Ed Dodd is a veteran in the tech space who specializes in solving technology issues in the manufacturing and sourcing domain. He is the Vice President of Business Development for Cofactr, a company that leverages AI and innovative technology to help manufacturers solve complex procurement and sourcing problems.

Nate Wheeler is the host of the popular Manufacturing Insiders podcast. He also owns weCreate, a nationally recognized marketing agency that helps manufacturers grow, save money, and become more efficient.

In this episode of Manufacturing Insiders, Ed Dodd reveals how AI is quietly revolutionizing one of manufacturing’s biggest headaches – procurement and sourcing. While most companies are still manually hunting through supplier websites and drowning in vendor communications, Cofactr has cracked the code on automating the entire process from design to delivery.

Ed shares fascinating insights into how their platform is saving companies 30-50% on time and 20% on costs, while providing the kind of supply chain intelligence that was previously only available to massive corporations. Read on to learn more about the innovative ways Ed is using AI to solve challenging procurement problems.

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Nate Wheeler (00:01.105) Welcome to Manufacturing Insiders. Today I have Ed Dodd with me. He is a veteran in the tech space, really solving tech issues for really critical applications. He’s deeply involved with a company that is helping manufacturers solve problems in the sourcing space, really using AI and just some really innovative stuff. Welcome to Manufacturing Insiders. Ed, can’t wait to hear about what you have to say.

Ed Dodd (00:32.984) Thanks, Nate. I’m really excited to be here and am looking forward to our discussion.

Nate Wheeler (00:36.419) Awesome. So along the lines of procurement, what kind of problems are you guys solving there and who are you working with?

Ed Dodd (00:47.032) That’s a great question. So I think the easiest way to think about what Cofactr does is we fill that gap between design and manufacturing. The digitization and the digital transformation of design has been well underway for a long time. Likewise, industrial automation and manufacturing automation has been in the works for a long time.

The gap between there is once you have that design, how do you get the parts you need? How do you source the parts you need? And make sure that they arrive at your manufacturer to feed that next process. To date, that process has been relatively manual, relying on people to search distributed websites by hand and that kind of thing.

And then, of course, deal with the process of vendor communication, shipping schedules, all the snafus that happen in between when you place the order and when you expect the parts to arrive. When you’re pegging your manufacturing start date to a bunch of promises upfront, that really starts to matter. Those delays can really add up and be costly. So what we’re doing is we’re automating that purchasing the vendor discovery, supplier discovery,

purchasing, order tracking, delivery. And then we also have physical presences in New York and in California to actually receive parts on behalf of our customers and kit them up and make sure that they do arrive at their manufacturer, at their point of manufacture. That’s from an end to end standpoint, we’re connecting the design from the bill of materials through the process right to that beginning of manufacturing where your MES and your digital manufacturing controls start to take over.

Nate Wheeler (02:55.447) It’s fascinating. So I’m kind of picturing a PCB manufacturer. You’ve got your capacitors and resistors, and you’ve got 1,000 different components on a board. They’re going to use your system to really put in that design and the list of the bill materials. And you guys are going to come up with a kind of a shopping experience where they can say, hey, I see that the price is cheaper with these guys, but they have a long lead time. These ones have a shorter lead time, more expensive, and get to make those selections. That kind of works.

Ed Dodd (03:35.65) Yeah, the purchasing process itself and vendor, you know, the vendor discovery and purchasing process itself really provides the sophisticated practices of like the large aerospace companies, the large automotive companies and automates that in a way that small to mid-sized companies can now start to take advantage of the kind of intelligence that really has been brute forced, right?

So they don’t have 15 people to throw at this printed circuit board assembly to look at all of the different vendors for each part. So like you said, there could be 100, 150 part types on a PCB. Having somebody go through and look at the eight to 10 different suppliers for each of those parts is just impractical. And usually what you see is you see people go to some of the component distributors.

And then throw the whole bill of materials at them and sort of cost the bill of materials from shop to shop. It’s not a line item by line item thing. And in doing so, they end up leaving a lot of money on the table. So what we’re finding is that by just surfacing a cost versus lead time matrix for our customers across all the authorized distributors in these parts, they’re able to get the best deal in the timelines they’re looking for.

