about everything you're doing, but it's, again, it's a really novel and interesting way to get data in non -standard ways that is, that you guys really have done in a very unique way. The last thing I wanted to ask you about are the questions that came up when you were unpacking some of that was, well, the other integration I wanted to ask you about is, how do your customers integrate, say, cofactor directly into their CM? Matthew Haber (12:57.368) Yeah, it's just a couple of ways. One is some contract manufacturers use co -factor themselves and our software is designed that if your contract manufacturer is co -factor and you use co -factor that unlocks some collaboration data sharing type opportunities and visibility opportunities, which is great. For the folks that don't, it can look somewhat similar how it is with other suppliers, where it's about pulling information out of emails and things like that. Or customers can give kind of read -only or limited access to their co -factors and to their contract manufacturers. We also see some cases where folks give their CM partners access to interactive inventory data, to direct with supply chain data, to view and extract BOM data. And so they have co -factors kind of the shared source of truth, but they can securely Judy Warner (13:25.181) I see. Matthew Haber (13:49.554) and in their control kind of share some of that information with their contract manufacturer. That's also a great option. Judy Warner (13:57.246) And then also you mentioned how you can enable traceability to standards like ITAR or the FDA or any other compliance. and how do you, that's another, like, how do you do that through accessing your customers or the CM's database? Like, how do you pull out so you have that full traceability? Matthew Haber (14:09.292) Exactly. Matthew Haber (14:24.288) Yeah, so a couple things there as well, right? Part of it can be like integrating with customers, ERPs or other systems that maybe have some of that information. In a lot of cases though, they don't have that information to begin with. Like they have not been capturing it adequately or it's in physical paperwork and file cabinets is like a very common one, right? So we integrate with like literal document scanners, the same AI that works on emails. Judy Warner (14:36.626) Hmm. Yes. -huh. Matthew Haber (14:48.076) works on physical paperwork. And so that's very common that our customers, their receiving stations, incoming material stations, will have co -factor connected document scanning, where all the packing slips and specific conformity and stuff are being fed into those. And our system then deals with, again, extracting them, linking them up to the correct items, tracking that through the stock lot level. At the sort of ideal extreme, we again, we have contract manufacturers that use co -factor in the warehouse. Judy Warner (14:59.058) Mmm. Matthew Haber (15:16.97) in the main, on the manufacturing floor to actually track the barcode scanning, all that data as the materials move down the line. And so that is sort of the ideal level where we really have that like true sort of ultra granular and to end traceability. but it can always be some hybrid of any of these, where it's some of the data is coming from, from their manufacturing execution system. Some of it's coming from our incoming materials receiving, some of it's coming, you know, from some other third party system they have. our system is really designed to be sort of extremely flexible about how it stitches together these disparate pieces of information to build one sort of validatable, coherent sort of thread of data. Judy Warner (15:59.918) That granularity as we've spoken just one other time is what has so impressed me about the abilities of co -factor. So good for you guys. It's amazing that you can get that much integrated information packed into one tool. So how long has co -factor been in business and how is the market sort of, you know, both from the CM side and the OEM side you know, sort of your ecosystem within your different customers. How are they responding and tell us how long you've been in business? Matthew Haber (16:38.382) Yeah, we've been around three, a little over three years at this point. And we have several dozen customers, you know, ranging from sort of hip early stage startups building satellites to companies like Waymo and Amazon. So on the larger end, And, you know, as you might imagine, sort of our product is something that requires a lot of trust. And so it's gotten easier and easier over the three years to get folks to adopt this as part of their workflows. But broadly, I think we found that there's a lot of folks in the industry who are really excited for new solutions, who are really like aware of and recognize how acute these pain points have been for themselves. so, you know, broadly, we did met with kind of a lot of excitement on the distributor and component manufacturer side. That's where we've been seeing. I would say kind of increasingly accelerating excitement of late with a lot of those folks also coming to us and saying, Hey, we have our own pain points around this data. We would like to figure out how we make both life easier for our mutual customers, but also how can we kind of learn from what co -factor is doing and learn from the information co -factor as available. So I think that's also kind of a new forefront in industry excitement, which certainly was not happening three years ago, but we're starting to see a lot more of recently, which is exciting. Judy Warner (17:55.152) which is, you know, that's the real world where the river meets the road. So I imagine that that kind of collaboration is invaluable in both directions actually. So you also, I don't know if you mentioned it or not the first time, but the one thing I was intrigued about is that you were also setting up sort of, I don't know if you'd call it a fulfillment center or, but like physical spaces where you have the ability to stock parts. for customers, can you unpack that a Matthew Haber (18:27.158) Yes, we provide what we call third party logistics for electronic components for our customers. We're not a distributor in any sort of traditional sense. We don't