Eze Peralta:
0:35
When you're doing something by yourself, if I'm trying to solve a problem and I don't know how to do it, then maybe I Google, maybe I use AI or whatever, but I'm still using my brain to solve the problem. Once I solve it, I learned something, right? Same with human interaction, maybe some employee making a mistake also reveals that there is a process that needs to be improved, right? So then you can so I think error, and it's part of life, and it's also part of learning. And I think we are entering to this notion of we, we have these agents doing all the work for you, but then after you see the work done, have you learned something from that process?
Blythe Brumleve:
1:31
The freight tech hype cycle is real, but behind the buzzwords are folks actually building the plumbing that keeps your freight offs running as a Peralta is one of them, and he is back with SPI logistics, VP of technology on the everything is logistics podcast, in order to break it all down for us, I'm your host, Blake Milligan, and of course, we were presented by SPI logistics, and I was just telling Eze his last appearance on the podcast a couple years ago, I believe is our most popular SPI logistics episode. So sorry to everyone you know within SPI that's come on the show, but we will love Eze. We
Eze Peralta:
2:10
We are good friends. So I so it's all good. I think.
Blythe Brumleve:
2:14
no competition. So let's, let's set the stage. So for SPI, for folks who may not be familiar with your role within SPI, can you kind of give us a high level overview of what you do on maybe a day to day basis, a weekly basis. What does I guess a week in the life of Za look like?
Eze Peralta:
2:36
Well, there's we have two main areas. So one is the things that we are building internally. The other area is the things that we need to maintain or integrate or are in relation to tech vendors. And so there's a bit of swing between between those two aspects. So a lot of the time is meetings, meetings with vendors trying to align the road maps of what we're trying to do with what they're trying to do, trying to keep up with all the the new features that the new vendors that come up. It's it's a lot of time, because evaluating tools and evaluating next steps and trying to sometimes might maintain the roadmap, but at the same time being flexible enough to pivot. So a lot of a lot of the time is, is that kind of more strategic point of view? And then there's a lot of time that is just coding or, you know, jumping into the the actual implementation, a lot of modeling and diagramming with the with the business users as well. A great deal of the of software development. A lot of people focus on on the coding side with software development, but in my experience, software development is a lot about modeling and understanding what you need to build before starting to build. Right? It's like, for example, you're going to build a house. You're not going to start, you know, cutting wood and laying bricks right away. You need some sort of blueprint. You need some sort of understanding of what needs to be built. You need to understand, even, you know the terrain where you're going to work with and, and, and a lot of other factors. So a lot of the time goes into that as well. And
Blythe Brumleve:
4:39
so for folks who may not be aware, you know, SPI Logistics is a freight agency, and so you don't have any some freight agencies will have an in house brokerage team or an in house trucking team. SPI doesn't do that because they their internal team is set up and dedicated just to support their agents. And so you guys are, I believe and correct me if I'm wrong, but you guys have a general tech stack that you use, but then you also accommodate the freight agents, and maybe if they have, like, a particular tech tool that they like to use, you'll incorporate that into sort of, I guess, the mothership of SPI Is that accurate?
Eze Peralta:
5:18
Yes, yes, correct. So we try to embrace also that diversity in our agent agents network. And you're correct. Yes, we you. Where we spend quite, quite, quite a bit of effort on understanding those needs and also offering the tools that we have to enhance the existing operations when, when agents on board with us. So because maybe they already have certain workflows that that, that they already applying, and that's effective for them. So we don't force anybody to, okay, this is the way how you should do it, but we do offer the tech stack we have, but also open to incorporate and integrate other technologies that agents might bring when, when they on board and, yeah, trying, trying to augment and enhance their operations and and then this goes in line we're saying before, of understanding what is needed before going into the how we're going to do it right. Once we know what is needed and what is the most helpful for our agents, then we can decide, okay, you know, how we implement it sometimes, that is getting a new vendor. Sometimes is, you know, building some customization on an existing tool. It could take any shape, basically.
Blythe Brumleve:
6:44
Are there any sets of tools that your agents are using every day?
Eze Peralta:
6:51
Well, the TMS is what our agents use every day. And I think the operations we have the track and trace capabilities that that sometimes some agents would go directly into the tracking portals because they have specific needs, or some other agents will use them. Use these tracking capabilities within the TMS. Similarly with posting, sometimes people would use, you know, posting directly to the boards. Sometimes people wouldn't do it through the TMS, but we try to have a layer of control of all that data and where it goes, where it's coming from. So we can also offer some insights and analytics on on that data as well. And then we have, yeah, for example, tools for procurement, capacity or risk management that we created internally. And a lot of the times, what we do is try to aggregate that very vast landscape of data into more actionable information. So you know, instead of our agent having to go into five different portals to make sure that their carrier is not fraudulent, then we kind of like consolidate all that data. We say, hey, yeah, this is, this is a good to go carrier, or this is flagged for these reasons, yeah, trying to also combat that tiredness that comes sometimes people drop the ball on certain things related to risk, because it's just too cumbersome going into different places to having to check in 10 different portals To make sure that you know your your provider is good to go. So people stop doing it right, people, people stop checking because it's just cumbersome. So we try to also think about that, and, like, make sure that we make it easy. So, so those tools are, are used. Oh, that's super interesting.