Nate Wheeler (04:56.999) Right. So it seems to me that it would be difficult, putting myself in your shoes, to visualize all the possible needs for components and parts out there in the marketplace. So how do you reach a critical mass of relationships that you have with suppliers to make this a valuable end product for the sourcing person?

Ed Dodd (05:25.912) So, I mean, the great thing about the electronics industry is that it’s a known quantity, right? And we also help bound the problem by being domestic first. So, Cofactr typically serve the aerospace and defense market. We also serve robotics and automotive and those kinds of markets. our focus is really on highlighting domestic sources.

And we can talk about the non-electronic stuff in a little bit, but for the most part, we’ve bound the problem. The other thing is, we have an amazing team in our data group that does nothing but surface ways that those distributors make the data that we need in order to be viable available, right? So each

Each supplier has different ways of doing that. We are constantly making sure that our APIs are up to date, that our data sources are up to date, that when a customer is looking for parts, they can see how many are on the market right now, how many have been on the market for the past year. They can see the price and the lead time that is no older than today.

Ed Dodd (06:53.038) When I log in, I get today’s prices, today’s lead time. that matters. I’ve seen a lot of cases where there seems to be an availability of a certain part of the market. That availability really was at the request of one of the large OEMs. And between the time you design in the part and go to purchase the part, that OEM has purchased the 10,000 parts that they requested being produced.

Ed Dodd (07:22.592) And suddenly, those parts aren’t available. So by making sure we have up-to-date information, we’re arming our customers. And again, mostly in the small and mid-sized market with the kind of information that Intel hasn’t been available.

Nate Wheeler (07:40.791) So are you procuring this information directly from what they make publicly available, or do you have another mechanism of communication with them to kind of assess that?

Ed Dodd (07:52.716) Kind of like an octopus, right? So there are, whenever I talk to the data team, there’s a whole range of activities that go into pulling that information in, right? It’s not, there is no silver bullet. There is no, we just plug into this database and we’re good to go. We are the ones that are aggregating and curating that database from just a range of sources. We use AI to do a bit of data scraping. We use the APIs where available.

However we need to interact with the larger global data environment in order to pull that information in and aggregate it. I mean, if you’re looking for specific processes, that’s a little deeper than the kind of thing that I’m involved in personally.

Nate Wheeler (08:46.215) Sure. Right. And probably not stuff that you wanted to share with anybody, right? Yeah, there’s got to be some secret sauce there. So tell me some success stories, maybe the type of company and how they’re using your solution and what it’s doing for them.

Ed Dodd (09:08.088) Sure, sure. Many of the companies that we work with view their use of Cofactr as a competitive advantage. And so I’m hesitant to really do a lot of name dropping. If you go to our website, you can see the logos that we’re allowed to share. We’ve seen a number of success stories that were sort of built around the collateral value, right?

Time saved, right? We see 30 to 50 % of time saved in the purchasing process. We see costs down, right? We see an average of, I think, 20 % cost savings on parts as they are just simply from doing the cost comparison, shopping around, right? The way I like to talk about this, I mean, imagine instead of going to a single grocery store, like you had a grocery list of a hundred things that you needed to pick up.

What if you could go and look around at all the grocery stores in your area and then push one button and have Uber Eats or Grab Hub or whoever, go and pull just those parts, just those food items from the cheapest grocery stores in your area. Pull all of that together to deliver to your house.

Your grocery costs would go down and we don’t do that personally because nobody’s going to spend two days buying groceries. Nobody’s going to go around and buy groceries. So we do the same thing with electronics, with parts. And when we see companies implement our product, the time it takes them to analyze the bill of materials.

Ed Dodd (10:56.526) For things like life cycle, obsolescence, multi-source, is this part going to be available when I go to scale my production, right? That information surfaced almost instantly. The time it takes to do that kind of research is cut down to something that is practical. We’re seeing a lot more companies become more aware of their supply chain.

