Ep. #69: Harish Abbott, CEO & Cofounder, Augment

This week, Andrew sits down with Harish Abbott, CEO and cofounder of Augment, the AI teammate for logistics. Harish says, “Logistics is broken,” and in this episode, he goes deep into just how broken, talking about the inefficient ways information is shared between numerous parties on any given shipment. He talks about how overwhelmed operators are by emails and manual processes, leading to costly inefficiencies, a lack of time for creative work, high turnover, and burnout. The former CEO and cofounder of Deliverr, which was acquired by Shopify for $2.1B in 2022, is setting out to change that with Augment.

In this episode, Harish shares:

• Why the flow of logistics information is broken and the real-world costs of its inefficiency, including missed appointments, wasted labor, and asset underutilization.
• How Augment aims to solve these problems with an AI teammate named Augie that can understand SOPs, manage workflows like tracking and document collection, and learn from context, freeing up human operators for judgment-based tasks.
• The critical importance of living out your company’s values and deeply understanding operator pain points in building scalable businesses.
• Insights on navigating the rapidly evolving AI landscape, balancing innovation with delivering tangible business value, and Harish's approach to fundraising for a capital-intensive AI venture.
• A five-year vision for Augment focused on significantly reducing waste in the $10+ trillion global logistics industry and enabling more efficient commerce.

Follow The Freight Pod and host Andrew Silver on LinkedIn.

*** This episode is brought to you by Rapido Solutions Group. I had the pleasure of working with Danny Frisco and Roberto Icaza at Coyote, as well as being a client of theirs more recently at MoLo. Their team does a great job supplying nearshore talent to brokers, carriers, and technology providers to handle any role necessary, be it customer or carrier support, back office, or tech services. Visit gorapido.com to learn more.

A special thanks to our additional sponsors:

• Cargado – Cargado is the first platform that connects logistics companies and trucking companies that move freight into and out of Mexico. Visit cargado.com to learn more.
• Greenscreens.ai – Greenscreens.ai is the AI-powered pricing and market intelligence tool transforming how freight brokers price freight. Visit greenscreens.ai/freightpod today!
• Metafora – Metafora is a technology consulting firm that has delivered value for over a decade to brokers, shippers, carriers, private equity firms, and freight tech companies. Check them out at metafora.net. ***

Chapters

• 0:00 Sponsor message and episode intro
• 2:12 “Logistics is broken”
• 10:54 How Augment's Augie is solving it
• 26:11 The idea for Augment
• 29:20 Key insights in customer research
• 32:26 Lessons from past experience
• 40:08 Building at the speed of AI and AI competitors
• 44:45 Approach to building Augment
• 55:12 Soliciting new business amid AI fatigue
• 1:00:48 Turnover and burnout in brokerages
• 1:08:15 Augment’s $25M raise and what’s next
• 1:15:27 What success looks like in 5 years
• 1:20:12 Founding advice and guiding principles

Transcript

Andrew Silver: 0:00

Hey FreightPod listeners. Before we get started today, let's do a quick shout out to our sponsor, rapido Solutions Group. Rapido connects logistics and supply chain organizations in North America with the best near shore talent to scale efficiently and deliver superior customer service. Rapido works with businesses from all sides of the logistics industry. This includes brokers, carriers and logistics software companies. Rapido builds out teams with roles across customer and carrier, sales and support, back office administration and technology services. The team at Rapido knows logistics and people. It's what sets them apart. Rapido is driven by an inside knowledge of how to recruit, hire and train within the industry and a passion to build better solutions for success. The team is led by CEO Danny Frisco and COO Roberto Lacazza, two guys I've worked with from my earliest days in the industry at Coyote. I have a long history with them and I trust them. I've even been a customer of theirs at Molo and let me tell you they made our business better. In the current market, where everyone's trying to do more with less and save money, solutions like Rapido are a great place to start To learn more. Check them out at gorapidocom. That's gorapidocom.

Andrew Silver: 1:32

Welcome back to another episode of Freepod. I'm your host, andrew Silver, joined today by a special guest. Per usual, always a special guest on the show. Mr Harish Abbott, did I get your name right? It's perfect, perfect. Welcome to the show, mr Harish Abbott. Did I get your?

Harish Abbott: 1:46

name right, it's perfect.

