Podcast: Finding Product Fit in the Supply Chain Market with Jake Hoffman

In this episode, Jake Hoffman, CTO of Gnosis Freight, joins Host Brian Glick, CEO of Chain.io, to discuss finding product fit in the supply chain market. Listen now!

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Supply Chain Connections Podcast with Jake Hoffman

Finding Product Fit in the Supply Chain Market

In this episode, Jake Hoffman, CTO of Gnosis Freight, joins Host Brian Glick, CEO of Chain.io, to discuss:

  • The importance of collaboration across the supply chain industry
  • Jake’s start in the logistics industry and the problems Gnosis Freight solves
  • The different priorities for different shipping companies
  • How to determine what to buy vs build
  • What the future of logistics technology holds

Jake serves as the Chief Technology Officer for Gnosis Freight, a provider of end-to-end supply chain visibility and automation solutions to logistics companies worldwide. Gnosis Freight started its journey through deep collaboration with key partners in the supply chain industry – tasked with understanding supply chain’s most critical pain points and addressing them head-on.

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Episode Transcript

Jake Hoffman 00:04
When we went to the singular data providers, it became like us just playing middleman between our customer asking us a question about data, us having to go to the data provider and ask a question. And then us not really having a great answer other than like, hey, the person that we get this data from, kind of messed up. And so that was where it became a business choice where I was like, obviously, this visibility data is so essential to the way that our platform runs and the way that we communicate with customers, that we decided to make a pretty significant investment in creating that data set and managing it ourselves and iterating on it quickly as we did with the rest of the product.

Brian Glick 00:43
Welcome to supply chain connections. I'm Brian Glick, founder and CEO of chain IO. And today we have Jake Hoffman on the show Jake is the CTO at Gnosis freight Gnosis is a supply chain software company who's taken a very interesting journey that Jake will tell us about he's got a wide range of experiences, working with freight forwarders and shippers, B slash bcos and with other tech companies, and really has set an interesting perch of how to bring these parties together and find real product market fit across a number of different constituents. So that further ado, here's the episode.

Brian Glick 01:24
Jake, welcome to the show.

Jake Hoffman 01:26
Hey, thanks, Brian. Happy to be here, man.

Brian Glick 01:28
Why don't we start off with a little bit about your history and how you ended up with Gnosis?

Jake Hoffman 01:33
Sure, yeah. You and I were joking, I think before we started recording that everybody in logistics technology was just born to be in the industry, right? They're born and just like, hey, I want to be in logistics. I actually studied chemical engineering and undergrad. I went to Auburn University and undergrad, I was friends with Austin, our CEO and founder. And I kept seeing him do all these cool traveling trips when he was going to Vietnam and going to Thailand. And I was literally messaging them, Hey, man, what are you doing? And he was like, I'm working on something and international aid, you should check it out. And we kept in touch over the years. And eventually, he convinced me to come to lunch with them and beautiful Charleston, South Carolina, where we're located and took me to lunch on the water. And I was sold. I was sold at that point. And that's kind of where Gnosis was born. Austin started here in Charleston working with a freight forwarder. And then, you know, you and I've talked several times about how Gnosis has kind of evolved over the years. But everyone that works at Gnosis is in Charleston, started working with a freight forwarder and transitioned to working with pretty much strictly VCOs. And then now that we have a whole data business now, and it's kind of all transitioned from there, but so chemical engineering somehow to international freight, and here we are today.

Brian Glick 02:43
So what was it? Besides how wonderful Austin is, that kind of attracted you to it at the beginning?

Jake Hoffman 02:51
You know, it was something about the way that he described this, like, Hey, there's this whole world that you have no idea about, that's kind of hiding in plain sight, because you drive by the giant ports, and the giant cranes picking up containers, and I didn't realize it was hiding in plain sight. I was driving by it all the time. And I thought it was cool, but I didn't pay attention. And then he started showing me how all the data works and where it starts and where the container ends and what's inside. And it was just amazing to me, this whole new world of international freight that was kind of unveiled. And then even more like, you think that there's all these experts, and there are experts. But the problem is so big that there's still a lot of stuff out there to be solved. And that was an attractive thing to me. Yeah, the thing that has kind of kept me going for 20 some odd years. And this engineering problem is almost unsolvable. Yes.

