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00:00:01
Finding Product Fit in the Supply Chain Market with Jake Hoffman
134 Plays2 years ago
In this episode, Jake Hoffman, CTO of Gnosis Freight, joins Host Brian Glick, CEO of Chain.io, to discuss:
- 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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Transcript
Strategic Shift in Data Management
00:00:04
Speaker
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
Introducing Jake Hoffman
00:00:23
Speaker
up.
00:00:23
Speaker
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. 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.
00:00:43
Speaker
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 slash BCOs and with other tech companies and really has set an interesting perch of how to
00:01:12
Speaker
bring these parties together and find real product market fit across a number of different constituents. So without further ado, here's the episode.
Jake's Journey to Gnosis Freight
00:01:24
Speaker
Jake, welcome to the show. Hey, thanks, Brian. Happy to be here, man. Why don't we start off with a little bit about your history and how you ended up with Gnosis?
00:01:33
Speaker
Sure. Yeah. You and I were joking. I think before we started recording that everybody in logistics technology, it was just born to be in the industry, right? There's like, it was 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 and I was friends with Austin, our CEO and founder. And I kept seeing him do all these like cool traveling trips when he was like going to Vietnam and going to Thailand. And I was, I literally messaged him. Hey man, what are you doing?
00:01:59
Speaker
And he was like, I'm working on something in international trade. You should check it out. And we kept in touch over the years. And eventually he convinced me to come to lunch with him in 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.
00:02:16
Speaker
That's kind of where Gnosis was born.
Evolution to a Data Business
00:02:18
Speaker
Austin started it here in Charleston working with a freight forwarder. And then, you know, you and I have talked to 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, transitioned to working with pretty much strictly BCOs. 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. So what was it?
00:02:45
Speaker
besides how wonderful Austin is, that kind of attracted you to it at the beginning.
00:02:51
Speaker
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. You know, cause 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.
00:03:18
Speaker
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.
Tech Solutions for Supply Chains
00:03:34
Speaker
The thing that has kind of kept me going for 20, so many years in this is the engineering problem is almost unsolvable. Yes. It's just fascinating how many
00:03:47
Speaker
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 don't realize that there's a thousand holes under that hole that are all equally deep in each of them and it's just holes all the way down.
00:04:03
Speaker
Exactly. Yeah. There's problem on problem on 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. So what problems specifically are you guys working on at Gnosis and
00:04:25
Speaker
Kind of how did you get to that problem? 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 were auditing drage invoices and chastity invoices and streamlining things for the freight forwarder. And then it gradually transitioned to like a customer facing portal where it was like.
00:04:49
Speaker
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 that were customers of the freight forwarder.
00:05:03
Speaker
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 do we like 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.
00:05:27
Speaker
I mean, so it became a like stitching together all of the different shipments, figuring out how to organize all the tracking data. You know, we had sourced container tracking data from freight forwarders for a while, from individual software providers, the people in the 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.
00:05:54
Speaker
The problem that we're solving
Building an In-House Tracking Engine
00:05:55
Speaker
for the importers and exporters, and we have an export product too, is organizing the data that surrounds their entire supply chain, servicing things that they're important, demurged attention alarms and things like that, identifying the exceptions, and then also developing those on the edge, 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?
00:06:23
Speaker
I'm going to ask you to put on a product manager hat for a second here, because I have a question I'm curious about. In your experience working with BCOs and forwarders and the software providers that you also share data and sell data to, I guess more in those first two categories, the forwarders versus the BCOs. When it comes
Adapting to Market Changes
00:06:45
Speaker
to getting product feedback and how actively they participate in the product envisioning and development,
00:06:53
Speaker
What's different between working with a forwarder and working with a BCO? Right. There's the simple differences, right? That's like not unique to their, I guess, customer persona. If I'm speaking with my product manager, they care about different things. You know, I think everybody cares about the demurged attention, streamlining, you know, those kinds of things.