Andrew Silver: 1:47

Perfect. Welcome to the show, sir. How are you doing? I'm doing great. Thank you for having me. So I think you've got one of the most successful backgrounds of any of the guests. I've had Multiple companies founded and sold, and the most recent one for a big number. But you're back at it, back in the action, with your newest business Augment. As you say, the logistics industry. Logistics is broken, I think, is the tagline on your LinkedIn page. Let's start right there. How is logistics broken? Why is it broken? Let's start right there. How is logistics broken? Why is it broken? You seem like a seemingly lifelong logistics guy with your businesses.

Harish Abbott: 2:33

So I'd love to hear your perspective there. Yeah Well, first, I'm not sure about being the most successful, probably being the most lucky, I'll take that. Most lucky, I'll take that. Listen, logistics is, I mean, we all know it's the backbone of sort of everything. Right, like everything you touch, the coffee mug on your table 20 different companies, probably coordinated from Asia to Chicago for that coffee mug to be on your table, and it's complex, you know, it's ships, it's trucks, it's warehouses. But if you think about you know it's somewhat like these 20 companies, for them to get that coffee mug on your table have to trade information and trade goods. Right, whether it's the manufacturer or the distributor, or the freight forwarder, or the shipper or the port on this side, the crosstalk, or the trucking company, they all have to trade information. It's like, hey, here's a bill of lading, here's the container number, here's the trailer number on which this truck is, this thing is at, here's the you know bill of goods or things like that.

Harish Abbott: 3:52

And you know, the trading of information today happens through the lowest common denominator Like you've lived it right Like emails, phone calls, text, telegram, whatsapp, and it happens very asynchronously. So operators across these 20 companies are trading information asynchronously over emails and phone calls. All of those methods are low bandwidth methods. They don't contain a lot of they cannot. They're just designed to be small bits of information that can be traded. So first, it overwhelms the operators, right, like they have to deal with hundreds of emails. You know, the other day I was at one of the brokerages and I'm not kidding, the operator had 800 unread emails, right. So if you come in the morning and your inbox says 800 unread emails like that's not a good in the morning, and your inbox says 800 unread emails, like that's not a good sign, that's not an industry that is, like you know, not broken. But two, when you trade information with these, you know these methods of communication well. Invariably at somewhere, someplace, it becomes five o'clock for somebody, right.

Harish Abbott: 5:06

But the trucks don't stop. The warehouses are still taking appointments, but the information trade stops. Right, and that's the broken part about it, right. Which is a truck unused for a day or a night is probably 800 bucks. A warehouse missing an appointment and having labor there could be hundreds of dollars, right. A container sitting on a port for seven extra days because they couldn't get the paperwork on customs done, you know, could be thousands of dollars of capital cost, and so the underlying thing is not stopping. The perishability cost of these assets is so high.

Harish Abbott: 5:50

But the trading of information is what's broken. It's broken because we're using fairly asynchronous, cumbersome methods to trade information across these companies and so it overruns the operators. It creates waste in this industry, because when you stop trading information, waste happens. The container stays on the port for a few more days, you know the intermodal doesn't get picked up or it's dropped, but then it's never picked up the next time. The appointment is missed. That's what I mean by you know. It's such a crucial industry and the operators are the heroes here who are making this happen.

Harish Abbott: 6:30

In spite of all this, like, in spite of getting 800 emails a day, they're executing it. You know, literally I was at another brokerage and you know, know, this person shows up at 6 am and she drives for an hour to get there. So her day is starting at 5 am. At 6 am she starts her day and she's not leaving till like 5, 36 pm and then an hour back. So that's a 14, 15 hour days full of emails, phone calls, and it leaves her like very little room to do creative work, the work that was advertised when she got the job.

Harish Abbott: 7:08

She's not doing any of that. She's not calling on the shipper and saying, hey, let's look at this month's shipments. Can we read out them? Can we pre-schedule them? Can we do a multi-stop for you? Can we reduce your waste here? Can we do a multi-stop for you? Can we reduce your waste here? Can we make it more efficient for you?