Brian Glick 03:43
It's just fascinating how many sharp edges there are to this. You know, the thing I always say is, every time you see a hole, and you feel like I have to go down this hole and learn, you know, realize that there's 1000 holes under that hole that are all equally deep, and each of them and it's just holes all the way down.

Jake Hoffman 04:03
Exactly. So yeah, there's problem on problem, one problem, and then all these people are trying to solve it together. You know, it's not like one person has it. And it's a secret. It's collaboration in the supply chain, as we know, and as we all know, is key. And everyone's trying to figure it out, too. So it's pretty cool.

Brian Glick 04:20
So what problems specifically are you guys working on at Gnosis and kind of how did you get to that problem?

Jake Hoffman 04:27
Sure. Yeah. So from the times when we worked with you a couple of years ago at the very beginning of Gnosis and we originally were working with a freight forwarder we were automating a lot of internal processes, we are auditing drayage invoices and chassis invoices and streamlining things for the freight forwarder. And then it gradually transitioned to like a customer facing portal where it was like, the BCo wants to see a lot of this data we have internally but we're not really sure how to surface only the things that they need to see and only their shipments and so on. And then we started just working directly With the bcos, where our customers are the freight forwarder. And then the bcos would say, Hey, this is great for our shipments that are moving with one, freight forwarder. But we have these shipments that we have direct contracts with ocean carriers. And we have four different freight forwarders we work with. And so we worked on how to stitch all this data together to show this BCo, the cargo owner, a full picture of their inbound supply chain, right, so we were mostly working with importers at that time. And so it became like, stitching together all the different shipments, figuring out how to organize all the tracking data. Now we had sourced container tracking data from freight forwarders, for a while from individual software providers, the people in this space. And then we've now eventually built our own container tracking engine. And that's a totally separate part of our business that we have been investing heavily in the past year and a half, two years. The problem that we're solving for the importers and exporters that we have an export product to is organizing the data that surrounds their entire supply chain, servicing things that are important that you know, demurrage, detention alarms and things like that identifying the exceptions, and then also developing those on the edge the transit or the execution modules, if you will, of how they can actually not just have visibility into what's going on. But then how do they actually manage that and do stuff with that data that we're giving them?

Brian Glick 06:22
So I'm gonna ask you to put on a product manager hat for a second here because I have a question. I'm curious, in your experience, kind of working with bcos and forwarders. And the software providers that you also kind of share data and sell data to, I guess more in those first two categories, the forwarders versus the bcos. When it comes to getting product feedback, and how actively they participate in the product, envisioning and development, what's different between working with a forwarder? And working with the BCo? Right?

Jake Hoffman 06:57
There's the simple differences, right? That's not unique to their, I guess, customer persona, from speaking with my product manager. They care about different things. You know, I think everybody cares about the demurrage detention, streamlining, you know, those kinds of things. But from a freight forwarders perspective, they care about the box itself, they care about, is it cleared customs, you know, is it in demurrage? Is it in detention, those kinds of things, there's a separate priority that the BCO has where we help them by joining all this data together to know not just what's the status of the box, what's the status of this container. But what's inside of that, know if they have a furniture, you have a lot of furniture customers if they have some furniture that's sold, and it's one of their most important customers, and it's in a specific container. And they want the ability to say, hey, we want that container out first. But to a freight forwarder, or a drainage provider, or the terminal operator, whoever it may be, they just see all these boxes, and they know that they're all for X customer, right. And so there's just different priority sets. And that's how we have the container tracking data. But then it surfaced to each of these different parties, in its own way to help them understand what's important and what they want to do with it.

