AI & Software Solutions for Supply Chain Logistics

Wade Erickson (00:13):

Welcome to another episode of Tech Leaders Unplugged. We have two guests today kind of unique for the show. And the, the, the topic is today is AI and software solutions for supply chain logistics. Something I think that a lot of us have been affected by in the last few years. And yeah, so we have Dan Acosta, CEO of GRYDD, and we have Phil Hodsdon managing director at GTM of Port Portola Valley Partners. Welcome guys to the show.

Dan Acosta (00:50):

Take you Wade.

Phil Hodsdon (00:50):

Yeah, thank you Wade.

Wade Erickson (00:52):

So, so tell me a little bit, we'll just jump right into you guys, Dan and Phil. Tell me a little bit about yourselves and then about GRYDD and Portolo Valley Partners, and a little bit about how you guys came together to work with each other.

Dan Acosta (01:09):

Sure. Phil, if you want to give it a go. Sure.

Phil Hodsdon (01:12):

So Portola Valley Partners works on partnerships and investments with software companies that we think have a lot of potential to grow rapidly. And we first started working with GRYDD probably six months ago, and we helped them with capital raise, and we put in sales support to people as well. And GRYDD has been a phenomenal success. Its software hit a market need, and we've been able to grow the company over a hundred percent year to year. Dan.

Dan Acosta (01:44):

Awesome. Thanks Phil for that. Yeah. Look on our side I'm the founder of course, of GRYDD and started this journey about five years ago. This is actually my third company in the logistics and supply chain side. And what we have started a few years back is understanding what the real needs of the customers are in the market. I've been in supply chain and logistics in and indirect ways for the past 20 years with a couple of 14, 500 companies and small companies and medium sized companies. I've been lucky to see the whole process from end to end. And what GRYDD has been starting to do while we worked in our, on our thesis has been a little bit different that what we see out there in terms of building just one solution, that you have inventory of systems trying to figure out what to do as a company. So we came with an idea of, hey, we're non-disruptive, and I know that is not the typical Silicon Valley. Hey, we love this, be disruptive, change the market. Our idea is a little bit different. It's not being disrupted, especially in supply chain and logistics. It's our idea is, look, we understand that supply chain and logistics is kind of the vein that actually gives life to all the different companies out there that are moving products around the world. And there's multiple different companies in the process, right? So we understand that first and foremost, you, you as a company has have already invested millions of dollars in different systems and capabilities. And we have multiple clients that actually have that, that 15, 5, 10 different systems or one or two trying to do this. So we come in and say, look guys, we're going to leverage what you currently have understand the data needs that you currently have, understand the pieces that need to be automated or digitized. And we come in and say, well, whether there's an SAP, an Oracle, CargoWise, Mariah, you name it, any company out there JD Edwards you name it, right? We come in with our expertise and we come in and integrate those pieces, get that data sorted, and in the flow we say, look, we understand that as a shipper, as a freight forwarder, or as a carrier, these are the pieces where you need to digitize the process. So think of us as a, not only a data integrator and data analyzer, but also bringing those Lego pieces, those modules that actually can flow, can make that flow go faster and better. So really we're looking into how do we make things more efficient for our clients? So we took a very different approach in the, in that process. And yes, working with Portola, we started expanding a lot more into different markets, different clients, and actually we are basically in growth mode as we speak. And yes, wait, I'll go into more details. I know that's a lot of things, and it's hard too, but it's, this is where, where GRYDD is very different, and all of us in our company come from the market. We've done this before. We've worked in supply chain, we lifted boxes, we, you know, worked on containers, we've worked with carriers with freight forwarders. So we've experienced this first firsthand, and we wanted to build a solution that was actually catered to the industry and to our customers.