Blythe Brumleve:
8:47
So you essentially are, you know, using different maybe, and I'm just spitballing here, but like a highway and a carrier, sure. And you know, some of these, these vendors that do are in the same realm, but do things a little bit differently, but they all help give a fuller picture. And so you're able to build that into a dashboard for your agents,
Eze Peralta:
9:09
yeah. And sometimes, even aggregating it. We have tools where the result is, you know, you're good, you're not good and up to that point. And then if you want to see more details, you can go into the portals, or you can expand on those details. But yes, we do that, like with all the compliance vendors we have, because sometimes, you know, maybe highway has some insights or flags about specific things, like, for example, where these people, these carriers, are accessing the system from. But then maybe freight guard, they have very you know, if people who are reporting these carriers but right care for one, for example, so you need both right? Because one will give you, you know, certain insights. The other one is going to give you, I don't know, highway for example, give you insurance information, inspection information, but if someone got burned by by a bad actor, the first thing they going to do is, most likely, is reporting it to 401, so we also want to, you know, action on those, those reports as well.
Blythe Brumleve:
10:15
So one of, and I heard you talking about this with Chris jolly on the freight freight coach podcast that you guys were at technovations, Tia's, technovations in in late 2024 I'm sorry I missed that. It was actually it. Jacksonville, Florida, but I was getting married that week, so I couldn't, I couldn't sneak away to go to that to go to that conference, but I heard that AI was just everywhere, as it is with most you know, freight conferences right now, what's what's your? I hear you laughing there. What's your, I guess, overall take on, is it hype? Is it a buzzword? Is it? Yeah, is it valuable? Is it kind of all of the above?
Eze Peralta:
10:56
I think, I think it's all of the above. And I think AI is a very vast field, so it's not the same. Saying, You know what? We are using the hype, this current hype wave of AI is most related to large language models, which is, you know, the chatgpt. But artificial intelligence is something that existed for a while. Now, the computing has gone, you know, it's more available and for companies to use these large language models and the training techniques have improved, but before we had machine learning or other types of of artificial intelligence applied to analytics or different aspects, like forecasting and these kind of things. So I do find it very valuable for a lot of use cases. We use it internally a lot in our like our dev team uses this. Use it quite a bit. But also we we are cautious to not try to chase AI or implementation or any tool like AI or any other tool, just just for, just because everyone else is doing it, or just because, you know, it appears to be the solution, magic solution, to all these use cases we we are of the idea that alignment between business and technology is key. You know, integration and governance of all the integrations is key. Governance of data is key. So those things what we focus on, and if there is, you know, if AI can help us to achieve that, to achieve the business outcomes that we want to achieve, and improve the KPI we want to achieve. Then we evaluate it as we evaluate any other tool, and then we we apply it, right? But we are, you know, we try to keep focus on what is important for our agents, what is important for for the business as an organization. And, yeah, we do use AI and in many ways, and we are adding more use cases to it. But at the same time, I, I think there is this notion that is going to come and solve everything for everyone, and suddenly it's going to replace workers and all this thing and like, that's that's not something that, I mean, we don't see it that way as much. Yeah, you can, you can automate phone calls and these things. But what about the when things go wrong, nobody wants to talk with a machine. And most of the logistic business is managing risk right. And are you going to let a machine to manage that risk for you? Are you going to let the machine do that negotiation or do that, you know, relationship building for you. So it's yeah, if, if you have a mature enough system, then you can connect with your shipper via API, and then you don't need to have like a voice agent, you know, calling a shipper or but at the same time, there are certain, there are certain use cases that, yes, you know, for support, we had these autoresponders for phone for years, where you say, hey, you know, give me your load number. You just type it in the phone. And so it's not very No, it's not that different than that. And then, and then you have also the ethics aspect, which is, I was reading a LinkedIn post. I don't remember who it was from, but it was something in the in the lines of, I was talking with an AI rep, and I asked if it was an AI. They said no, but then they found out that it actually was an AI, but it seems that this AI was trained to lie, right, to say that it was not an AI. So I think, you know, we should keep being honest. So that's non negotiable, right?
Blythe Brumleve:
15:26
No, that's a very good point, and I think that that's something. That's a concern that we've raised in the past and in previous episodes on when do you disclose that you're talking to an AI agent? And I think most people are fine talking to an AI agent when they need an answer quickly about something, where is my load? Something like that, but for a deeper maybe customer relationship. There is a level of you should probably disclose you know that that information as quickly as possible, so then that way the person can make that preference on if they want to talk to somebody real or talk to a virtual agent. I would be curious to know what other maybe use cases are you seeing? You know, maybe two different use cases. One where, you know, it's machine learning that's actually doing the job and you're using that. But then, on the flip side, a large language model. I'm curious about the use cases for each of those that you're seeing.