Brian Glick 08:08
So that difference between kind of understanding the box and understanding the SKU or the part or the priority, the part has that dragged you into having to have more, say corollary data about not just what's in the box, but the importance or the you know, the liver of recommitment dates or those type of things around that, like have you had to go deeper into the bcos company to kind of understand that information.

Jake Hoffman 08:38
Yeah, absolutely. And it's, you know, we talked about how difficult the problem of international freight is in itself. And then, you know, tag on that everyone is interacting, and international freight has their own terminology, their own important thing. So I mean, you mentioned like a committed delivery date, and then there's a sold value, you know, for some of our furniture customers that are selling, hey, the furniture in here has already been sold to a retailer until like, that's important, because it's already sold versus it's going into a warehouse to sit in inventory. Then there's, you know, we have tire customers, and it's, they have to get the tires to an auto manufacturing facility by x date, or else they're going to shut down an entire line. The dollar value associated with things like that is incredible. And so we've had to kind of extrapolate, like, we have our core data, and then we have all the customer specific data that's always changing. And it's a hybrid between like we have something standardized and something specific to the customer that we're always working on. So I mean, to answer your question, we've done everything from CSVs being emailed to we have a full API where we've kind of organized the SKU level with the purchase order or tagging it to containers. We've kind of run the gamut of how we integrate and figure out how to work with customer specific datasets.

Brian Glick 09:54
So I'll ask a potentially dangerous question here, but I'll give everyone a little bit of back Around about our history that, yeah, when you guys started in the forwarder site, you use chain IO to do some of your early integration work, and then eventually decided to kind of bring that in house. And especially as you moved into the shipper side, you saw it as more of a core thing, kind of when it comes to buy versus build, whether it's with us or with anything else, kind of how did you go through that journey of deciding what to buy? And what to build?

Jake Hoffman 10:23
Sure. Yeah, definitely. I mean, to your point, when we were primarily working with freight forwarders, you guys had the expertise there. And working with the systems that freight forwarders are used to, it just made financial, logical sense for us to work with a partner like you guys that had all that pre existing connection built. And to figure out how, and for us, it was fantastic. We had thought through every single time we sign up somebody, it's as easy as you know, extending, I mean, it could be just an API endpoint, but really extending the same source of data with a different identifier, and you guys handle everything else, right? That was the dream there. Then, as we, you know, got into all the different shipper systems and everything they were doing. A lot of it was how they live in the world, for the most part and how we saw people interacting and international traders and excel sheets. And so it was a lot like, they get reports every day, or they have an export that comes out of their ERP system. And so we to your point on the builder by piece, we did an analysis of like, hey, if we tried to ask chain IO to figure out how to map all of these different spreadsheets into like one singular database like that sounds, you know, tough for them. And it's tough for us to but that's something that's not really like a core product that made sense for any company to have like a product built around to that was something kind of just logically made sense. On the builder, you know that that's something we've gone through a lot, especially with the data piece, we could talk about that and a different piece of the conversation. But where do we source the data from one place? Do we just rely on freight forwarders to send us tracking information, and we ended up just deciding to build it ourselves. But that was kind of a totally different situation than the integration work. All right.

Brian Glick 12:04
Well, let's go a little deeper. And I'm fascinated, right? Because I think it is probably one of the existential questions in the industry right now. So I think we're gonna get something important here. And I don't want to drag you too deep into this whole, okay, but it's sort of like, how close to the center of your product, you think that something has to be to build it? Right? Like, you know, if I'm building just a TMS, I might say, hey, visibility, data is one of 1000 things I need to do. But if I'm building a visibility platform, obviously, visibility data is the thing I do. Yeah. So like, kind of where in that Bullseye deve I know, it's a very abstract question. But like, how do you think about how close it has to be?