own any materials. We don't buy and resell materials. But what we do find is that often there's some sort of like real world steps that have to happen for customers that there may be just not physically equipped to deal with themselves. That can just be an issue of kind of timing, right? So what we sometimes see is folks want to get ahead of potential disruption. They want to buy more materials than they need today. or buy materials that are shorter lead, but they're not convinced, you know, they'll be able to get in the future while they wait for longer lead parts to come in. And they need a safe place to store that. They need a place where they are confident that all the traceability and regulatory requirements are being met, that they have complete confidence that when they go to use those parts down the road, they're going to be available. And what we see is lot of customers, maybe they haven't decided who their contract manufacturer is going to be or who the EMS is going to be at scale. So they don't have that resource base to do that. Maybe their EMS or CM doesn't want to do that for them for various reasons. Maybe they have in -house warehousing, but it's not really equipped to deal with electronic components. doesn't have the, know, moisture sensitivity handling capabilities, doesn't have the ESD handling capabilities. They, we've seen a lot of customers where they're in -house warehouses, you know, lose chips and stuff. And that's obviously not good. And so we do provide this sort of software integrated facility that, that allow customers store materials, have them re -realed, have certain inspections performed, all in a very sort of traceable, quality managed environment. Also handle some other stuff like bonded imports and exports. So there's some kind of more niche, kind of global trade considerations that we can help with that can be really important for certain customers. But that's all sort of deeply coupled to the software. So I think that's one of the nice things is customers don't even necessarily have to think so much about I'm going to send it to the warehouse. I have to do this, right? They can just kind of say like, here's where I materials to be and when I need them to be there. And if that involves those materials needing to go to a facility and wait for a bit before they make their way to their final destination, the software is just going to kind of automatically route them that way. Customer self complete visibility. They see what's going on. They own those materials. There's, there's, you know, very deep visibility and transparency about what's happening, but a lot of automation to make it very convenient. our facility also runs on the same software that a lot of our contract manufacturing. Matthew Haber (20:51.918) customers and partners use in their facility. It's the software that we make as part of our overall platform. And so it also gives us the opportunity to really validate and test and hone in the real world, a lot of the software that we sell as part of our solution. And so that's also really valuable in terms of being able to show our customers why the software is really differentiated, right? It sort of doubles in the showroom. It gives us a super tight feedback loop. We're on the phone, you know, on Zoom calls. every day, constantly with folks who work in our facility, getting their feedback about how we can make the software more efficient and shave seconds off of each action and where they have pain points. And that all flows down to our customers. And so it makes the software extremely, you know, kind of performant and convenient to use and really tailored for these customers' requirements. And so it has a lot of benefits beyond just kind of offering the facility itself to Judy Warner (21:45.278) So you briefly mentioned, one, I think that's phenomenal. can see why that would be of value, but something I haven't heard others talk about ever. with working remote and wanting to sort of shrink the physical brick and mortar, can see that sort of as a way station and a go between, but securing those parts in a timely way. Do you guys, is that just mostly a software enabled just function, physical function of cofact or do you do anything you talked about things that have to be bonded or whatever? Do ever get into things like counterfeit mitigation or doing any of that work or do you just hand that off to the CM where it traditionally lies? Matthew Haber (22:35.021) Yeah, we do have an in -house anti -counterfeiting lab. You know, it has pretty standard stuff, reel -to -reel, x -ray microscopes, know, labs do various chemical testing, things like that. it has a fairly, we have a fairly extensively equipped lab. We were founded coincidentally, shortly before a lot of the COVID era chip shortening stuff happened. And so that was a capability we put place pretty early on to deal with a lot of the challenges folks were having a couple of years ago. I fortunately, that lab is getting used a lot less these days, which is how we would like it to be and how it would ideally work. In an ideal situation, you're not really having to pull from that. But we do have customers with additional testing requirements. whether it's LCR testing on passives where they want to know, we definitely got the right value, whether it's other kinds of, you know, checking the screen printing or the laser etching on each chip against what they're expecting. There's all sorts of potential quality checks that customers might want done. And they potentially want those done, not, you know, the minute they show up at the production line and now they're holding up production because you discovered at the 11th hour, they want those inspections done the moment those materials arrive from the supplier so that they can get way ahead of any of those problems. That's an advantage of doing those kinds of inspections before those parts go into storage at our receiving staff. And so those are things we offer for customers that choose to use Judy Warner (24:00.286) Amazing. You mentioned briefly how you're using AI to sort of scrape data in a very laser targeted, safe, compliant way. What are other ways that maybe you're taking advantage of AI to help