Harish Abbott: 7:32

But it's just so busy that there's no time for the creative work. But the only time is for hey, is this information there? Oh, can I log it into my siloed system that nobody else sees than me? But I still have to log it. And then let me download something and send it to somebody else, and they're doing the same thing. They're logging it in their system that no one else sees, right. So that's what I mean by it. The brokenness is one of the largest industries in the world, like worldwide $10 trillion, in the US 3.2 trillion, like a tenth of our economy. That powers every single thing that we see and touch and feel is still today run on trading information in very, very archaic methods, in my view. You know so. Oh, it makes it perfect.

Andrew Silver: 8:25

So what I was going to say is anyone who has ever worked in a brokerage perfectly understands the problem you're describing. So we're talking about the day in the life of an operator, and different brokerages and different models have different titles for this function, but it could be logistics coordinator, could be operations wrap, operations coordinator, account manager. You know the roles, the functions that I'm specifically thinking about are people whose responsibility it is to take care of existing customers, take care of existing customers, and in doing so you have to build orders. Depending on if your customer is sending things over via EDI or if it's email, you're often having to manually build the orders. You have to schedule the orders pickups, delivery. You have to communicate whatever new POs are added to the orders, whether that's putting them in the system or notifying the carrier that's booked on the order. You have to communicate any updates, delays, and your day is, you know, coming into 800 unread emails is not a surprise to me at all. That is a common reality for the operator in this business, and the day is a constant. It's a never-ending game of catch-up and you never are really caught up.

Andrew Silver: 9:54

So the way you describe this problem is pretty astute, because, as someone who's operated a brokerage. You know that was the life of a lot of our employees and exactly what you said in that, the job someone thinks they're signing up for is never that. That's not what ends up coming to fruition, and it's not intentional necessarily, especially for growing companies. It's like you're constantly growing and throwing more people at the problem. At least historically, that's been the way we've always addressed it. That seems to be changing in today's environment with companies like yours. I have no choice, because I started with this question. I have no choice but to talk about Augment for a bit here. I was going to start in your background and then get there, but let's talk about Augment. So this is the you know, the business you're building today. Augment is intended to solve this exact problem, correct?

Harish Abbott: 10:52

Yeah, it's intended to. You know, I think we feel like to fix this industry. You have to make the lives of operators better. You have to get them back to what their advertised role was this creative problem solving. You're helping the shipper, you're building relationships, you're negotiating. You know things that were in the job board and we believe the way to do that is to take all this tedious mundane you know repetition out of their day. You know, and so, yeah, so that's what we're building. We're building these. You know AI teammates. Think of them as like a personal intern that everyone will have. You know they can interact with systems. They can call, they can email, they can text, so they have sort of the skills that you would expect from an entry-level employee to have. But they can follow these workflows and SOPs.

Harish Abbott: 11:52

You know this business, as you know, is a lot about SOPs. Like, hey, if I have my enterprise customer Pepsi, they want me to run my loads this way. That's a 30-page document and you don't want to miss that. And in status quo, you have like a team that like learns those 30-page document and then make sure that every load is sort of matching that SOP. You know these. We're calling it Augie, but people like Kristen in any way they want. There's lots of different names now, but Augie can like read these SOPs, can like follow these SOPs to a T, and so it takes away that tediousness. It's like am I, you know, am I making sure that when I'm asking for the truck it's below refrigerated minus 10, because that's what my customer, don Foods, wants? Okay, I can ensure that like, like Augies can do that.

Harish Abbott: 12:46

And then they're taking over, like some of the you know sort of basic workflows designed as, like you know, tracking loads, collecting all the documents. Like nobody likes collecting documents no, no one likes it and like documents that has lumpers, then detentions, then accessorials, some of those you find out a few days after the load is being delivered. And now you have to go back and now the you know the dispatcher on the other side is like what are you talking about? I've sort of moved on, you know, and no one's getting paid, commission's not getting paid, you know. And so like, okay, let's not have humans do that. Like we've come pretty far ahead, let's have you know systems collect these documents. They should be able to understand that, oh, this load requires excess oils, it has detention. Right Now, let me go collect those.

Harish Abbott: 13:41

And when I get the documents, can I like, match it up with, like, is it for the right load number and is it for, you know, does it sign or is it not signed? You know, like these were the things before, like we would get that we would forward it to an ARAP or a finance person. Then they get to it a week later and they're like, hey, this is the wrong document, I can't invoice. Then they pointed back to the rep. Now the rep sort of moved on. Oh my gosh, I need to deal with this load that was delivered 10 days ago, but if I don't deal with it, nobody gets paid, and so these things add up.