Phil Hodsdon (04:46):

Well, you know, Dan, what I like about what GRYDD has done is that you integrate into the existing supply chain logistics and all the software flows inside an enterprise. And we recognized early on all the data that you're collecting from all of these stove pipe systems, that that data if it's sitting in a data lake, doesn't do you much good. But if you applying data science against it and generative AI against it, then that data turns into information. And, and what do clients do with that information? Dan?

Dan Acosta (05:17):

Look, and I think I would say this GRYDD has always been a data company. The idea is and part of my experience, I used to work with multiple companies and the business intelligence side, I led the business intelligence side for a couple of 4,500 companies as well. And the beauty and the power of a company stems from your data. And unfortunately, that data really is dispersed, broken is not connected and is not being well used. And supply chain is just one of the many industries that gets impacted by that. So we, one of the key things for us as well, understanding how your data is impacting your business, right? And we've done this with a couple of distributors, big distributors, I would say 3 million or transactions or so in the market, you know, with working with multiple companies like Starbucks and, and Chipotle and Chick-fil-A and McDonald's and so on. We've actually encountered that look in, there's a lot of power behind what you're trying to do, but there's a lot of fragmentation in the systems and the processes that you run. So you have different systems to run, different pieces of your supply chain or your logistics, and you really don't have visibility or orchestration and visibility. I would always say this, there's companies out, there's AI visibility is track and trace. That is one piece of the puzzle visibility is understanding really embedded in your company how things are flowing, how a product gets from the warehouse to the truck, to the truck, to the final destination, how that data is being given to the customer, understanding how efficient they're actually being and basically ingesting that data to make sure that every time you do things better what's actually could change. Is it traffic patterns? Is it the way I'm actually using or ingesting data into my containers and so on. So that's where we're very, very different that we like to do is just come in and say, look, we're going to really understand the data that already resides into your systems, built a cohesive view of that data, and then just feed you the data and give you that visibility. We actually taken customers from a, what we call a 25% visibility to over 95, 90 8% visibility, understanding really what's driving their business. Super important, right? Just first and foremost, before I even give you a module, try to sell you something. Let's solve what you currently have. Then we come in and say, well, we can get that 95% to a hundred percent if we do this, so that now we do this. So we're not trying to sell you something to say, oh, that this should be something that works for everybody. No, this is just ca customizing something that is for your needs. We, you know, standards, modules that we currently have that data as well allows us to do predictability models, understanding demand planning models, and understanding how you can predict how many patterns out there and, you know, weather patterns and understanding how product patterns and sales patterns and so on, that's extremely important to become a lot more efficient. Rather than having to bring X number of containers a year, you can minimize the amount of containers because you understand the patterns and you understand the demand that is needed for that. So we actually do predictive machine learning modules, and it goes back to what we're talking about today. Ai. So y AI would be great. So AI will be as good as the data that you're feeding that ai, right? So if you don't have the backbone, if you don't have the, the base for that AI to work well, it's the typical garbage and garbage out. So we emphasize on makes clean, making sure that that infrastructure, that data is good, is great, is clean, and then the ai, the machine learning components will sit on top and give you the recommendations that you need, both from a logistics tracking perspective, analyzing predictability models, and when you need product to be delivered to understanding when your vessels, your trains, your trucks, your planes are coming into the last final piece of when you need to connect all those pieces and actually save, save money in the process. Efficiency is extremely important. So there's a lot more pieces to that, but we actually are in right now launching this year, five components of ai. But again, I would say those components wouldn't be ready and it would be premature if we didn't have the infrastructure behind it to work the right way. So that's, that's one of the things that we're doing. And, and I know, Phil, you've seen this firsthand, so I don't know if.