the software become more intelligent or sort of serve you and your customers? Matthew Haber (24:24.62) Yeah, there's a couple of big buckets. One is kind trend prediction. So we have some features in our software around looking at both kind of historical availability and supply chain trends on a given component, and then using AI to kind of spot patterns in that and predict outwards, right? So examples are, you know, looking for data in those historical data sets around, does this look like a product that's being actively used? Is the sort sales volume, what we'd expect it to be for a healthy supply chain. What is that? What's the impact of that from sort of the probability of this part being end of life prematurely, some of those kinds of like risk factors that we look at. AI can be really useful for that. We also have a whole swath of features that are kind of like an internal alpha right now that we'll be launching over the next few months around alternative component suggestions, AI assisted parametric search. So a lot of tools really to help engineers find the part they want. get there more quickly than they might be able to by selecting specifications one at a time in a distributor's website or something like that. So tools to really help engineers very quickly arrive at the part numbers that are going to meet their requirements. And then once they've picked a part, also be able to sort of accelerate the multi -sourcing process by picking other parts that are going to be formed at function equivalent. So they can have a little more supply chain flexibility down the road. So a lot of capabilities around that are in the works and we're trying those out with some of our kind early engineering, kind of like customer user base and getting a lot of feedback on that and iterating on and getting ready to launch those later this Judy Warner (25:58.93) Hmm. Exciting. So you've mentioned some real clear differentiators in my mind, but I'm thinking about our audience and wondering really what are the very precise differentiators between cofactor and say someone like Silicon experts or Octopart or Snap EDA or the other companies that are taking a look at how to provide intelligence supply chain solutions. Matthew Haber (26:31.192) Yeah. So I think on the sort of what we'd call like the park data intelligence side or that sort of component side, the data side of things, you know, each of these different companies has like some area of strength. Obviously there's sort of a large amount of Venn diagram overlap between Austin Silicon expert and everyone else. Right. You know, you look at Snap EDA, they have this whole footprint, E CAD symbol strength, that like is, they go a lot farther than a lot of these folks certainly ourselves include, right? In fact, we use Snap EDA in our products to give people footprint data. But I think there's a couple areas that we have some strength. One of them is certainly like this kind of real time and historical supply chain price and availability data. I would say we go quite a bit further than anyone else in terms of having really wide coverage of it, but also really high data quality, right? So you look at, know, products Octopart, who we work with, we have a great relationship with Altium, their parent company. Octopart has great breadth, but because all the data is self -reported by suppliers, sometimes it's just not right because they're being given incorrect data. Right? And so we do a lot to kind of deal with some of those discrepancies. You look at a product, so look an expert. They have, you know, maybe better data quality, but they don't cover nearly as many different distributors. And so that can be challenging if you want sort of broad coverage. So think on the data side. That's where we're pretty different in terms of having kind of maybe similar data from a compliance and technical spec perspective to a of those companies, but having, you know, we think much more sort of actionable, immediately usable supply chain data. And then I think beyond that though, really it's like a bit of an apples to oranges comparison. We think of those companies ultimately as primarily sort of data providers. We think of co -factor as a execution platform, right? Certainly, none of those companies really get into the procurement workflows, the document processing workflows, the inventory workflows, the physical warehousing, the warehouse management software, all of that kind of stuff that we look at. That sort of supply chain aware engineering data. So taking engineering data, but contextualizing it with what's your organization's demand requirements? How does that fit into your overall kind of materials and resource planning strategy? There's a whole swath of that side of our product. It's really like 90... Judy Warner (28:37.917) Mmm. Matthew Haber (28:51.298) percent of our product that looks much more like maybe a traditional ERP, but is designed to work alongside those kinds of products. And so we do have some customers that use engineering data tools, like the Silicon experts and know, the IHS markets are accuracy of the world alongside cofactor when maybe they have some really niche specific compliance data requirement that one of those tools is particularly good at. We can integrate with those data sources too. So if you want to use them all together, that's, you know, can be a really smooth and great experience for our customers, but we find most folks kind of get their data needs met with Cofactor, but then also of course get these kind of really massive real world efficiency benefits and sort of outcome benefits with our execution Judy Warner (29:35.462) It's kind of nice that you have the ability to play with others, right? And let the customer choose, right? Rather than pigeonholing them into, I mean, they can and you're hopefully competing on providing the best experience, but you're given the freedom to work, you know, however they want to work. So I think that's pretty empowering. Matthew Haber (29:57.596) Yeah. Judy Warner (29:59.386) You have several, I noticed on your website, have several case studies which are pretty fun. Do you have like one case study that kind of wraps all these capabilities into