Harish Abbott: 14:14

All these are the word I was saying. In this world of AI, let's just make all of these things so that we can take on all this tedious work, so that the operators can now focus on things that we are. Take on all this tedious work so that the operators can now focus on things that we are uniquely positioned to do, like judgment, right, like, oh, here's an enterprise customer. You know we got these loads, but this load is going to run negative margin. But you know we've got to maintain this relationship. We have an rfp with them. Okay, I'm going to run a negative margin, like that's a decision. Yeah, I can't take that human can, because they have a puts and takes on the relationship, the rfp. How much negative margin? What's the pulse on the market?

Harish Abbott: 14:59

You know, or like relationships, you know some deep negotiations, or when things break down, like you know, a truck's on the way, you did a track and trace call and the guy said I broke down, I'm on the side of the road, I need help. Well, a bunch of people needs to now get coordinated, like the customer needs to know the warehouse needs to know an extenuating circumstance has happened. You need to now figure out what to do with this. Do I send a new truck? Do I have enough time? Well, that's the time you want the operator to spend on. That's the service level that we're delivering to the customer and the shipper. So Augment's vision is that, hey, it's all fixing logistics, all starting by really bringing the operator back to doing creative work, decision-making, this stuff, and then let's take all this tedious work away from them.

Andrew Silver: 15:52

So it's interesting because I see a clear. So the best way to say this, I guess, is relying on humans to recall all of the rules that exist for all of their customers while playing the game of catch up constantly. So you know, I think the big challenge for people is yeah, there's an order, so for one, I want to focus on revenue generating opportunities, and so I'm trying to spend my day on the phone with customers or carriers or whoever can help us get the next load and make the next dollar, and oftentimes these issues that come up are not issues that could certainly make you any more dollars. They're not getting you another load, they're almost. They're generally a distraction from the opportunity to do those things you want to do, which is a big reason why reps don't want to deal with them.

Andrew Silver: 16:50

You know, when you get that lump or receipt from a load four days ago and you know the carrier sends it to you finally, and now you have to deal with it.

Andrew Silver: 17:00

It's like I can either deal with it now or I can focus on what's making me money, and but by not dealing with it now, one I'm delaying our chance to get paid, I'm delaying the carrier's chance to get paid and most importantly, potentially is there may be a rule that says if lumpers aren't turned in within 48 hours, they don't get reimbursed.

Andrew Silver: 17:20

There are plenty of customers who have rules like that, whether it's for a lumper, for detention, a layover, whatever it may be, and over time that money adds up. Remember every rule for every customer and act accordingly to ensure every load is taken care of within those rules while dealing with the kind of nonstop firefight of their day-to-day job. And so there is a lot that's missed and it makes sense if you could be certain that the AI will. Essentially, if Augie can always like, it will never miss a rule If you've told it A plus B equals C, or like, if this, if AX, then do Y, and it just will always do those things. It does set up the business very nicely to have way less, I guess, leakage or just kind of fall out from people making mistakes.

Harish Abbott: 18:26

Yeah, that's right. And the other piece here, andrew, is that you know it's sort of counterintuitive or maybe not, but you know when you ask somebody for something and it's on top of their inbox, they respond fast, right, like something happened, and like, hey, andrew, you have this info like right there. Forward it right Now if I ask you that 10 days later it's going to take you longer to find that right. So you slow down in responding. You're like okay, I got this email. Oh, I know, this happened 10 days. I have to go search, search, find it. There'll be four emails. I have to look at those four which ones it is. Maybe I'll get to it. End of the day. Sometimes you forget. So now it's 11th day, maybe you forget. I'll struggle. Now, five days later, I send you an email I'm saying, hey guys, it's 15 days, I need that information.