Jake Hoffman 12:46
Yeah, I mean, with us and the way that we've kind of evolved over the years, it really was more of a try and try again, and see what sticks. We tried several different, you know, data only providers where that's their core business, we tried, you know, sourcing it from the different parties that our customers interact with. So setting up EDI integrations, to get 315 messages, every time a customer brings on a new freight forwarder those things were becoming a pain and a limiter, right. Then when we went to the singular data providers, it became like us just playing middleman between our customer asking us a question about data, us having to go to the data provider and ask a question. And then us not really having a great answer other than like, hey, the person that we get this data from kind of messed up. And so that was where it became a business choice where it was like, obviously, this visibility data is so essential to the way that our platform runs and the way that we communicate with customers, that we decided to make a pretty significant investment in creating that dataset and managing it ourselves and iterating on it quickly as we did with the rest of the product.

Brian Glick 13:55
It sounds like you know, everyone always says fail fast. Everyone always says, iterate. Everyone always says, you know, lean and all of these things. But it sounds like you guys have a culture where you live that pretty effectively, you know, as evidenced by really having multiple different, you know, evolutions of the product. But there's a word that I personally hate, which is pivot. I use it, but I hate it. Because I think there's a little bit of in the startup world that pivot is like a euphemism for we screwed up, which is not really always true. And there's different sizes and shapes. But you guys have pivoted a bunch, what's been the kind of cultural or emotional journey inside the company of going through those kinds of changes.

Jake Hoffman 14:44
Sure, that to your point is like maybe it gets a negative connotation sometimes. I mean, maybe I consider it a pivot. But really, it's kind of like our core business idea of, like, a collaborative environment to manage the entire lifecycle. Have a shipping container. That's still the core business, right? That's still like that ethos, what Austin kind of put a sticky note on the wall when I was there for day one is still what we aim for. But the idea of building our own data and getting more into, like the PIO and SKU level data for is all kind of customer driven just by market demand, right. And, as we know, building an entire container tracking engine, versus buying it and sourcing it. We needed the ability to ingest data through a web hook and understand API's and do those things when we were buying data from other people, right? And then as we expanded our engineering team, and we started trying to build it ourselves, I was one of our first coders. But by no means am I capable of standing up an entire cloud based infrastructure. I don't know half of that stuff works. We have some super smart people that handle those things. I kind of just like, hey, this is kind of what we need to happen. Can you guys do that? How does this work? Teach me? How do I connect to AWS? Like just yeah, this is funny seeing some of the stuff that I used to do. And I had no idea what I was doing. But just building out that team and the people that we hired, we were really lucky that they were enthusiastic about it and wanted to come in and solve that giant problem. We've tried to instill the culture of like, everything's a challenge, we think we can be the best at it. So let's compete, and let's do it. Right.

Brian Glick 16:25
What's the most fun for you in this?

Jake Hoffman 16:28
Yeah, I mean, to your point earlier about, like, everything in international trade is you plug one hole and another hole opens, and there's so many problems, it's a deep problem. And there's things in the industry that that it's just never ending, it's a really complex engineering problem. Some people may not like it, I love the idea of coming into work every day, and there's always something new, a new problem to solve. There's always a, how can we use data from US customs that complement our current container tracking data? How can we work with our customers to understand, what are they trying to say and say that they're using our system? And then they're exporting in an Excel and they're going and sending an email to all the truckers with, Hey, pick up these containers that are coming into the port? How can we automate that for them? How can we start dispatching delivery orders, there's so many things in international freight. And it's always evolving, always changing that I love the idea of coming in every day and never doing the same thing.

Brian Glick 17:27
It hit me that I have two consecutive days that are the same. The third day I'm gonna quit. There we go. I'm right there with you. You know, when you're doing the building the systems especially for you're working with bcos, you deal with a lot of different parties, right, the forwarders, and the carriers and the DRE providers, and so on and so forth. If you had a microphone, and you could just scream at all of them to fix one thing, which drives you crazy.