Eze Peralta:
16:28
So machine learning is mostly used on, you know, analytics and forecasting or finding anomalies or things like this. So you have a you know, data from the last, let's say, 10 years, and then you try to find, you know, seasonality. You try to find, like, certain patterns that would be more difficult to find just manually, you're trying to dig into all that data, so and so for that is, is, that's a good, good use case. And you can also train it to find trends, you know, oh, we're, you know, when these, when these metrics are, how metrics relate, oh, when these two metrics are going down, it means that your business is trending up, or, I don't know, or you start finding those relationships. And so for analyzing those huge amounts of of data, it's, it's machine learning, it's, it's, it's valuable. And for large language models, I think the important part to understand is that no matter what the what the vendors say, they don't reason right. Reasoning is a different thing. They just predict the next token, the next the next symbol that's this should be there according to their calculation or their training. So what I find really interesting for as a use case is categorization and then interpreting natural language text, for example, emails, tagging an email saying you can plug it into to your inbox and say, Okay, I have 20 call requests. So in a day I have 20 quote request. I have 10 track and trace requests, or where's my load kind of questions. Then I have 15 carrier carriers asking for posting. And then I have three complaints and and then you can, you know, categorize all of that, and eventually you're going to have enough data to understand your your own inbox, for example, much better, right? And then from there, you can automate, oh, when, when these type of request comes in, or this type of email comes in, then you can auto generate a response, as long as it fits with the with that category, right? So categorizing, I would say, understanding topics or subject on on text, and then creating some sort of simple, simple responses or template or responses for certain type of inquiries. Those are, I think, really good use cases. And
Blythe Brumleve:
19:17
then I with, as you were talking, I was thinking about, you know, is there any, I guess, safety issues that go on with, you know, using a large language model that, you know, maybe agents should be a little cautious of, of putting, you know, personal information maybe into some of these systems. Or is it that concern maybe largely overblown? No,
Eze Peralta:
19:40
I think, I think that it's a it all depends on, on the architecture that you have behind it, right? So, for example, we were talking with our team about cases where you see people doing this that they call now vive coding, which is like,
Unknown:
19:57
I hate that phrase.
Eze Peralta:
20:00
It is, what it is. And yeah, and then people were able to hack applications built in this way in 30 minutes, just because the credentials were all pasted over in the code. So you could just go into the repository, public repository, and see all the credentials for, for, for different APIs and things. Because, yeah, if, if you. Know what you're doing, you wouldn't do that, right? So if you don't know what you're doing, then you maybe think it's fine. You trust that the AI will do it okay for you, and then you just ask the AI, oh, make it secure. That just doesn't work. You can't just tell the Oh, make make this application for me. Make it secure. I wish it was like that, but, you know, there's so much more to it. So I think security is one of the big, big topics to think about when thinking about AI
Blythe Brumleve:
21:02
for sure, what about from the email side of things? Because I personally struggle with sorting through my email on a daily basis, and I can't imagine what you know a typical freight agent is going through with their email inbox. What kind of tools are you seeing that's helping to categorize those emails? Is it all strictly done through the TMS, or is it, you know, a bunch of different tools that that can help, you know, categorize those emails? Maybe, you know, auto respond to them. You know, get rid of the junk. Is it a bunch of tools, or is it one or two really good tools?