00:07:12
Speaker
But from a freight forward perspective, they care about the box itself. They care about, is it cleared customs? You know, is it in demerge? 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. You know, if they have
00:07:37
Speaker
of furniture. We 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, then they want the ability to say, hey, we want that container out first. But to a free forwarder or a Gerais 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. And so there's just different priority sets. And that's how we have the container tracking data, but then it's surface to each of these different parties.
00:08:04
Speaker
In its own way to help them understand what's important and what they want to do with it so that difference between Kind of understanding the box and understanding the skew or the part or the priority of 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 delivery commitment dates or those type of things around that like have you had to go deeper into the
00:08:35
Speaker
BCO's company to kind of understand that information.
00:08:38
Speaker
Yeah, absolutely. We talk about how difficult the problem of international freight is in itself, and then you tag on that everyone interacting in international freight has their own terminology, their own important things. You mentioned a committed delivery date, and then there's a sold value. For some of our furniture customers that are selling, the furniture in here has already been sold to a retailer until that's important because it's already sold versus it's going to a warehouse to sit in inventory.
00:09:08
Speaker
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
Challenges in Data Standardization
00:09:21
Speaker
things like that is incredible. And so we've had to kind of extrapolate, like, you know, 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 some things standardized and some things specific to the customer that we're always working on.
00:09:37
Speaker
So I mean, to answer your question, we've done everything from CSV is being emailed to we have a full API where we've kind of organized the skew level with the purchase order or tagging it to containers. We've kind of run the gambit of how we integrate and figure out how to work with customer specific data sets. So I'll ask a potentially dangerous question here, but I'll give everyone a little bit of background about our history that you guys started in the forwarder side.
00:10:04
Speaker
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.
00:10:14
Speaker
When it comes to buy versus build, whether it's with us or with anything else, how did you go through that journey of deciding what to buy and what to build? Sure. Yeah, definitely. I mean, to your
AI's Transformative Role in Logistics
00:10:25
Speaker
point, when we were primarily working with freight forwarders, you guys had the expertise there in working with the systems that freight forwarders are used to.
00:10:34
Speaker
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, hey, every single time we sign up somebody, it's as easy as 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,
00:11:01
Speaker
you know, got into all the different shipper systems and everything they were doing. A lot of it was they live in the world, for the most part, and how we've seen people interacting in international freight is in Excel sheets. And so it was a lot of 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 build or buy piece, we did an analysis of like, hey, if
00:11:24
Speaker
We try to ask Chain.io to figure out how to map all of these different spreadsheets into one singular database. That sounds tough for them and it's tough for us too, but that's something that's not really a core product that made sense for any company to have a product built around. That was something just logically made sense. On the build or buy, that's something we've gone through a lot, especially with the data piece. We could talk about that in a different piece of the conversation, but that was where
00:11:51
Speaker
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, right? Well, let's go a little deeper. 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 going to get something important here and I don't want to drag you too deep into this hole, but sort of like,
00:12:18
Speaker
how close to the center of your product do 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 a thousand things I need to do. But if I'm building a visibility platform, I've seen visibility data is the thing I do. So like kind of where in that bullseye do you, I know it's a very abstract question, but like, how do you think about how close it has to be?
00:12:46
Speaker
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
Gnosis's Growth and Industry Reflections
00:13:06
Speaker
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?
00:13:16
Speaker
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.
00:13:36
Speaker
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. It sounds like everyone always says fail fast, everyone always says iterate, everyone always says lean and all of these things, but it sounds like you guys
00:14:06
Speaker
have a culture where you live that pretty effectively as evidenced by really had multiple different 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.
00:14:36
Speaker
What's been the kind of cultural or emotional journey inside the company of going through those kind of changes?
00:14:44
Speaker
Sure. Pivot 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 of 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.
00:15:11
Speaker
But the idea of building our own data and getting more into the PO and SKU level data has all been customer driven just by market demand. And as we're building an entire container tracking engine versus buying and sourcing it,
00:15:29
Speaker
We needed the ability to ingest data through a web hook and understand APIs 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 how half of that stuff works. We have some super smart people that handle those things. I kind of am just like, hey, this is kind of what we need to happen. Can you guys do that?