Jake Hoffman 17:57
Yeah, that's tough. And it's the way you like, to your point, you know, working with the BCo. You know, I think we kind of gravitated towards them just in the way that the market pulled us because at the end of the day, they're the people at the end of the supply chain that are the customer of everybody, right. And so when we're working with them, and you know, for some of the things that we do with moving data about containers, and the ancillary processes, does require that collaboration from a trucker, a freight forwarder, a customs broker, whoever it is, if there's a missing piece in the puzzle that might have a piece of information that we need to make something happen, I'd say like, I would open, you know, turn the microphone on and say, Hey, we need standard data from everybody, if we just had standard data that fits our data model from all of you guys, and things that would make our life so much easier. But then at the same, you know, level is that each party in that supply chain that we're talking about has their own data model. Like we said earlier, everybody cares about something different. They have their own, like Job, or it's a delivery or this purchase order, they have their own kind of unit of whatever business they're working in. And so it's really, really difficult to sit there and scream at all these different parties and say, Hey, you guys don't need to fit our data model. Sure, that would be perfect. In a perfect world. It all fits one model. But I don't think that that's necessarily each person's job to do it for us to just sit here as the software provider and say, Hey, give me standard data. That's where we've kind of taken the idea of like, how can we facilitate getting whatever information we need, but then put a translation layer between all these different things and just make our own data model is kind of the approach we've taken,

Brian Glick 19:43
which is exactly exactly what we do. Yeah. Same approach, right? Do you swim upstream for long enough and you just get tired of things? Yeah, I remember

Jake Hoffman 19:52
Looking at your API documentation the very first time and seeing like your standard Chain.io shipment JSON example right? Like, that's it, you guys did that, that's like a somewhat similar model we've taken on working with some of the bcos. And what they care about. That's the goal.

Brian Glick 20:08
You know, the thing that probably sits below that, that maybe is even more frustrating is sometimes you want to sit with a freight provider and say, could you do this same shipment the same way? Twice? Right? Could you put the data in your data model consistently? Yeah. Like, that's the one that always has gotten even when I was a forwarder. So we would sit there and go, Why can't we get New York and LA to keep the shipment? Or the custom sentry the same way? Right, right, for the same customer with the same product? Yeah, right. You know, there's so many fields in the TMS and so many different ways to interpret what's going on. Right, this person enters transport legs on a shipment, this person doesn't enter the legs, but they add notes. And this one remembers 10 through Pio numbers, and this one enters Pio numbers and reference fields and this, that and the other and what's an arrival that you paid?

Jake Hoffman 21:06
What does the arrival date mean is that the day that ship docks, when it starts getting unloaded is the day that ship enters the port? The date anchors off port even at times when la Long Beach had 100 ships off the coast, their arrival could be 21 days before the birthday. So Right.

Brian Glick 21:26
I guess what would be nice and get it? I'm not signing up to lead this industry charge but I've always felt that we don't need another EDI spec. But we need a better glossary. Okay. Right. Like these are what the words mean.

Jake Hoffman 21:41
Yeah, that's awesome. Yeah, like that would be. That would be nice, though. Super nice. And then not just that, but then like, hey, everybody agrees that we're gonna all do that, right. And then that's where the, you know, the DCSA, and the new like, track and trace standards that are continuously evolving. Those are great. I'm sure you guys work with those a lot where like, the DCSA keeps in it's I think they're on like three point something now where they're continuing to evolve with what that container tracking model looks like. Initiatives like that are awesome.

Brian Glick 22:14
They really do a lot of thankless work there. And then everyone complains, they don't do it fast enough.

Jake Hoffman 22:19
It's tough to the point we're saying everybody calls it something different. So awesome for them for tackling that and taking that on.

Brian Glick 22:25
So they're doing a great job. What else has you excited? What other tech or initiatives Do you see out there that you think are fun?