a win of one of your customers that you sort of have top of mind? Matthew Haber (30:15.543) Yeah, there's a recent one from a company called Neuros that makes North American manufactured drones for governmental and defense customers. And they started working on us sort of unusually early. Most of our customers don't start when they're just a couple of people in a garage, but they very immediately recognized, we don't really want to do any of this stuff. We need this taken care of for us. And so they were kind of an early, very early adopter. in their journey. And now they're in a new 15 or 20 ,000 square foot factory. They're making thousands and thousands of units at a time. So they went from, making one at a time or whatever to making tens of thousands at a time. And I think like their, their chief technical officer really kind of like summed this up awesome in the case study. He said, basically for us scaling is just typing another zero into the quantity box and cofactor. And so I think like that, you know, obviously there's a huge amount of complexity under the hood to make So works that way, right? And they use it as part of their engineering workflows. We're now working with them to integrate into their accounting workflows and all these other things in more sophisticated ways as they scale. They work with contract manufacturers that use co -factor. So there's a lot of like, kind of like real world architecture to make it work like that for them. But I think the overall experience of being able to go from both sort of that initial design phase where they're designing these products with an awareness of how many they want to make at scale and designing products are actually going to be able to be made at scale, right? Not that you can type an extra zero into co -factor and we can magically make any product 10x more sourceable or 100x more sourceable, but because they used us from the beginning, they were able to design products that they really had confidence were going to be able to scale, scale with their cost objectives, scale with their of supply chain risk objectives. And then when they're ready to scale, it's just about saying, you know, make more basically, and having that really automate for them. So I think that's been really exciting for us go along with them on that journey and see how that happens. But it's exactly what we see with lot of customers who adopt us either early in their journey as a company or just sort of early in their journey developing a particular product, right? So we have plenty of customers who have been around a long time, but they start to adopt us into their product development life cycle. And then as those products mature into production, they start to see all these benefits from using us. We see customers all the time, of course, who adopt us at any point in their product life cycle. Matthew Haber (32:38.346) It's still extremely valuable, but you certainly get kind of like all of the benefits when you use us at the engineering phase and then all the way through execution. Judy Warner (32:47.694) Right. It's easier to build something quality from scratch than, you know, doing it backwards. What I like about that story, and I guess my question is, is for a startup like Nero's, does it give them the ability as they're thinking about their ramp and their roadmap, does it give them the ability to sort of forecast? Matthew Haber (33:10.326) Yeah, that's exactly right. So we have tools, whether it's our bomb analyzer feature that lets you basically put in all the potential quantities you're thinking about making for design at the engineering phase. And it helps highlight which areas you need to think more about, which parts are going to be the ones that give you trouble or our program management features, which is sort of the more like, we're actually getting ready to do this part of it. But yeah, we see customers all the time who use co -factor for these kinds of scenario planning, forecasting type activities where they're taking preliminary bombs out of Altium. They bring them into co -factor regularly and they are typing in, we think that if things go well, we're going to make 10 ,000 next quarter. Which parts are going to give us trouble? What do we have to get ahead of? And they type 10 ,000 in and then they can see in red, okay, we don't have to worry about 99 % of the parts, but these parts either, we have to pick different parts. We have to find alternatives. We have to order them now to get ahead of those challenges. And the system kind of gives them all the information to quickly what the right next step is and then the button clicked to actually do that next step so they can go back to designing their product or focusing on scaling their business. Judy Warner (34:15.08) That's phenomenal. I can't imagine how powerful that is for your customers, but will continue to be, especially if they're young in their journey or even if they're not, know, business changes is volatile all the time. Speaking of roadmaps, so you talked a little bit about hoping to have more of the AI implemented by End of Year. What other things do you have on your roadmap and what do you envision you And Phil, how do you, where do you see this going in the next, I don't know, year, Matthew Haber (34:50.995) Yeah, so we just introduced into beta a whole massive new swath of very sort of sophisticated procurement type features, probably not going to be that exciting for engineers. They get to keep using the kind of extremely streamlined, one click by kind of experience that engineers tend to love because they don't want to spend a lot of time, know, slicing and dicing procurement strategies. But for their procurement colleagues, their supply chain colleagues, there's a whole new really powerful set of features that are built based on kind of a year plus of feedback from our mid -sized to large customers that have a lot of folks in those departments who want more control, who want more granularity, who need more sophisticated approval workflows and things like that. So these are features that are really good for our more kind of like mid -market enterprise customers or contract manufacturing customers. But those are super powerful