Phil Hodsdon (09:31):

No, I think it's exciting. I mean, I, I think one of the applications that I saw a demo that's under development is a ocean container tracking system that's predictive. And what it looks at is what are the wind conditions from port to port? What is the current, how fast is the current running, what's high tide, what's low tide? When is that container ship going to arrive at that port? And when should the trucks be there to pick the containers off the port? You know, we saw in Covid that we had clogged ports and truck drivers getting frustrated in parking lots. Somebody's paying those truck drivers to sit there and idle their engines. And for every day that you screw up, when is the container going to arrive and when is it going to get offloaded? It's going to cost you tens of thousands, if not millions of dollars, depending on your size. And so having a predictive way to understand when something is going to arrive from point A to point B to point C is really important and it drives profitability for companies that are using it. You know, Dan, we talked the other day about one of your larger clients a case history study. They've been able, I think you said they were able to grow 10 times the amount of volume that they had when you first started working with them, and yet they haven't increased any headcount at all. Can you talk a bit about that?

Dan Acosta (10:44):

Sure. And unfortunately, I can't mention names, you know, legal stuff here, but it's a big food manufacturer. And basically we run we run their complete shipping line. So they actually have a own their own carrier inside the company. And it's been a very successful story. I think carriers in itself actually mean, when you look at carrier freight forwarders, their margins are pretty slim. They deal with a lot of issues. They, you know, freight rates fluctuate like crazy and you've seen companies like Convoy and so on kind of have the impact of that. But what we've done with those guys is really automate the process, digitize the process, really thinking how they actually work, how they collaborate, how they work, how all the processes go within their system. So for anything from creating a booking to managing contracts, to managing their vessel schedules, their vessels predicting when, when products are going to be delivered and so on. So basically a full end operating system that also integrates with their rbs, right? We connect with Oracle in that sense. We're giving them interaction in terms of basically making sure that the financials are okay, that they can charge their clients when things happen, like the merge and storage and electricity and so on. But we took that company from very high growth. I think they grew 10 x and their margins were about 50%. So, which is un unexpected expected. And like Bill said, those guys are extremely happy, and I would say more than happy, as they said, they've started growing a lot more with us, but we haven't, they haven't had to invest in resources, meaning more people running the solution. So for a company that's going 10 x, you expect a normal carrier that you're going to have to increase tenfold the number of people that run it, in this case, the same number of people are running a much more efficient solution. So now we're starting to take that model across different carriers and grow that. But basically it's digitalization of the process. But also I would say the biggest piece for us is we listen to our customers. You've got to listen to our customers. We're not sitting in a silo trying to figure out, hey, this product is going to be good for everybody else, is we understand what you need and our product is going to replicate how you operate so high for us, collaboration, integration and the development piece of the product is extremely important. We don't run a company that is not based on what customers need and that's never going to work. So, and we've seen how many companies are going to fail, and going back to the covid situation fail, super important. I think what you saw in Covid, it's how do I, the metaphor that I've always tried to use in Covid is the issues in supply chain and logistics were always there, right? It's like when the ocean goes down and you start seeing the rocks in the, in the beach and you start, oh, there's a bunch of rocks and covid that's just basically all the rocks were already there and it just basically exacerbated the issue. So because the demand increased because people were not moving and you saw spikes in freight like no other, so you were paying $30,000 a container, which is, you know you used to pay $33,000 a container, hence why we have inflation and so on and so forth. The issues were not, oh, this is not new to covid, this, they were there, there's just the demand increased massively. And it created this effect of lack of transparency, lack of collaboration, fragmented the systems that are not connected or not sharing data across each other. So that's what we saw. And at the end of the day, somebody pays for it. The, the ultimate payer is us. The user that is buying a product in a company, we're paying for it, right? Inflation I'm sorry, carriers or shipping lines or reporters are not going to say, look, I'm going to, they're going to transfer the cost and say, look, retailer, you actually have to charge that to your client. And so on. I used to work in retail, so we know exactly how it goes. So that is the key component, is the ability for us to build an operating system that works well with others, with other systems that gathers that data that allows you to be more transparent and allows you to break that fragmentation and actually build those bridges. That's what we're doing. That re reduces the transparency, it reduces the friction, and it gives you a better flow how things are projected to go, and it makes it more efficient and it ends hands, everybody wins, right? That's the goal of it. So covid, one big thing for us, one big inflationary component based on all the issues that were there could potentially happen there. I mean, you see the issues in the Red Sea now you know, being vessels being stuck and, and, you know, freight rates are going up again. So you might see impacts. Geopolitical components are always going to be an issue in supply chain. It is a global issue. Every time something sparks, everything's going to happen. If you have the ability to utilize that data and not say, Hey, let me just be reactive and be proactive and actually reroute vessels, reroute shipments, and so on, and be more effective, that's where the money is. That's where you actually get a, a view for your, a better return investment for your company and for all of us, right? At the end of the day. Sorry, that was a good long-winded answer, Wade, but.