Jake Hoffman 22:32
So I'll be super cliche, and say that I'm super excited about some of the implications of the new AI technology, and the chat IGBTs of the world and how that translates to logistics. And now not in the usual like, Oh, it's just I can ask it, where my shipment is. And it tells me Of course, there's chat bots, and you know, things like that, that can understand data and do those things. What's super interesting to me, and while we've worked on some and continue to work on is using that like the large language models, to take all the unstructured data that it's like a commercial invoice, a packing list and email, a text message, whatever it might be that information that's super important for international freight, a bill of lading, right? And digest it and have that AI understand it enough to put it in that data model that we want. Right? I talked about that like a standard if we could get everybody to participate and say, Hey, this is the standard data model. And we're all going to participate. Well, if you can use some of that AI technology to understand the translation between what one person says and another and take an Excel sheet and convert it to what needs to go into an API. That's something that's super exciting that I've seen, some companies work on and do some really cool stuff with.

Brian Glick 23:56
So there's a thing that's been rolling around in my head, I'm gonna try to put it into words and see what you think of it. But I'm struggling a little bit to get this thought out. But the way that, you know, a chat GPT works, right? It isn't prescriptive, right? So it isn't a flowchart and a decision tree. And you know, it sort of, you know, it takes input and it gets to an output, but it's not really deterministic, intentionally. When we think about supply chains, across the industry that gets baked into the assumption that a supply chain starts with a prescriptive plan at the beginning. And you execute that plan, right, I am going to decide, before I produce the product that that product is going to move on an ocean can vessel from Shanghai to LA and then be trucked to Charleston, you know, or it's going to go through the Panama Canal or whatever the case may be. And we think of this as okay now. Have a command and control. And then we have exceptional cases, right? And I've always thought that the way that packets are delivered on the internet is not prescriptive, right, the packet finds its route to its home by moving through a whole bunch of routers. And right people don't know this, but like, if you're streaming a Netflix video, one frame of the video to really oversimplify might go through one part of the network, and then there's an issue and then the next frame moves in a different path, but gets from the Netflix server to you. And they find their way. And there's a lot of error correction, and things to kind of smush everything into this nice path. We don't think about supply chains that way we think about them as like, Oh, if the one connection, you know, if the signals going from Netflix at the line that gets cut outside your house is the line that we thought that it was going to go over, it won't just reroute naturally to the other line. Right. Okay. And I wonder if when we look at all of this generative AI and chat GPT and the like, whether there's a point in the future where people think about supply chains differently. And they think about it as I'm dropping my product into the network. And I have an SLA of when it needs to be where it needs to be. And I'm gonna let the network or the providers, you know, sort of bid on a cost, right? I'm willing to spend this much to move it and I needed this fast, right? And let it happen, as opposed to the BCo saying, I want it to happen this way. Right? Very different way of thinking of the world. And then I mean,

Jake Hoffman 26:38
That is awesome. That's a fantastic idea. And then you know, to that point is when a container misses a train shipment, or you know, it gets stuck, any one of those things happen, that the network could theoretically, take all the information about what containers are on that vessel and where they need to go and optimize after that, right. That's a perfect application of it. And then on top of that, too, we've talked to some of our customers about it, and we kind of do it. But there's a limitation to it. We can't rebook a container that's already in the ocean. But transit times are what they are like, it takes a certain time for a container to get from, you know, the Shanghai to LA or we'll do the Vietnam to Charleston. But the demand for whatever that product is, if it's not already sold, all of a sudden, in Charleston, a lot of stuff gets bought, a lot of couches, get bought from a certain retailer, or one of those things. What if you could, you know, use all that information around your sales data and move it through some of these AI models to take all the inventory you have on the water. And instead of going exactly to those distribution centers that you had it to go to gets rerouted. It's like, Hey, this is actually a much more optimal way for this to work, right. And so like another level of like, what you're saying, and then not just letting it like, reroute how it gets to that place, but also like decide that it goes to a different place would be really cool.