Eze Peralta:
21:39
So, I mean, there are a lot of tools and probably missing a lot here, but so are the PMs that we use ravinova, they are adding now features that natively allow you to to use AI and then connect your email to it and, and they will It will create loads for you. You will create truck postings for you, and, and, and also, with all the automation that exists already available in Salesforce, you can create these responses back and connected to all the the the other existing work. So, so for us, that's that's a really good one, and levity, I think, is doing a lot of a lot of work on that as well. I I personally like the what they have there. And then what I'm seeing also is that even the existing client email clients are starting to add all these features internally, like, if you have, for example, Outlook, you could grab, you know, power automate, which is their little automation tool, and you could have little workflows that categorize emails and use the AI Within the Microsoft environment. And that should be at least, you know, if you already trusting outlook, then you know you can keep your your existing data already there, and it will not leave that, leave that environment and that that might be interesting. Gmail, I think it's also adding all of that. And I think eventually all the gmss are going to start doing that. I know that other GMs for brokers as well, have already that. I know that. Yeah, tools like pray the also have some email automation going on. I haven't tested it freely, but yeah, I think all of those tools should do a good job on, on, on, you know, categorizing emails. It's not at the same time I've seen more and more orchestration tools, or the tools that allow you, like, to create your own automations. And a lot of people are starting to build their own automations around email. I was talking with Sarah from other logistics, and she was telling me about some AI tools and that they're using for some use cases. And I think it's called sola solar, solar AI. And so any tool should work again. It all comes down. I want to bring it back to have you modeled your business process. Do you know what your business process is? Do you know how you're going to measure if your process is working or not? Have you Do you know what's the outcome that you're trying to achieve? Because if you don't know that, then you're going to go into it. How the implementation without knowing the what, and then you know it might fail, and then you're going to think that the problem is the tool, that the problem is, oh, this AI is not working, or this doesn't work, but, but how? How are you even measuring if it's working or not? Because you didn't know what your performance was before, you don't know the metric that you need to look at to know what your if your performance improved. So then it's like, it's all going to be gut feeling. And of course, the gut feeling at the beginning of implementing a new technology, the gut feeling is going to be frustration, most likely. But if you have the metrics in place and the business processes modeled properly, then you're going to realize that, oh, well, I'm frustrated because I don't know how to use this tool, but objectively, these metrics are improving, right? So I like always taking it back to that, like the business process. Needs to be solid and needs to be documented, needs to be refined. And it means because, if not, you end up with the vendor deciding for you how you should be working. And that's, I think, advice for anyone evaluating tech. You know, tech vendors will generally tell you that they can do everything. You're going to ask them, Oh, can you do this? They're going to say yes, because generally, you're talking with a project manager or a sales a sales representative. And then they're going to go to the developers, like teams, like my team, and they're going to say, Hey, I sold this. I sold this new feature. Now you need to build it, and then when you roll it out, then you're like, well, but like, how does this match with my existing workflow? What? And there's a lot of friction. So if you don't know exactly what you're looking for in terms of business processes, it's going to be harder for a vendor to to be effective, right? And it's, sometimes it's not even a problem of the vendor, because, you know, these are tools, and if you don't know what to do with the tool, then also it's, you know, it needs to be on both sides, a commitment on both sides.
Blythe Brumleve:
26:51
Yeah, no one wants to do the the boring and really underrated, challenging part is documenting your processes, because you have to be prepared to rip them all out if they're not working. But just simply documenting them is, I find it personal experience, just very like draining on my brain, but once I get a dud, then I'm so relieved, because then I can figure out, okay, what do I need to do? What can I outsource? What can a tool do? And I'm curious as as to how you how do you approach helping agents document their process?
Eze Peralta:
27:31
So something that we do is visiting agents, because being on site with with the people who are executing the tasks and executing the processes, I'm able to understand much better all the nuances, right? And also, you know, I don't like this idea of the tech team being, like, isolated, and then, you know, requirements come in, and people, you know, the dev team doesn't know what the process is, and we try to all of our team is involved in, in these modeling sessions. And we generally we try, because we know also that agents are very busy, and we want to also take out too much time or effort on that. But when we do this visit, we try to document as much as we can about what we see, and then we come up with a plan of, okay, this is this is the process that we see. These are the points, the critical points that we could maybe improve. We have these tools available to help you on this particular point and asking a lot of questions. I think listening and asking it's key, because, again, if we in a way, the tech team is like a vendor for the agents, right, in a way, like it's an internal vendor, but we need to provide something that makes sense, and in order to be able to do that, we need to understand what the problems are. And so yeah, a lot of Yeah, listening and going on visits, because on a zoom call, you can get an idea, but sometimes you just need to be there to really to hear the phone ringing and, oh, how many you know, how much of the time is being spent on answering this call? Oh, what if we have a tool here that can filter out these calls and like, you know, tell you which, which call you should take first. And how do you, you know, how does that impact your overall time to cover a low for example? Just, just to give you one example, something that we did was also one of our agents was having a lot of inquiries for for posted loads from from boards. And what we were they were copying and pasting a template to respond to these inquiries. We're like, Oh, what if we try to automate that? So we just set it said, you just set up all the your pricing in the TMS, and then we can just find the load that you're asking for and then give them back that information. And if it's covered, instead of telling them, oh, it's covered, we find similar loads in similar lanes, so we think, Oh, that load is covered, but we have these other loads, right? But we. Needed to go visit the agent to really understand that, right?
Blythe Brumleve:
32:10
How do you approach, you know, when you're you're thinking about, you know, onboarding a new agent, or maybe it's a current agent that is, is looking at a new tool. How do you decide what to say yes to and what to maybe caution them on?