And be able to manage component selection during that process. We’ve seen that purchasing process because we use AI to go through and pull out all of the relevant information from all of the associated documentation. If you think about the documents associated with that whole purchasing process, you’ve got RFQs and quotes and purchase orders and shipping bills of lading and shipping documents and receiving documents, all of that information, we have a tool that pulls the relevant data out, structures it, and provides it to your systems of record.

If you’ve got an ERP or a PLM or an MES, we pull all of that together and structure that. And what that does, it creates a traceability from end to end where if you’ve got an issue in manufacturing, if you’ve got an issue with parts that are hitting your manufacturing floor that maybe shouldn’t be, you can look through that data trail now and understand where in the process things might have gone sideways, tracing that and relatively quickly. So taking weeks worth of investigative work.

And allowing that to be almost just at your fingertips and say, what happened here? And this is where it went wrong. And now you can go and approach that right point in your purchasing process for a correction or remediation. So we’ve seen some manufacturing processes get saved on a timeline basis just because those parts were delivered, but then they didn’t match.

And then the investigation in terms of where did that go sideways and how did that enter the chain allowed them to really bound the problem and move forward with those parts of their process that weren’t effective.

Nate Wheeler (13:33.445) Right. And like you mentioned before, in terms of a recall, instead of having to recall everything from a year, maybe you can recall everything from a day, right?

Ed Dodd (13:46.252) Right. If you know, I mean, and we track this, right? If you know which parts from which supplier, from which stock lot were applied to which manufacturing, which assembly process and which lot coming off the line. And there’s a problem from, you know, inside of your supply chain, you get notified of a component issue. You’re no longer faced with, well, I’m not sure which of my assemblies were, you know, affected by this. Now I have to recall everything.

I can say those parts I received on this date, that stock lot was used for these two production runs. And I can now just pull those off and save a lot of, again, investigation time, effort, tracking down, or even just some companies will just do a full-on replacement of their entire population. That’s really costly.

Nate Wheeler (14:43.473) So what type of company should be looking at Cofactr? What space? And then what size of company? I mean, does it make sense for a company that only does 1,000 pieces a week throughput to look at what you’re doing? Just how do you kind of characterize an ideal client?

Ed Dodd (15:08.376) So anybody that’s doing high mix, low volume is an ideal client, right? Because the number of times they have to go through that purchasing, screening, sourcing process, the more they have to do that, the more value they’re going to see from the Cofactr, right? If a company has a single product that they’re building tens of thousands of a week, and they use the same parts all the time, they could use a Cofactr.

We’d be happy to serve them, right? It’s not impossible. But their sourcing activities are going to be a little more custom. They’re going to have a little more of a direct relationship with their vendors. And they don’t have to switch up all the time. So they can get comfortable with their billing materials and really cut down that way. But on the other side of that, we work wit

Nate Wheeler (15:47.453) Gonna rinse and repeat.

Ed Dodd (16:08.098) Satellite companies that are building 10 to 20 a year, right? But the criticality of that, I absolutely positively have to have it. All my parts show up on this date for manufacturing because of the qualification process and the cost of missing those dates becomes critical. We tend to serve the new space market really strongly.

Ed Dodd (16:36.61) We tend to serve the unmanned vehicle space really strongly. Companies that are moving quickly see the value and who are scaling see the value of Cofactr as a way for them to grow in the directions they want to grow, utilize their technical capability without getting bogged down by building out an oversized purchasing and supplier department.

Nate Wheeler (17:12.433) Gotcha. So let’s just say we’re talking about a new space component or an aerospace assembly. How much of that assembly is somebody going to use for sourcing?

Ed Dodd (17:30.702) Well, I mean, we started off just in the electronics market, right? Just because those parts are extremely well-defined. There’s a strong standardization around component part numbers, manufacturing part numbers. The supply chain is relatively well-behaved from who’s selling what. But we’ve expanded into the balance of the bomb, right?

What else is in that assembly, whether it’s housings, whether it’s electromechanical parts or mechanical assemblies. So we’ve got a couple of things, right? So the electronic side of things, plus you can put in, if you’ve got a housing supplier, can do your purchasing from, just by anything through our tool on top of that. But we also have a vendor discovery platform now.