Wade Erickson (15:41):

No, that's, that's great. That's great. I appreciate all the, the good details. You know, I think a lot of the comp folks out there, you know, tech people as well, we take for granted the whole supply system, right? Only until there's mishaps like Covid that we actually start to dig into it and hear about it on the news. And you know, applying ai, a lot of, you know, ai, we understand that to be learning from the past, learning and training the ai. And one thing that's interesting is, you know, if you could talk a little bit about how the supply chain, you know, what it's been like, what it is like today, and then if we use AI to understand patterns when things are good, can you talk a little bit about how you apply, what if scenarios to teach it, to understand how to make these adjustments to the shipping issues when a geopolitical event happens, or a covid or an earthquake to kind of teach the models to understand these jolts that you cannot really predict that they just happen and all this, this stuff has to adjust and machine learning obviously, and AI can help with that.

Dan Acosta (16:54):

Yeah, look, I would say the expectation always is, is how you're going to build a system. And this is going to be magic, right? From day one, technology is going to solve all my issues, right? And it's not in supply chain is one of those where it is a highly collaborative industry. It is when you're dealing with products when you're dealing with logistics and supply chain, you're dealing with freight forwarders, depending on what role you play, you're dealing with freight forwarders, you're dealing with carriers and vice versa and so on. So everybody's working together, right? So that's, that's the first thing that you need to understand in supply chain is that AI and technology will enable you to be better at what you're doing and be more efficient, but it's not going to solve the issue. Collaboration, extremely important. How do you make sure that those relationships happen and be better for you? Extremely important, I think, and the ability to predict and help you make decisions faster kind of re-engineer decisions faster and say, Hey, if something's happening here, should I go, should I go somewhere else to get this done? Should I reroute my shipment and so on? That would be ideal. And make sure that the whole chain in the process gets involved in the process, that they know what's going on. That's extremely important. So, so that's where we're coming from, is just basically, again, not being disrupted. We don't expect, and I would say this again, don't expect AI to solve all your issues, that don't expect your AI to replace a freight voter or replace a carrier or replace an operator. That's not going to happen. Expect AI to help you be more efficient, be leaner, faster, better. Yes, a hundred percent. That's what we expect. So that's what we're building here. We're not here to replace people. We're here to enable to as people, to be better and right, like I said the example that we had, you can run the organization with less people, less resources. And I think I'll go back to this. So yes, when we started GRYDD years ago, one of our initial models was looking at predictability of weather patterns geopolitical components. So actually one of our data science teams actually built that in saying, look, I'm going to, I'm going to mine the world and I'm going to look at news outlets and ports data and so on, and I'm going to tell you, all right, there's a issue with the port of Ningbo is being shut down because of covid and nothing is moving out of there. So should you, even as a factory, think about moving your product from Ningbo to long Beach or should just move to the port of Shanghai and make sure that that doesn't have an issue. So, right. So that that way your product is not stuck. So we're going to basically let you know, hey, the, the, the model is telling you shouldn't do this because if you do this, your product is going to get stuck in the port. It's not going to happen. And same thing if the port of the Long Beach years ago, again, the same if the ported Long Beach is stuck and you have not enough capability to run those should just move to Vancouver or Seattle and so on. So reroute your shipments to not have that issue. So that's one of the things that we're going to take care of. Weather patterns are going to be an issue always for everybody else. So we could say, look, and we are looking at vessels. We track about a 15,000 vessels on a daily basis, on a per minute basis. Same thing with about 40,000 planes around the world. And we're starting to do more trucks, but we're starting