Harish Abbott: 19:21

So the longer you wait, the longer it takes you know and it's a human syndrome and so where these AIs are good at like, they're setting alarms for themselves at a load level. Like Augie is setting an alarm saying, okay, this load got delivered, you know, maybe I text the driver if that's what the workflow says. Within 10 minutes the driver doesn't respond. I need to email the dispatcher in like an hour. And it's not missing that it's doing it at a load level and so that makes it actually do these things faster too. On the other side, they actually like it because it's timely, and so we as humans, let's say, if a rep is running, let's call it actively 100 loads right now that are active like somewhere in motion. That's like in your mind, you're setting 100 alarms and there are 10 things that happen on the load and there's an alarm that needs to extend for those 10. That's like a thousand things that they have to keep track of. I mean, that's impossible, like expecting a human to have a thousand things time-wise, at an hourly basis, to keep track of, right? Well, this is the thing these ais are amazing at, so let's use them for that, and then let's use them for that. And then let's use us for what we are great at, which is judgment Right?

Harish Abbott: 20:48

Nobody like AI doesn't have judgment. We have judgment. We can do puts and takes on an uncertain outcome and incomplete information. We can come out of a decision that aligns with my company's goals or values or objectives Right, but if we don't give humans the time to do that, then they're spending all their time chasing these alarms and they have very little time to exercise their judgment.

Harish Abbott: 21:12

You know, and so that's what our hope is that we can make this happen. And if we start with that, then I think we can uncover, like the second aspect of it, which is the waste, that, okay, if you get your operators doing great things, creative work now across these 20 companies that collaborated to get your coffee mug where it is at, we can now maybe reduce the waste between them. Now we can do more smarter things across these companies. You know, and so that's sort of our, I would say, objective number two in logistics is that, one, make the lives of operators great, but two, let's reduce the waste here, and if you reduce the waste, we make logistics sort of better. There will be more of it. It's just the nature, you know when you make something better, there's more of that.

Andrew Silver: 21:58

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Andrew Silver: 22:57

So a couple of simple questions. I guess One is it possible for Augie or the AI to miss an alarm? Just to stay with that analogy, if you give it a rule or give it an SOP, such as if a load is booked with a carrier Augie must call the driver one hour before the pickup appointment if there is no update in the load. If you give it that clear rule, can it ever miss it?

Harish Abbott: 23:35

I mean, you never say never, but very rare, very rare. Like you're looking at you know, maybe less than than you know, half a percent or less than even that, like 0.1. We haven't seen that. But systems can go wrong. Uh, you have to, obviously. You know um and and so but. But even if it misses, it's going to be better than humans for sure.

Andrew Silver: 24:01

I just am curious to understand it. So that's why I'm asking that question. It's not meant to be critical of it, it's more just to like understand. I'm pretty sure I understand the answer is if it has a rule and you know the situation is within that rule, it will execute the rule Like it's as trustworthy as you are going to get with that I think where it's not great at Andrew today is that you know, let's say you do.

Harish Abbott: 24:31

It's an hour before you make the check-in call and the person said hey, I don't know like I'm ready, but I'm not in the truck, and you know I'm waiting for something, but I think I have it. I have to check in my email. So this is sort of complex call. It's not very clear. Like check, check, check, check, check, equipment check. It's like there's some grays there, right. And now we can set a rule in the workflow to say like hey, if there are some grades, like if the equipment is not matching or if, I don't know, the reefer isn't cooled enough, whatever the rule is, then either escalate to your rep or at least inform the rep. Or you could say like maybe call back and say like hey, we need these things to be done. We need to call back Now.

Harish Abbott: 25:27

Interpretation of that, because a call can be quite complex or an email chain can be complex. You have to interpret like hey, is it really matching every single thing that the SOP said or not? There I would say it's like today, at least for us it's like 97, 96% us, it's like 97, 96 percent. So there are three to four percent of the cases where the adherence on those is not hundred but something as binary as I can't call within an hour that it does very well and there's lots of software work that's going on now that like improves that adherence from 96, 97 to 99, a little bit higher, yeah.

Andrew Silver: 26:11

So when did this problem and the solution you're developing, when did that first come to mind for you? How long ago did you start thinking about this?

Harish Abbott: 26:23

Well, I've been thinking about the problem. At Deliver, we were a consumer of freight. We also had built our little own freight brokerage. Because we were consuming so much freight, it made sense for us to build our own a little bit. Deliver was a very tech-centric company. We were mostly engineers and we had consuming freight and this, and every time we sort of grew freight.