With our acquisition of Cogbase that helps to identify domestic manufacturers of machine parts and other manufactured parts here in the US. So we’ve got a database of over 400,000 domestic manufacturers with all their capabilities mapped. And it’s an incredibly powerful tool to understand who is around and who can manufacture those parts for you. So we’ve got the electronics part. We’ve got the balance of the system part. But we also have vendor discovery for all of those custom parts that need to be manufactured, that need to be machined or cast or printed.

Nate Wheeler (19:15.559) Which is fascinating. As you know, I’ve dabbled in that space a little bit. And I can imagine if a tool like that were to take off, what the repercussions would be for the Thomas nets and the Googles and any of the other ways people are typically doing procurement. How do you position with that other branch?

Nate Wheeler (19:44.413) How do you position your value add in relation to a Thomas net?

Ed Dodd (19:51.87) I mean, we tend not to be comparative when we’re providing the service. And again, it’s a service that we provide in addition to. So it’s not something that we’re selling independently, or it’s part of a service with the rest of our procurement platform. So it’s a feature. And it’s not something that we’re going out and saying, look, guys, we’re competing with this, and this is why you should use us instead of them.

From our perspective, we’re just helping companies avoid obsolescence. We’re helping companies who don’t have the visibility they need into the domestic manufacturing market to be able to cost-effectively onshore or reshore their manufacturing processes, especially given today’s geopolitical climate.

And then at the same time, the ability for our customers to then diversify and even compete with parts where they may have just gotten a little too comfortable with a single source. And now that source has solely increased cost or has taken on work from maybe a different client that is providing them greater volumes.

Your parts are now lower on the priority list, especially like again, in the new space world where they may have fewer assemblies per year, they wanna be able to look around and say, okay, who’s out there that is going to be willing to manufacture these at these volumes at a price that we can live with?

Nate Wheeler (21:38.173) Sure. I don’t usually do this, but I might be putting you on the spot. So it’s OK to say it would take some time for you to set this up. But do you think it would be possible to give us a little demo of either the manufacturing service provider side of things or of the pillar part of it, the electronics sourcing?

Ed Dodd (22:05.164) Yeah, I’d love to. I think I’m probably not the best person to be doing that. I can poke around, I’m a little bit dangerous. But I’d love to set up another meeting maybe where we have our team go through and just provide a little bit of a walkthrough and a demo. That would be wonderful.

Nate Wheeler (22:26.205) Yeah, we could probably just kind of insert it into the podcast. We could do a little bit of editing after the fact anyway, but that’d be neat. So just in terms of the tenure of the company, how far along are you guys?

Ed Dodd (22:41.902) That is kind of how long a piece of string is type of a question. We are, so from a, I guess a funding perspective, we’ve gone through our series A, we’ve got our series B funding square in our sites. We’re moving quickly into our growth stage and through our growth stage, we’re hiring like mad in order to support that.

So from that perspective, that’s where we’re at. I think we’re at about 50 people right now, if you want to look at it that way. We are, I think, from a red box size perspective, we’re somewhere in the 75 to 100 customers ballpark.

Nate Wheeler (23:33.821) Wow, yeah, very cool. Yeah, I mean, it sounds like you’re making some good headway. With that many customers, you have to assume that they’re having a good experience with it. It’s working well.

Ed Dodd (23:46.818) All the feedback we’ve gotten to date has been extremely positive. The value proposition, it’s one of those things where the application isn’t the sexiest in the world, right? It’s not like computational fluid dynamics where you can show all these really cool images of cars driving through the flow field and race cars and fighter jets and stuff like that.

Ed Dodd (24:14.862) So it’s one of those problems that the industry has. It’s a challenge that the industry has that is quiet. It’s not the kind of thing that is typically waved around and where the solutions are flashy. But the value, once those tools are deployed, the value in terms of ease of purchasing, ease of vendor discovery, streamlining the communication between you and your suppliers allows the conversations to be much more meaningful. The day to day, hey, your parts are being shipped. Okay, great, thanks, is handled by the AI tools. But then we surface.