and I think ultimately will help engineers who want to see co -factor adopted at the larger companies they work be able to make the case that this is a tool that is going to work at that scale. A lot of new integrations. So we have a half dozen new product life cycle management integrations in the works right now. We have a half dozen different ERP integrations in addition to the ones we already have in the works right now. So that's a big one that we're seeing is really rolling out a lot more capabilities for customers to stitch co -factor into sort of every possible system or workflow they might want to stitch it into. And also give them a lot more flexibility to tailor those workflows. So there's a new visual workflow builder tool where people can really customize exactly how the platform behaves, what kind of events trigger, what kinds of actions. And again, this is really for customers who are scaling out of that early phase, or already at scale, where out of the box, the platform's gonna do a lot for them, but everyone has slightly unique aspects of their workflows that they want the system to accommodate. And so we're really trying to give customers progressively much more powerful tools to be able to kind of tailor their reporting, alerting, workflow management aspects of the platform. So those are all like big areas of focus that we're seeing a lot of customers excited to adopt. Judy Warner (36:57.502) Well, I can tell you someone that's been in the industry for 30 plus years. This is so exciting. It feels like science fiction, but like I've known for a long time, we got to get out of this very analog print paper that you talked about. you know, I think you, Matthew and Philip, like you guys are gonna, it feels like you're gonna get it done in a more intelligent way. And I think it's so exciting. you know, kudos to you. Before I let you go, I sort of teased to our audience early on about your origin story because I thought it was so fun. So why don't you share briefly about how you and Philip met and tell us a little bit about your educational background. Matthew Haber (37:43.694) Yeah, so both Phil and I have fine art degrees. So we have some of the only kind of like, bachelor fine arts, master fine arts probably in this line of work. I have a background in set design and projection design for the stage. So if you think about like a Broadway show or rock tour, there's screens and visual elements on stage. And so I have a degree in designing those and Phil has a master's in a similar adjacent type of design discipline for the stage. And so we both spent a while, him more on things like rock tours. He worked with folks like Third Eye Blind and things like that. And I worked on Broadway and also in kind of touring music and things like that. And so, but throughout that, we both were very much involved in not only designing these things, developing the technology to make it possible. And you look at kind of museums or retail experiences or theme park attractions, things like that, that are very engineering heavy. We both were very involved in that. And so we met in that space, but ultimately started a company that basically developed technology for those kinds of customer bases. So, you know, again, theme park attractions, things like that, building the engineering elements, the software systems, the embedded control systems, the sensor systems that are for those kinds of industries. developing some of our own product line. were electrical systems, electronic devices that were used for those kinds of things. know, sensor interfaces and things like that. And so we spent a lot of time doing that and that ultimately evolved into our automotive work and our product development work. yeah, definitely a little bit of an unusual backstory for Judy Warner (39:25.086) But I love that your frustration at how building some of those systems work for you, you birthed this company, know, well, a couple of companies actually. So, and I'm always amazed at engineers, what their origin story is. And I think yours is one of my favorite and how art and tech, you know, and electronics go together because I'm sure you know a lot of engineers that I know they're in a band or they're drummers or they have some kind of artists. know one guy is amazing master sculptor and it's just not intuitive that you would take these traditionally right brain or left brain people and you bring it together and I think it's fascinating anyways. Thanks for sharing that. That's great. Any last thoughts before I let you go? And why don't you let Matthew Haber (39:53.646) you Judy Warner (40:18.694) know also as we wrap where they can connect with you in cofactor. Matthew Haber (40:24.022) Yeah, so online we're at cofactor .com. We're also very active on LinkedIn. You can follow me personally. You can message me. You can message Phil or anyone else on our team. You can also meet up with us in the real world. We'll be at IMPS. We'll be at PCBWESC. We'll be at Electronica. We'll be at IPCApex. We'll be really all the kind of shows you might expect, I think, over the next year. We also host dinners for hardware folks in this industry in various cities. So if reach out to us. We'd love to include anyone who works in electronics or works in hardware, one of those. And we are often around visiting customers and stuff. So we always love meeting with folks face to Judy Warner (41:07.344) I love it. Well, again, congrats to you and thank you again for recently joining as a sponsor. And I can't wait to continue to shine a light on you and the amazing work you're doing in industry and specifically in our case to really empower engineers to have amazing visibility and planning ability that's just going to make their lives easier. So thank you so much, Matthew. For our audience, You are interested in connecting with us. I'll put all those links that Matthew mentioned in the show notes below and make sure you go follow them and connect with them so you continue to follow their project. Thanks for joining us today. I hope you've enjoyed this conversation as much as I have. We'll see you next week. Until then, remember to always stay connected to the ecosystem. And that is a podcast. Stop.