to analyze and understand, hey is there a weather pattern that is actually impacting that vessel to come through faster? We look at speed dynamics, we look, the route's going to take longer. And what Phil was saying is, look, we could tell you don't even send the truck to the port because that vessel's not going to make it on time. It's going to be a couple of days delayed. So you're going to have a truck that is expecting there. So those things are very important for us to let you know, predictably, hey, might not be the 18th of the month, it's going to come out on the 20th, don't do that stuff. So that's also predictability. We, last year, we run about 120,000 routes through our system. So every route, the system and the ai and the machine learning is learning what route is more efficient, the most efficient what vessel, what plane is actually be the best option for you to get your product from point A to point B. What ports are going to be more efficient? So is it Savannah that is actually great, is the port in New York. You know, we started looking at those patterns and understanding, look, we're going to rate those and tell you the likelihood of you having an issue in this particular location is high or low. And we're going to say, Hey, routed to this port or this location. The other part that we're doing with AI is the piece of how do packet times zero containers before they even leave? So we, in supply chain, there's a thing called the whip effect. So the whip effect, as you can see, when you whip something, the, the wave starts growing as they go faster. So when you screwed up at first, it actually expands tenfold every single time. So basically the cost and the issues expand tenfold. So basically you have an issue of a thousand percent issues if you don't do, do things the right way from the get go. So one of the things that we do, and this is from our learning being in the retail e-commerce industry in the past, is look, if you're able to packetize your container and say, look, I'm going to packetize my container and palletize it in a way that when it gets consolidated in the port of the Bo Shanghai or anywhere in the world and I know that it is going to the port of Long Beach, but some products going to go to Seattle, some products going to go to Dallas, some products going to go to New York, and so on that, that process, rather than just saying, let's wait to packetize max that container out, packetize it in a way that is strategic. So when it comes to the port and you're consolidating that, it's very efficient, alright, this pallet goes to New York, this pallet goes to Seattle. So from the get go, we're making sure that everything is easy. There's cost related to everything that you do. There's a cost of 11 cents to 17 cents per touch point every time somebody has to touch a container or a, or a packet. So we can minimize that touch point and everything just flows. That's what we're doing. So we always look at it from a proactive approach. So it's one of the things that we're doing with ai. And the last piece I would say is of course, sustainability, right? We're understanding we're running sustainability models and understanding, alright, what's the most efficient, greener option, right? We do have to take care of our planet and we have to do it in the right way. And I know companies are looking for that. It's important for them to be green to have a supply chain green option. So we're also looking at those options and what is the most optimal way to get things moving. So that's, those are the ideas that we're running. This are the models that we're running behind the scenes and helping companies be more efficient, of course.

Wade Erickson (23:22):

Great, great. So, you know, we're getting close to the top of the hour. Time flies fast on this show. And you know, this I like, I like to pivot in the last five minutes to a little more about a personal side. Dan, you said you've had at least three companies in the past and you know, Phil, you, you, you, you, you know, Portola Valley partners provide services to help them grow. Can you talk a little bit, Dan what was the founder mentality that you had to have the courage to start these companies? We have a lot of people that have these ideas and you would like to start it. And oftentimes it's the mindset to get going. And Phil, just talk a little bit about what services you provide to GRYDD and how that supports them for their growth. Cause a lot of times we just think of, you know venture partners and stuff just providing money, but a lot of that is really about services to, to help them, you know navigate the potholes and be more efficient.