Ed Dodd (25:06.582) All of those issues and all of those changes in your orders and that your suppliers have that are meaningful so that you can say, all right, here are the three conversations I really need to have with my suppliers. And you can focus on those. And then those conversations are much more meaningful, a lot less stressful because you’re not trying to pull them out of the noise of the rest of your communication.

Nate Wheeler (25:30.929) Yeah, I definitely see the value. And I mean, I think it would be really interesting to see how a company is using it. Yeah, I’m fascinated by it. Because I really think that data aggregation, which I assume is the heaviest lift in your company, any really technology-driven company acquiring the data is so difficult.

I’m curious to know if you have any perspectives on the data side of things. With the idea in mind that AI solutions are the way of the future, AI needs data to train, to create valuable outputs. How are you aggregating data? Are there problems that you’re experiencing there that maybe you’re working towards a solution that might be a benefit to someone else in this type of an environment.

Ed Dodd (26:33.08) So our use of AI is a little different than what most of you listeners might be thinking about. So when we think of AI these days, we think ChatGPT, we think about Gemini, and these really sort of applications where we ask these open-ended questions, and we are expecting those AIs to be creative in the way that they source information and compile an answer and feed it back to us in a way that we can understand it.

We are not asking our AI to be created. We have set out to create an AI system that is much more deterministic. And what I mean by that is when you provide a certain set of inputs, you’re going to get a very specific set of outputs.

And if you come back two weeks later and you provide the same inputs, you’re going to get exactly the same output. We’re not asking the AI to take that information in and wax poetic about that. We’re saying, here’s a set of data. Can you please structure this one? If we think about what our inbox looks like after we place 50 to 100 orders, think about Christmas time.

Ed Dodd (27:55.564) Just using amazon.com, right? you’re ordering from a bunch of shops and you place a bunch of orders and they send you your receipt or your invoice or your, you know, and then they send you your shipping document, each person you buy from, each shop that you buy from, those documents are going to look different. It’s not going to be easily transferable into a spreadsheet.

What that’s going to require you to do if you are the kind of person that tracks all that kind of thing in a spreadsheet, you’d have to open that up and then type that in yourself and make sure, okay, where’s the shipping date? There it is. It’s over there on this one or it’s over here on this one. Which credit card did I use to buy it? All of that information resides in different ways in all of these documents from each of these vendors.

So what we’re using our AI tools to do in that case is to look at that document, identify the markers that indicate the standard pieces of information that we’re looking for, pull that information out, do character recognition, all the kinds of stuff that we need to do in order to just pull that out and put that information in a structured way that then allows the user to operate off of the dashboard. If I’ve got 100 orders open, 90 of them are probably going just fine. I’m going to get them when they say I’m going to get them.

Ed Dodd (29:23.182) 10% of them might have some issues. Some of them might be shipping early. Some of them might be delayed. Do I need to get a different gift for my daughter because the one I ordered isn’t going to be here until January 20th? Now, those kinds of questions, do I cancel that order? Those decisions are easier if that 10 % is really highlighted and pulled out of the noise for you. So that’s it.

Ed Dodd (29:51.98) That’s what we’re doing. When we think about AI and how we’re using AI in that way, it’s much less creative, much more deterministic, which leads to, we don’t really have to worry so much about hallucinations and things like that because we’re not asking it to reach beyond what we’re doing. And then if you think about challenges associated with that, really it’s all about training the tool to recognize the kinds of fields we’re looking for.

Ed Dodd (30:21.208) Heaven knows there’s enough documentation out there that we have to deal with that training becomes relatively straightforward. The big challenge is like, what about this document? Can we get it to read a new thing from a new document type? Those are the sorts of the kinds of things that our team has to lean into and put their heads down and make sure that the next thing is executing at the standards that we’ve established with the work that we’re already doing.

Nate Wheeler (30:54.235) Right. Yeah, the application for AI that you’re talking about is probably the one that’s more usable and more important to manufacturers than the creative aspect. Because I think the problem that you talked about, taking disparate information from multiple sources, assembling it into something meaningful, and having a standardized output is that I’ve run into a lot of applications or needs for that over the years. I can imagine if your team is able to develop that, that you could apply it in a lot of different ways beyond just what you’re doing here. I don’t know if you’ve thought about that at all.