00:15:57
Speaker
How does this work? Teach me how do I connect to AWS? Like just, yeah, it's 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. What's the most fun for you?
00:16:27
Speaker
Yeah, I mean, to your point earlier about like, everything in international freight is you plug one hole and another hole opens and there there's so many problems. It's a deep problem. And there's things in the industry that there's just never ending. It's really complex engineering problem. Some people may not like it. I love the
00:16:47
Speaker
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 to complement our current container tracking data? How can we
00:17:01
Speaker
work with our customers, understand what are they trying to do? Say that they're using our system and then they're exporting it in 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. I always say that the time that I have
00:17:31
Speaker
two consecutive days that are the same. The third day I'm going to quit. There we
Closing Thoughts and Future Updates
00:17:35
Speaker
go. I'm right there with you. You know, when you're doing the building these systems, especially for when you're working with BCOs, you deal with a lot of different parties, right? The forwarders and the carriers and the dry 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, what drives you crazy?
00:17:57
Speaker
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 like 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, you know, data about containers and the ancillary processes does require that collaboration from
00:18:26
Speaker
a trucker, a freight forwarder, a customs broker, whoever it is, if they're a missing piece in the puzzle that might have a piece of information that we need to make something happen.
00:18:36
Speaker
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 lives so much easier. But then at the same level as that is like 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,
00:19:03
Speaker
Job or it's a this 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 all need to fit our data model
00:19:18
Speaker
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 as kind of the approach we've taken. Which is exactly, exactly what we do. Same approach, right?
00:19:47
Speaker
Do you swim upstream for long enough and you just get tired? Yeah. I remember, you know, looking at your like API documentation the very first time and seeing like your standard chain IO shipment, Jason example, right? It's 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. You know, the thing that probably sits below that, that maybe is even more frustrating is
00:20:15
Speaker
You know, 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 got, even when I was in forwarders, like we would sit there and go, why can't we get New York and LA to keep the shipment or the custom century the same way? Right. Right. For the same customer with the same product. Yeah. Right. You know, then there's so many.
00:20:45
Speaker
fields in the TMSs 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 PO numbers and this one enters PO numbers in reference fields and
00:21:04
Speaker
this, that, and the other. And what's an arrival date mean? Yeah. What does the arrival date mean? Is that the day the ship docks, when it starts to get unloaded, is the day the ship enters the port. Is it the day it anchors off port? The times when LA Long Beach had 100 ships off the coast, their arrival could be 21 days before the birthing. So who knows, right? I guess what would be nice and, God, I'm not signing up to lead this industry charge, but would be
00:21:34
Speaker
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. Yeah. That's awesome. Yeah. Like that would be, that would be nice. That would be super nice. And then not just that, but then like, Hey, everybody agrees that we're going to all do that. Right.
00:21:53
Speaker
And then that's where the, you know, the DCSA and the new like track and trace standards that they're continuously evolving. Those are, you know, great. I'm sure you guys work with those a lot where like the DCSA keeps in its, 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. They really are. They do a lot of thankless work there. And then everyone complains they don't do it fast enough.
00:22:19
Speaker
It's tough until the point we're saying is everybody calls it something different. So awesome for them for tackling that and taking that on. So they're doing a great job. What else has you excited? What other
00:22:29
Speaker
tech or initiatives you see out there that you think are fun. 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 GPTs of the world and how that translates to logistics. And I'm not in the usual, like, Oh, it's just, I can like 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.
00:22:57
Speaker
What's super interesting to me, and what we've worked on some and continue to work on, is using the large language models to take all the unstructured data. That's like a commercial invoice, a packing list, an email, a text message, whatever it might be, that's information that's super important for international freight. A bill of lading, right?
00:23:21
Speaker
and digest it and have that AI understand it enough to put it in that data model that we want. I talked about that 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,
00:23:35
Speaker
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. There's a thing that's been rolling around in my head. I'm going to try to put it into words.