Eze Peralta:
32:28
Yeah, I don't want to be super repetitive, but I bring it back to what is the use case that you're trying to resolve? What is the business process that this fits in? Because sometimes you realize that by moving a few pieces in a different part of the board, right then you are also, you know, changing the tension on the part that you're interested in. So sometimes it's okay, let's try to quickly understand at least the skeleton of the process that you're doing, and understand if, if it's a tool, what you need, or maybe it's a shift on some other structure, right? That might be, maybe it's a tool that we already have and that they don't know that we have. Maybe this a training issue. Maybe it's a lot of times comes down to training. It comes down to knowing the the tools that we have available, because there are so many that sometimes it's like, well, if you're an agent who is doing truckload only, maybe you don't even know that we have an LTL program, or that we have a customer portal that so they maybe are looking for a vendor that might give them a portal for LTL integrations. I don't know. And then, hey, we, we already have that. We, you know, we, we can just set it up for you and say, a lot of times, goes back to that understanding, where does that fit in the overall business, business process, and if it's needed, then we're going to talk with the vendor and make sure that that can be shared with the entire network. And sometimes we set it up for a specific office, and we help that specific office to get that one vendor that they need. Because reality is that there are certain vendors that make sense when you have a specific type of office or specific type of shippers, and there are, so it's like, why other agents should go through the process of onboarding that if, if they don't need it, right? But, yeah, it'll go long story short, it comes back down to business process, and where does that fit. And technology should be an enabler of that, not just something that you bolt on trying to just, you know, fix it on itself, a square peg into a round hole, almost. Yeah, yeah. And in my experience, those type of involvements have not gone very well. A lot of times it's a solution in in search of a process, right? So let's try to understand the problem first and see if this is a good solution.
Blythe Brumleve:
35:22
So with all of the you know, remote offices, the tools we've talked about. How do you approach the cybersecurity elephant in the room?
Eze Peralta:
35:32
Well, we are, we're cloud. Our TMS is cloud based. So one a lot of is delegating, the main, the main operational system that is the TMS. They're getting a lot of that security to to a company like Salesforce that has, you know, invest billions of dollars in in security and and so we don't hold, we don't have anything on prem, on on servers, on prem. Then for the tools that we build internally, we are cloud based, but also use containerized workloads that are kind of like disposable so if like it's we use, yeah, so it's not that we have the one big virtual machine with everything in it. We have each capability has its own containers, and then we have event driven system that connects everything together. So we try to incorporate the security on on the design itself, of the solutions that we do so that's on the aspect of more like infrastructure security. You know, security access to your database. We don't have one central database where everything is there. I mean, we do that have a data warehouse, but the operational systems you have, each feature will have its own little. World, and if that, if that data goes away, we could reconstruct it, for example, right? So we try to incorporate all that security by design. We use for all of infrastructure for the tech nerds out there, we use infrastructure as code. So in order to deploy infrastructure like databases, Virtual Machines and these kind of things, we are not just going into a UI or depending on a person doing their job right. Everything is templated and has all the security measures already in those templates. So when we deploy it, for example, our databases don't have access to Internet. In order to access our database, you need to go through some other some other steps, and only our containers and virtual machines can access those databases. They are not open, right? Yeah, and we tried to control our APIs in that way as well. Where if something doesn't need to go over the internet, it doesn't, it doesn't go we only expose to the internet the things that like have to be exposed. So
Blythe Brumleve:
38:23
you guys are building fortress over there is essentially what you say with several boats to protect the fortress.
Eze Peralta:
38:30
Yeah, we have in our team. We have Valentin. He's very, very strict on that aspect as well, and he knows quite a bit on that front of infrastructure security. And so we tried to incorporate all that, you know, from the get go, it's like we we don't deploy something if it doesn't have these characteristics, because it will be irresponsible. And also, in our case, we are agent based, so data needs to be siloed, so we cannot expose, you know, customer data from one agent to another agent. So all of that is controlled in the TMS, but also we have our own separate user pool and security settings that make sure that all the tools that we build on top of the TMS and the tools that we build custom also have that characteristic right
Blythe Brumleve:
39:26
in your experience, or maybe what you've seen at other, you know, agency, companies or brokerages, how I guess, involved is the internal IT team when it comes to, like, freight fraud. Are you guys, you know, in there, you know, trying to help combat it from a digital perspective, like digital warfare, or is that sort of a separate team that, you know, maybe closely works, you know, with the IT team, I'm just trying to, I guess, maybe understand where it kind of plays a role when it comes to the just the dramatic increase in freight fraud across the industry, I think
Eze Peralta:
40:03
in order to have an effective security strategy. You need everyone to be involved. And it needs the business users to to to be the ones also pushing the the risk management initiatives. In our case, we have very lucky that everyone in our team are, it's very much aware our, yeah, our VP of Operations, VP of Finance, VP, you know, Director of Career procurement, and everyone. It's very, very much aware of all of this. And they come up with the initiatives to us, then we tell them what is possible, then we discuss what ways we could be vulnerable. But the IT team is very aligned with the rest of the business in these initiatives, and we all know and understand, and we try to emphasize that with that team as well, that what the scenario is, what we are fighting against and but I think it needs to be. It cannot be just delegated to it, because the business user know a lot more than they they think sometimes about security, because they know how a business process work. They know, for example, with when you see these schemes of fake paperwork, or these carriers buying MC numbers and doing all these maneuvers, you know, they know the business user. Know the intricate intricacies of that from from, from the business perspective, and it can, can put in place measures to but we need to know how that works sometimes, and we need to be, yeah, in collaboration constantly. I think in order to be effective, you just, you need that. You need everyone on board. It's not going to work if just delegated to it, because it's just going to be a very. Partial view, and you're going to be covering this side, but then they're going to attack you on the other side. And a lot of the a lot of the threats are social engineering. So there's only so much you can do on the IT side against social engineering, because if people are giving away their passwords because someone just tricked them into doing it,
Blythe Brumleve:
42:26
you know, is that sort of, the crazier side of it that you've seen is just people willingly giving up that information. Yeah, our
Eze Peralta:
42:34
James or CFO always says it don't click the link. Like, if you get an email with a link that just don't click it, like, you know, you can reply back. You can call the person. You can, you know, try to, but don't, don't click it, because most of the times when something happens that someone gains access to an email or something like that, is because someone clicked the link, or someone got a call, got tricked into going to a website that was not the actual website. And there's always something like that, and so, yeah, I think definitely the most scary part, and the most difficult to combat is the social engineering threats.