Ed Dodd (31:40.01) Absolutely. We have conversations once in a while with other people who use other applications. Like, well, what about this? I’m like, well, I guess we could. The question is, where do we want to be? Is that a market that we want to serve? Is that worth the resources of our data team and our programming team to pivot and focus on versus, you know, what else we might have on our roadmap. And then once you have that data structured, feeding that into all of the other platforms, if we think about the digital transformation world and what’s been going on in the technology space over the last 30, 40 years, right?

ERPs kind of rise up as these sort of data aggregators, and their value is that they should be plugged into all of your different data sources, all of your different processes, and then allow you to assess and analyze across those different spaces, right? We’ve had design tools, have PLMs, we have MESs, we have shipping and receiving and purchasing and all of that.

And if we could find a way to unify that information, we should be able to perform some really interesting correlating assessments and understand where the levers of power that we have as business owners to make adjustments that will positively impact our bottom line, positively impact our processes and quality and things like that.

The challenge there is that in order to perform any sort of analysis on those data sets, you’ve got to have good data sets. And relying on people, like I said, could you imagine having to put all of your Christmas shopping into a spreadsheet and knowing that if you miss something or you mistype or you miss a line or something like that, you could throw any analysis you wanted to do on that off.

Multiply that by the number of products companies make, by the number of purchases they make, by the whole range of their supply and purchasing operation, now you start to understand why those ERPs have such a high dissatisfaction rating. Because the promise of that analysis to the business owners, the operations lead.

It falls short simply because it doesn’t have the kind of data that it needs in order to do that. So using a tool like Cofactr from that, that pulls in your building materials from your design side and carries that all the way through to manufacturing. Collects that data, structures that data, and then feeds it into tools like an ERP.

Not only does that provide value to the team running the purchasing operation, but anybody downstream that is a customer of that data that could actually make use of that data to improve other processes, suddenly that whole thing gets elevated. Those huge investments in ERPs, those huge investments in those data systems, GoFactor actually provides additional value simply by increasing the satisfaction and rate of success of those implementations.

Nate Wheeler (35:27.003) Yeah, I mean, it’s amazing. It really is. And I picture tools like this that address every area in manufacturing. And I spend a lot of time in each conversation just trying to figure out where those areas are. I mean, you’ve found the procurement side of things. That’s definitely a need. But there’s a lot of other things on the production side, production tracking, all that sort of stuff.

Ed Dodd (35:30.27) It is amazing, it really is. I think you were the coolest of my friends in the US.

Nate Wheeler (35:55.453) So it would be really interesting to get some engineers that wanted to solve all these problems for a company, put together this package, right? You know, that can solve everything. I don’t know if it’s possible, but that’s kind of what’s in my head.

Ed Dodd (36:16.818) The biggest challenge there is that you end up with a one size fits all solution and potentially a bloated solution. Right. So, I mean, it was kind of, it’s kind of the problem that the big ERPs had trying to sell into, you know, small and mid-sized businesses. They’ve got a tool that, you know, doesn’t fit through the front door of these, of these businesses. If you think about it like that, right.

So we partner with PLM providers. We partner with MES providers. We plug in and we’ve got a fantastic API and capacity to work with these companies to basically build the solution that each customer needs. Customers have different manufacturing process needs.

And so there is a range of MESs out there that suit different industries, different customers in their own way. Regardless of what the customer is using, they can plug that in. They can plug us in. They can plug their PLM in. And we connect basically those two things end to end. If they’re using an ERP, we can feed that data into their ERP. If they’re not using the ERP, they can use our native reporting processes to do that traceability, to do the tracking and analysis that they want to do, and export things to their own Excel files that they want.

But that modularity, I think, is something that we’re going to start to see more of in the technology space, as opposed to less. I think we went through a period there where everybody wanted that single solution. You had to go out and buy everybody. You the aggregation of the modeling and simulation space. Now you’ve got a couple of really, really large players.