00:24:01
Speaker
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, it isn't prescriptive, right? So it isn't a flow chart and a decision tree. And, you know, it's sort of a, you know, it takes input and it gets to an output, but it's not really deterministic intentionally. When we think about supply chains,
00:24:30
Speaker
across the industry, like it's just a baked in assumption that if 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 or, you know, or it's going to go through the Panama canal or whatever the case may be.
00:24:58
Speaker
And we think of this as, okay, now we have a command and control and then we have exception cases. And I've always thought about 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 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
00:25:24
Speaker
one part of the network and then there's an issue. And then the next frame moves it 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 signal is going from Netflix at the line that gets cut outside your houses, the line that we thought that it was going to go over, it won't just reroute naturally to the other line. Right. Okay.
00:25:54
Speaker
And I wonder if when we look at all of this generative AI and chat GPT and on 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 going to let the network or the providers, you know, I sort of.
00:26:23
Speaker
bid on a cost, right? I'm willing to spend this much to move it and I need it here 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.
00:26:38
Speaker
And then, I mean, that is awesome. That's a fantastic idea. And then, you know, to that point is when a container misses a terrain shipment or, you know, it gets stuck. And, you know, one of those things happened 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 perfect application of it.
00:26:59
Speaker
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 like 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.
00:27:17
Speaker
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.
00:27:42
Speaker
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. Yeah. I think where supply chain professionals have struggled and certainly the tech and the data haven't been in a point of enamoring a lot of trust here is
00:28:09
Speaker
There's a moment like autonomous driving analogy, but like there's a moment where you let go of the steering wheel 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 onto steering wheels really tightly.
00:28:29
Speaker
Yeah, right like that's who we recruit into this industry is like people who are very methodical and 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 family line spores and just some of them will land where they need to land and everything will be great Right. Yeah, I'll sell it over here because that's where the container ended up Yeah
00:28:54
Speaker
The supply chain planning team at a large company is different than the import management team. And so it's like, there's like 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 of that where some of these large language models that crunch billions of parameters could figure out how to do that. Right.
00:29:18
Speaker
I guess you guys will have that done next week then. Oh man. Well, like you said, move fast and break things. We'll try it and it'll reroute your container to Malaysia and then we'll be, ah, that didn't work. We'll sell those Super Bowl t-shirts in Malaysia. It'll be perfect. Yeah, there we go. Exactly. Cool. So what do you guys have coming up? What's exciting on the next steps for, for Gnosis? Sure. So one, you know, we've done very little marketing the past couple of years. You know, we've kind of been,
00:29:46
Speaker
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 our microphone on a little bit, so to speak. We've been to TPM the past couple of years, which is fantastic. We love going to TPM, my favorite time of year. Get to nerd out with all my fellow logistics people and I absolutely love it.
00:30:09
Speaker
We're going to more conferences this year, all the ones coming up in a few weeks and in the fall. So that's super exciting. We're hiring more people. We're growing. We're actually, it's interesting for a 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.
00:30:35
Speaker
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. Yeah. Well, I'm sure we'll cross paths again somewhere. It's exciting times, you know, the logistics technology space. It's crazy to think about like what have been, you know, 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 going to go in the next five to six years. Right. I'll leave you with the thought that I was told
00:31:05
Speaker
on my first day in logistics tech that if we could tell the customer five days after a vessel sales, what product got onto the ship, we would change the world. Wow. So that was the state that it was in in 2000. So I'd like to think we've got that. We definitely have that because ISF made that, uh, you got to know now that was the gold standard back then was five days. Like imagine the issue approach shorter. Yep.
00:31:33
Speaker
And 105 days later, you find out whether the product shipped or not. Man. And it was just blind between those two points. Yes. Essentially. So. You to your point, ISF really did fix that. Yes, it did. So. Okay. All right. Well, we're running up on time. So we'll put some links to no assistance to your LinkedIn and the show notes, you know, get always love chatting and looking forward to seeing you in person soon. Yep. Sounds awesome, Brian. I really appreciate it, man. Glad to be here. All right. Thanks a lot.
00:32:02
Speaker
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
00:32:23
Speaker
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, CEO at Chain.io.