Blythe Brumleve:
43:19
Are there any examples that you've seen that have like, maybe at other companies or something, what they're dealing with that has the creativity of a fraud scheme has almost impressed you.
Eze Peralta:
43:36
What impressed me is when the quality of the emails that people are crafting and sometimes even how they are putting malicious code inside of PDFs, for example, so you're not even clicking a link. You're getting, you're getting an email from your boss saying, Hey, can you check this report for me? And and it's looks exactly like them, and maybe it is coming actually from there, from their inbox, because they got access to that inbox and and they say, Oh, I'm not taking any link, even if it's it's a file, right? So you click on the file and then, and then you're done. So I think, yeah. Or when at Tia, the keynote speaker was was talking about how, with deep fakes, you can have someone, some AI, talking to you as if it's your boss, for example, asking you to put money on an account, or things like this. And in this case, the CEO was talking with the CFO on a video call. But it was not the CEO, it was just a deep fake. And they asked them to put money on an account for for an acquisition they were going to do. And they did it and like, how can you combat that? Yeah, it's, it's very it's very hard, right?
Blythe Brumleve:
45:04
Yeah, I think on the podcasting side of things, I have warned my family that I'm like, 30 seconds of audio is all it takes to deep fake me. And so if you get a call from me at you know, first of all, I don't call them, I text them. Probably know that something was up. But if you get a call for me, we've developed, like, a safe word within the family that you know, you're going to use in the event of something like that happening, where we would call and, you know, ask for money or something like that. We have a family safe word. It kind of sounds like maybe we need to do that at the corporate level
Eze Peralta:
45:40
too. Oh, that's definitely, that's multi factor authentication. Like, When? When? When people do their multi factor authentication on their phone asking you it's that it's a shared secret that only the people that it's securing that secret know, and then it can be used to to to unlock, right, whatever you need to unlock. And in this case, the this, that safe word is acting as that, you know, multi factor that are you actually you? It's like, so, yeah. But first things first, if you don't have multi factor authentication on in your organization by default for absolutely everything, then you should be looking into doing that first, because that's another thing, is that we're talking about really social engineering schemes and everything. But then people just don't have their multi factor codes on, on, on, on their phones. So you're basically that, you know, hackers and the bad actors. They try to find the easiest path for getting it. So, yeah, just start there that that was that solves like 90% plus of the of the phishing attacks. Is
Blythe Brumleve:
46:58
there any freight tech that doesn't exist that you wish
Eze Peralta:
47:03
existed? Yeah? Yeah, wow. I I think maybe all the integration landscape in the in the freight tech world is it's kind of all over the place. So I think some sort of standardization of what we all think a load is, what, what, what kind of events are relevant to, to a load or so, I think some sort of, I don't know if it's a software itself, some sort of agreement or standardization on how we're going to communicate these systems, between systems. EDI was an attempt to to achieve that, and I think it is still being used big in part, because of that, because it was somehow somewhat successful in in you know this creating a base standard that then everyone need to derail from that standard, and ended up doing like each area its only world, but with APIs, for example, it's happening that every API is different, and you need to, you have all these point To point integrations, and there's no, yeah, there's no standard. And I think there's, it generates a lot of waste for a lot of organizations, having to maintain software that is just a pipe to put data from A to B, right? So that, I would say, yeah, a lot of the time, even for tech vendor, even for vendors, it's like, it's not valuable work. It's just something that you need to do in order to get data. And then you start, you know, adding value with your product.
Blythe Brumleve:
48:55
Now, last few questions here for a potential agent that's thinking about making the switch, is there anything that they need to do on the tech side of things, on their end of things, to better prepare them for, for making the jump to, you know, maybe, hopefully, SBI, but maybe another company. Is there any, I guess, maybe standardization of of what you would recommend for an agent to get ready to make a switch.