Dan Acosta (24:25):

Perfect. Yep. Look, Wade, to me it was being a customer of supply chain, that's what sparked it. You know, being in the trenches, seeing how things operated beers, you know, seeing how containers would arrive or product would arrive at one of our distribution centers, we didn't have the capacity. There was no transparency on that one. We tried multiple different systems to make sure that everything was connected, integrated, and honestly failed. Legacy solutions were not ideal. So I thought, look we're looking at the problem from a different standpoint. We got to look at this differently. We got to look at this from a non-disruptive perception and more of an evolution or connectivity perspective. So that's what led me to say, look, there's, there's a lot of, there's a lot of solutions out there that give you some features, but at the end of the day, you end up having 15 different systems, it doesn't really jive. So for us was we got to really solve the problem. We really have to figure out how we're going to solve the problem. And yeah, it is complex and it is not, but that integrative cap capability that working as thinking open your mind and thinking, okay, supply chain is not just one guy. Is all these different players working together, even if they're different companies. So why do we make them work together in the same ecosystem and hey, they give them the tools to collaborate and work. That was the key component for us. So just really lift that man. And I lift thousands of containers getting stock you know, air making decisions. I was the finance guy making decisions and seeing costs ramping up and really buying those solutions and not seeing return investment and not seeing the efficiency. So we thought, okay, we are going tore-engineer how things should work, build GRYDD as this component and not deviate our path, not deviate in a path that's saying that, look, we're going to focus on one feature and this is what it is, and track and trace is going to be great and that's going to solve your visibility issues. That's not it. It is really, it is, it is painful, but it's, we have the passion to get it done, but we're going to go after the long run in solving the issue. So we, we've done it and we work with clients and we actually, our success nowadays has been the fact that we've worked with very good clients that are willing to work with us to solve the issue of overall so, and build a technology to support that. So it took a while to get there. Like I said, I, this is my third company. I run a digital freight forwarder for a while. And the reason why we did it is because we wanted to understand how freight forwarders really operate, how they thought the issues that they were having. And we started, our first company I started was, was more on the track and trace capability that expanded into GRYDD, really connecting and not being disruptive and also becoming a data company. At the end of the day, data is key. Every interaction that you have, every system, every Excel, every spreadsheet, everything that you run has data. So how do we maximize that data? And that was, that was the goal of GRYDD. So we'll continue moving forward. That has been I would say a very, very rewarding path. It's not easy to be a founder, but it's fun actually. I would always say this is great to be a founder, especially in tech. But it's, it's been very rewarding, I would say. And I have actually a phenomenal team. So I kudos to my team and my tech team that has been fantastic in operations to get this done and the partners that we have now. So it's been good.

Wade Erickson (27:45):

Great. Phil, can you share a little bit?

Phil Hodsdon (27:47):

Sure. So when we first looked at GRYDD nine months ago more or less, we saw a diamond in the rough. We saw a fantastic piece of technology and software for the supply chain, but the marketing philosophy was build something really, really cool that works really great and people will just find you beat their way to your door and want to buy from you. The real world doesn't quite work like that. So we invested in marketing for GRYDD and we invested in having a sales process that makes it easy for, for someone to try out GRYDD. We got rid of the friction. We, we built pilots. We, we worked with large companies and small companies and medium companies, and we basically really got our process straight of how to move it forward. And we had just phenomenal success. It, it actually surprised me. I've been in sales for 30 years. I, I never have seen the client reception to a nice piece of software. Now that we got the message out I wouldn't say people are, are beating their, their, you know, beating up their path to our door yet. But GRYDD is on its way. You are going to hear a fantastic growth story coming out of GRYDD over the next couple of years. It's a company that has technology that's ahead of its time and we're out to grow like crazy. We're, we're going to do a hundred percent growth year over year this year, next year and the year after that.

Wade Erickson (29:14):

That's awesome.