Brian Glick 27:59
Yeah, I think where supply chain professionals have struggled, and certainly the Tech have the data haven't been in a point of enameling. A lot of trust here is there's a moment like, autonomous driving analogy, but like, there's a moment where you let go of the steering wheel, right, and trust that you're not going to crash into the wall. Right? That's a scary, scary moment, especially in an industry where we hire specifically for the personality type of people who hold on to steering wheels really tightly. Yeah, right. Like, that's who we recruit into this industry. It's like people who are very methodical, and definitely, you know, data driven, but not like, Hey, I'm just gonna sort of throw my containers into the wind, and you know, like, let them carry like a bunch of dandelion spores, and just some of them will land where they need to land and everything will be great. Right? Yeah, they'll sell it over here, because that's where the container ended up. Yeah, the supply

Jake Hoffman 28:54
The Chain.io planning team in a large company is different from the import management team. So it's like there's a pitcher and a receiver. And it's difficult to get all the information that everybody has into making that decision. So to your idea, maybe there is a future state where some of these large language models that crunch billions of parameters could figure out how to do that. Right.

Brian Glick 29:18
I guess you guys don't have that done next week, then,

Jake Hoffman 29:21
man. Well, you said, Move fast. And so we'll try it. It'll reroute your container to Malaysia, and then that didn't work. Well. So

Brian Glick 29:28
this Super Bowl T shirt in Malaysia, it'll be perfect. Yeah. Cool. So what do you guys have coming up? What's exciting about the next steps for analysis?

Jake Hoffman 29:38
Sure. So one, you know, we've done very little marketing the past couple years, you know, we've kind of been a little bit under the radar to a certain extent where we haven't raised money. We haven't done any advertising or marketing or any of those things. And I feel like we're finally at a place where we're starting to turn the microphone on a little bit, so to speak. We've been at TPM the past couple years and it was just fantastic. We love going to TPM, my favorite time of year, to get to nerd out with all my fellow logistics people, and I absolutely love it. We're going to more conferences this year, all the ones coming up and you know, a few weeks and in the fall. So that's super exciting. We're hiring more people and we're growing. We're actually interested in logistics technology, a software company. We're all in the office in Charleston. So we make everybody come to the office every day. And we're all in the same building. It has its advantages, it has its disadvantages, but we've seen a lot of positives with it that we really like. We know that that'll change in the future. But it's been really cool for us to do so far. I'm sure that we'll hopefully see you guys at a few conferences coming up soon.

Brian Glick 30:43
Yeah, well, I'm sure we'll cross paths again somewhere. So

Jake Hoffman 30:45

yeah, definitely. It's exciting times, you know, the logistics, technology space. It's crazy to think about, like what I've been, I've been in the industry for six years now. Wild to think about what it was before that and wild to think about where it's gonna go in the next five to six years.

Brian Glick 31:01
Right? I'll leave you with the thought that I was told on my first day in logistics tech, that if we could tell the customer five days after a vessel sale, what product got onto the ship, we would change the world? Wow. So that was the state that it was in in 2000.

Jake Hoffman 31:20
So I like to think we've got that.

Brian Glick 31:24
We definitely have that because ISF made that. You gotta know now, that was the gold standard back. That was five days, like imagine issuing a purchase order. Yep. And 105 days later, you find out whether the product shipped or not. And it was just blind between those two points.

Jake Hoffman 31:41
Yes, essentially. So you to your point. ISF really did fix that. Yes, it

Brian Glick 31:45
did. So. Okay. All right. Well, we're running up on time. So we'll put some links to notices into your LinkedIn in the show notes. And I always love chatting and looking forward to seeing you in person soon.

Jake Hoffman 31:57
Yep, sounds awesome, Brian, I really appreciate it, man. Glad to be here.

Brian Glick 32:00
And thanks a lot. Thanks so much to Jake for wonderful insights. And for humoring me with my crazy ideas. As I mentioned, you can find information about Gnosis in the show notes as well as on their LinkedIn. And be sure to check out some exciting announcements that we have coming up from chain IO on our blog. We are releasing some very, very big product enhancements this summer that are really going to expand the ability for different parties in the industry to work together. So I'll just leave that teaser out there. And y'all make sure you're following us on social media so that you can hear the latest updates, and I will talk to you next time again. I'm Brian Glick, founder and CEO of chain io.

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written on June 21, 2023
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