Eze Peralta:
49:26
I think, I think asking the questions to to the to the agent network that that they're going to they're evaluating about what's their tech stack. But no, no, no, not as as listing the vendors that they use, because that you could have a really good list of vendors, but not have them working together. Well, right? So it's okay, can, can this network give me all fulfill all the use cases that I need to fulfill? For example, we offer, we push data to shippers. Sometimes they needed as a CSV file with a very specific format. Sometimes they needed the API. Sometimes they need to be Adi. Sometimes they need it as they come. Sometimes they need it in a schedule, right? So if you have shippers that are requiring this type of technology, then you need to ask very clearly at the beginning, hey, can you push data to my shippers in the way they need it. How long it takes for you to complete the new integration if a new shipper needs it? For example, can you automatically quote, because I have a shipper that asked me to respond to a quote within a minute? Can you do that like and same for you? Know what carrier fraud, carrier vetting and compliance is like, asking the questions, you know, but trying to get to the proper depth of the question. It's like, Oh, do you use one question could be Oh, do you use highway? Or do you use RMS, or do you use my care packets? That's one way of asking another. Another way of asking is like, how do you handle with a carrier trying to do this? How would you prevent this from happening, or how do you use those tools in order to protect me or protect my business? And I think, trying to find the depth in the questions beyond, oh, we use this vendor, okay, but how you use it? Why you use it? Why that one or not the other one? Like trying to get a bit more deep into into the into the ask, into the asking.
Blythe Brumleve:
51:37
Is there any? Well, actually, one more quick question that just popped in my head. AI agents, not necessarily like the call ones, but the the ones that are promising, you know, to fix, you know, be your internal marketing department, or be your internal sales department. It Do you see the rise of sort of a AGI agents that you know, you have a little you know, minions that are doing all of your work for you? Yeah.
Eze Peralta:
52:05
So to be honest, like from, from what I've been seeing so far, I think we're far from it still, whenever I try to, I mean, I use coding tool that has some sort of agent in it and and it also has, like an auto complete feature. I end up using the auto complete more than the agent, because a lot of times the agent is just going to go in a loop of trying to solve a problem, but in a very kind of, like, naive way, and maybe it's not understood for certain tasks. Yeah, I can see it working for certain tasks, but I don't see it happening at the level that is being advertised. Of, oh, now you're going to have these digital workers that is going to just do all of your calls for you, and it's going to give you all, you know, all these benefits, and I have yet to see something that shows me that that's possible and that's and also, one aspect that we, I was talking with my team yesterday, is what you get, you know, when you're in when you're doing something by yourself, like, if I'm trying to solve a problem and I don't know how to Do it, then maybe I Google, maybe I use a AI or whatever, but I'm still using my brain to solve the problem. Once I solve it, I learn something right. And same with human interaction, maybe some employee making a mistake also reveals that there is a process that needs to be improved, right? So then you can so I think error and and it's part of life, and it's also part of learning. And I think we are entering to this notion of we, we're going to have these agents doing all the work for you, but then after you see the work done, have you learned something from that process? So I see one of the possibilities is that our learning curve, it goes up, up, up, up, but then now we are just delegating all this resolution to these automations, but we don't know how they work, because nobody knows what an AI agent is thinking, and nobody is even if we could, no one is going back and say, Oh, how did you reach this conclusion? Was it accurate? Was it not what can I learn from the process of reaching the conclusion? So I am a believer that that process of reaching a conclusion is really valuable, and learning from these processes, learning from mistakes, is valuable. And I think sometimes the promotion of the type of tools forget that part, and they're just too focused on the solution. Instead of trying to understand how we get to a solution, how the problem works, why the problem even exists, could we define this problem out of scope so we don't even have to solve it because it doesn't exist anymore? You know, trying to find more depth, I think, I think it comes down to depth. I think a lot of these tools are being promoted with not enough depth in mind, just very tactically, and we're not thinking about, you know, maybe you needed to, maybe you needed to walk the path. Make a little mistake, that is, as long as it doesn't destroy you, right? You needed to walk the path. Make that mistake, learn from it, improve and keep going and and you can still do that while you're using AI agent, but if you just delegate everything to to and then you don't think about it anymore, then we're becoming kind of like thinking lazy, right? Like we're becoming lazy at thinking and I personally don't like that. I
Blythe Brumleve:
56:16
completely agree, and I echo that statement, because I on one side of the coin, I will say that, you know these even like Grox deep research tool. I love it, but I use that inside of chat GPT in order to help me come up with an interview flow. And it'll I did it for this interview. For example, I took our previous episode, I took the transcript. I said, Give me a landscape of, you know, the current freight trends and freight tech trends and technology and things that are on the market, analyze the transcript and then come up with an interview flow based on that. And I would say probably 60% of the questions were pretty good. But if I didn't do the active listening to our previous episode and also to other episodes you've been on. I wouldn't have been able to, I think, craft a better interview for the sake of this conversation. And so it's it. I don't know that that's something that you can replace. Is that active learning by doing it you have to still do the thing. And, you know, maybe there's some ways where you can automate the boring stuff, but there's still, you know, a creative aspect that you create, a problem solving and learning that I think is still needs to be prioritized. Yeah,