Dan Acosta (29:15):

That's fine. Actually it is very, very fine. And actually, honestly, wait, I will finish with this. I think supply chain in itself is in its name, right? It is made out the chains the different pockets of chains in the supply chain, right? So it is all connected. So we, I think the industry has taken a different view of all, let's just focus on one piece of the chain. The chain doesn't work without the other pieces. It doesn't, it just breaks. So we looked at it and said, look, we got to look at the whole chain. I know it's, I know it's big, I know it's massive, I know it's complex, but if we don't do it this way, we're just going tobe one more of the pile, one more system out there that you have to file. And we do want to work with Oracles and the SAPs and those guys because we do want to integrate. We want to make sure that we leverage your data. So extremely important for us.

Wade Erickson (30:04):

Yeah, those, those ERP systems are critical in a piece of the whole puzzle because like how many on average, how many different touch points are there from something going from Asia to the US? 5, 10, 50?

Dan Acosta (30:21):

Depending, depending on how complex your supply chain, it could range from five to 50. cause you got customs, you got ports, you got to do cross talking. There's different pieces that actually happen in different parts. So it could range. And think about it, the bigger you are, you are not working with one, you're working with multiple, yes, you're working with multiple carriers, working, working with multiple freight forwarders and they all have their own systems. And yeah, APIs, everything. And now you're expected to, hey, you're expected to work very efficiently and make decisions very quickly with data. That honestly, to be fair, that a lot of the clients that we talk to is like, oh, we still put in Excel and we run a spreadsheet model and then hey, we make a decision right after. Excel is still one of the most used system tools out there. So we I lot excel, don't get me wrong, but it's not a way to run your supply chain, right? So, so we got to make that efficient for all those.

Wade Erickson (31:16):

Yeah, it's like, you know, you're constantly having that chain. A link gets broke, you got to reattach the links to get the chain to continue to work even though you're breaking them along the way. So, awesome. Alright, well, you know, we're kind of at the top of the hour. I wanted to quickly introduce our next week's show and then you just have some parting words from you guys as we wrap up, if that's all right. Sure, go for it. Yep. Next week we have Reza Rasool, he is actually in Encore. We had him earlier in 2023 when he was with real Media. He now has retired and now is working with Kauai, which is an AI open source community. And he's going to talk a little bit about trying to get AI back into the open source in the open world. So join us next week for with Reza again and just a, a different topic but heavy on AI. Alright, so Phil, Dan, I just wanted to thank you again for your participation and sharing your knowledge here on Tech Leaders unplugging the community here. Is there anything you'd like to say before we wrap?

Phil Hodsdon (32:26):

I'll say one thing. I'll say that the success of GRYDD over the last year has been phenomenal. And the success isn't just from a marketing and sales system, it's from a core product. Value GRYDD has tremendous value for those companies that want to check it out. So if you're in this space and you're looking for a better solution, talk to us, see a demo of the product it's spectacular.

Dan Acosta (32:53):

Yeah, great. I would say thank you so much for inviting us over here. Phil, you said it best. To be fair, we speak customer, we live customer we like customers. I like customers more than investors, a lot more love them. I like to solve their issues. So yeah, reach out to us if you need anything. Love to show you a demo, love to work with you guys and really solve your issues as we can. Make it more efficient for all of us, right? And that's, that's the goal of it. At the end of the day, collaboration, integration and manage and give you the efficiencies that you actually need and will .

Wade Erickson (33:27):

And, and we appreciate all your hard work 'cause we're receiving those products, whether we buy 'em off the shelf at a Walmart or you know, have 'em at Amazon or whatever. There's just a lot involved to get the products to the people from all over the world. And so, again I think you guys are underappreciated but tremendously valued both to the, the global economy and you know, how people trade in the world. So appreciate your, your applying your intelligence and knowledge to that 'cause it makes life easier for all of us.

Phil Hodsdon (34:04):

Thanks Wade.

Wade Erickson (34:06):

Alright everybody. And we'll see you next week on Tech Leaders Unplugged.

Dan Acosta (34:11):

Thank you Wade.

Phil Hodsdon (34:13):

Thanks. Wait.