Ed Dodd (38:16.428) The acquisition world is massive in that space. Everybody’s consolidating. But I think you’ll see that the trend is going to move away from that. And people are going to start to build their own modular systems using the tools that they see for each of those spots. And the more we can make our edges friendly,

I think as solution providers, we’re going to serve the customer base better. We’re going to grow in the market faster. And our customers are going to be more nimble because certain aspects of their process are going to need growth and maybe new solutions without having to change everything.

Nate Wheeler (39:15.269) Right. Yeah, so certainly one size fits all. mean, there’s a cost associated with that and a lot you know, things that you don’t need. You know, and what I kind of think is, I think what’s really needed in this space is almost some sort of a consultant, you know, a technology consultant that understands the applications and solutions that are possible through AI and other technology that can, because a lot of these manufacturers don’t know what they don’t know.

I mean, they say, yeah, I’ve been thinking about technology and just trying to figure out how to apply it. Well, there should be somebody that can go into their business and be like, OK, I see what you’re doing over here. I see what you’re doing over here. You have this problem, that problem. I’m going to build out a solution for you. I think that’s what we really, really need.

Ed Dodd (40:13.021) I think that’d be a fun job, right? If you knew, you could keep up with all of the tools that are out there and have a toolbox of those modules, right? And then go into a company and be like, okay, here’s how I would configure your space. And this is the way it would work for a company of your scale and your cost constraints and your, all of that. I think that’d be a good time.

I know the large companies have been doing that for a while, right? Traditional aerospace, you know, has been utilizing companies like Booz Allen Hamilton and, you know, those sort of like solution providers can slash consultants that go in and architect these solutions and these stacks from, you know, the broader industry. The small and mid-sized businesses.

And I’m sure that you’re going to see all kinds of comments in the down below where everybody’s going like, no, no, no, I know like four guys that do this. But I think the small midsize businesses either don’t know to look or aren’t really being as served as sort of the large companies in that space.

Nate Wheeler (41:27.045) Right. Yeah. Yeah. And those are most of the ones that I come across. So I’m hearing that quite a bit. So just briefly, before we wrap up, you’re obviously in a business development position in the company. And I’m curious to know, you’ve got a new technology that you’re bringing to the marketplace, which offers, as a marketer, I’m very familiar with the challenges that has.

Nate Wheeler (41:55.421) How are you approaching business development and what’s worked for you?

Ed Dodd (42:01.006) I mean, the marketing side of things, we have a fantastic marketing department. Libby heads that up and she’s amazing. We find that face-to-face works incredibly well. We host dinners and we do a lot of trade shows. We go through basically just spreading the message.

Ed Dodd (42:30.734) We’ve got a fantastic digital presence, but effectively it’s just getting the message out. Once people hear about what we’re doing, once people see what we’re up to, the conversation flows really naturally from there and we see a strong demand, right? So really it’s just driving awareness, helping people understand the value proposition.

Again, it’s not super flashy. So those conversations get to a little more of a cerebral level where we talk about pain points and just smoothing things over, reducing the lift, making things a little less frantic and a little less about firefighting, a little more about managing.

Nate Wheeler (43:25.469) I can definitely see how the trade shows and whatnot would work for the introduction. Yeah, because that’s the challenge when you have that new product, that kind market penetration strategy. When you don’t actively have people out there looking for what you offer, you have to tell them. You have to educate them and then sell them. But I can imagine there’s probably some things that people would be just actively looking for on Google that would be.

Ed Dodd (44:05.088) Absolutely. When we think about business development and market verticals, I’m involved in a number of industry standards around component management. I have a lot of conversations around obsolescence and life cycle management of your supply chain and your parts. And I have those conversations kind of at organizational levels.

As we have those conversations aligning our products to the problems of the day, as you can imagine, reshoring and supply chain is a huge issue. Tariffs, right? We help track the landed cost, which includes tariffs as part of our process, right? But again, these are features. And making sure that people understand that these features are available to help them with the

Nate Wheeler (45:07.921) Yeah, it sounds like you guys are really thinking about all the aspects of it. And yeah, I can definitely see this having broad usage throughout the space. So congratulations on what you guys have built there. mean, awesome idea, awesome company.

Ed Dodd (45:16.558) Thanks, thanks. We’re excited for everything that’s coming next.