Eze Peralta:
57:35
and in this case, what the process you're describing you were driving the process you were not delegating to an agent that was driving the process, an AI agent that will drive it. But you were driving the process. You were using a tool to categorize to give you, you know, some help, but you were in the in the driving law, and I think that's important and and also it's like, it's, it's fun to be a human, and it's fun to connect with humans. Big fan of humans. So
Blythe Brumleve:
58:06
don't tell the AI that it
Eze Peralta:
58:10
already knows. Probably that's a topic for another, another podcast. But like, then there is that aspect of like, do you want to be working with an AI agent? Or you want to, you know, are we working for? What are we working for humans? Are working for ourselves, for human species, for that's more philosophical, maybe, but that comes into play too. When we're talking about, you know, replacing people, it's like,
Blythe Brumleve:
58:40
I don't know, I want to do more of the things that I like doing and less of that. And I think that that's, you know, sort of the the common complaint I hear with AI and automation is like it's taking away, or some people feel as if it's taking away from the things that we want to do more of instead of the things that we don't want to do more of, which is, like, I don't know, clean the bathroom, or, you know, fold your clothes. Like nobody wants to do that. But, you know, AI is not fixing that yet, and that's what we want it to fix. We don't want it to take away the things you know, that do make us human, creative problem solving, you know, creative indent adventures, things like that, talking to people, developing relationships with people. I think all of those things are really important. You kind of hit the nail on the head for the rest of you know, I guess say 2025, and beyond. Are there any, you know, new tech solutions that you guys are working on, or integrations that you could share with us, or or things you're thinking about that you think the audience should know
Eze Peralta:
59:40
we're working continue improving on, on the capacity, capacity tools that we have. We know that the you know, market still somehow lose on that sense. But we know, you know, being prepared for, for for different market conditions as as they show up. So adding more sources of capacity to our capacity hub tool continue adding on, you know, more data into our risk management tools. Also we're adding these more features on the AI email, you know, creating loads from emails and and these categorizing email requests, working also on automation of of bidding to the shipper side so and, and also a lot of work on on the back office, because we, we need to, we need to provide, you know, best service in the office, because our agents, we work a bit differently than maybe other other agent models, where agents just do the operation, they complete the load, and then we take over the entire AR and AP cycle, right? So in order for that to be effective, we would need to have a high level of automation, high level of efficiency on the back office. So a lot of work on 2025 is also going to go into continuing the already, already highly automated back office is going to continue being more automated and providing our staff with tools to, yeah, maybe to reduce some of their data entry and so they can focus on being more analytical, on on the audit and these things so, so yeah, that's those are things we're working on. A
Blythe Brumleve:
1:01:44
lot of work you guys are got ahead of you for this year and beyond, but I'm sure you know a lot of the agents are extremely thankful for the investments that you guys continue to make into the platform and the program itself as a where can folks find you, follow more of your work, maybe connect with you at a future conference.
Eze Peralta:
1:02:02
Yeah, so my LinkedIn. I am sa Peralta. You can find me there. My email is E Peralta at SPI three, bpl.com you can email me and I'll try to reply as soon as you can. Yes, no, I don't use email bots, so if I take time, it's because I'm actually responding. And if you see me at any conference, generally, I go to Tia and capital ideas and technovations and maybe a few other more. I don't have anything planned as of now. For for conferences, we have our annual agent conference this week. Yeah, exactly. It's gonna be fun. I be fun. But yeah, if you see me at any conference, just Yeah, would love to connect. Well,
Blythe Brumleve:
1:02:54
perfect. This was a great discussion. Hopefully people you know, like this one just as much, hopefully more than than the previous episode that we did together. But I'll be sure to add all those links into the show notes. Just make it easy for folks, but as a this is great. Thank you so much for your perspective insight. Thank
Eze Peralta:
1:03:10
you very much. Need for having me. Absolutely
Blythe Brumleve:
1:03:16
thanks for tuning in to another episode of everything this logistics, where we talk all things supply chain for the thinkers in freight, if you like this episode, there's plenty more where that came from. Be sure to follow or subscribe on your favorite podcast app so you never miss a conversation. The show is also available in video format over on YouTube, just by searching everything as logistics. And if you're working in freight logistics or supply chain marketing, check out my company, digital dispatch, we help you build smarter websites and marketing systems that actually drive results, not just vanity metrics. Additionally, if you're trying to find the right freight tech tools or partners without getting buried in buzz words, head on over to cargo rex.io where we're building the largest database of logistics services and solutions, all the links you need are in the show notes. I'll catch you in the Next episode in Go, Jags, you,