Harish Abbott: 26:56

You know, it just occurred to me like we're just not creating, you know, leverage here, like there should be leverage, you know, in a good business, which is you're doing more with the same number of people or you're doing better service with same number of people. And that's where I started to learn about sort of the freight word. And you know I chalked it up to saying like hey, this is a fragmented space, the softwares are also quite. There's so many different type of tms's, for instance, and at that point there wasn't a way. But I think as ai came in, you know, literally two and a half years ago, um, about summer of last year, I started to like think about prototyping and saying, huh, for the first time we can meet people where they're at If they want to do Telegram. Ai can do that, it can understand the message. It doesn't need an API. It can turn an email almost into structured sources really, really well. Or it can turn a phone call into a structured, almost API-like response quite well, way better.

Harish Abbott: 28:06

So that was like the sort of moment for me to say like, ah, maybe this is the time where we can meet the industry, where they're at right. We're not changing, we're not asking the industry to say, like stop using email or go into this one centralized system and everything will be magical. We're saying you can do the business that way. We're just giving you an AI employee, an AI teammate that can do exactly the things that you're doing exactly on the same system. There is no system to learn and how. Maybe that is a breakthrough. And so I think it was summer of last year and then we started building a bunch of prototypes. We shadowed a lot of operators, like I think, like 60 operators. We shadowed, like literally every day We'll just sit behind them and we see what they do, because there's no better learning. You know and and this I think learned very, learned, very quickly that, yeah, there is something here, like when we shadow these off, like we can build something that can help these operators become like you know, give them more superpowers, right so?

Andrew Silver: 29:20

yeah, were there any kind of unique takeaways or surprise? I know you said you had a little bit of a freight brokerage at Deliver but I know that wasn't the focal point of your time. I'm just curious as you prepared to kind of dive headfirst into freight brokerage and you spent all that time shadowing operators, were you surprised by anything or any kind of interesting takeaways from that time? That kind of were lightbulb moments for you as you got going here A lot of redundant communication.

Harish Abbott: 29:50

Like you know, in brokerages you do these customer email groups and everybody who is either a rep or a demand rep or an ops rep is part of that customer email group. And so there were 50 emails. Those 50 are going to everybody's inbox and everybody's looking at those 50, even if they don't have to take action or it's not even supposed to inform them. And just the amount of information overload that comes with that and I know why. Sort of it landed where it landed, which was like you know, people leave their vacation but loads are running 24 seven. How do you keep everybody informed? I sort of it landed where it landed, which was like you know, people leave their vacation but loads are running 24 seven. How do you keep everybody informed? But man, the amount of overload based on that was just mind boggling. You know like we literally analyze so many inboxes of people to say, like out of that, like which emails could I delete? And nothing in your day to day will change. And it was a big percentage.

Andrew Silver: 30:47

It's like, depending on the person, it could be over 90%. I mean it's a crazy number. It's such a good. I'm glad I asked that question because your answer is so perfect. I mean, the amount of email communication that is wasteful in brokerage is it's disastrous? I mean it is. I think about my own inbox and I may be a part of the problem as an ADHD guy who just was generally disorganized but, having spent a lot of time customer facing and selling, I brought in customers. I would be on the initial email chain and then three years later I'm getting emails about lumpers on an account as the CEO of the business and it just gets put into a folder that never really gets opened. But each of those folders has 4,000 unread emails in it. It can easily get out of hand it can get out of hand.

Harish Abbott: 31:41

And I think one of the problems there, in my view, is that you know it's sort of, you know it's hard to distinguish signal from the noise and because among those emails there are 10 that you really need to action, but you have to go through the 50 to find the 10. Now you've made very hard for the person to find those 10. And it's very easy to miss those 10 because you're so busy. So I think this whole signal to noise ratio is not great and we're working on that problem and we hope we will have a good solution there.

Andrew Silver: 32:25

Yeah, so I'm curious as you got started here in the last year, what kind of things did you pull from your experience? I mean, you had this incredible success with Deliver and a couple other businesses you had started. I'm just curious if there are any really important things that you as a CEO, as a leader, thought to yourself like I need to make this a cornerstone, as a leader, thought to yourself like I need to make this a cornerstone, like I learned from my experience and this needs to be a crucial part of how we build augment.

Harish Abbott: 32:58

Yeah, man, there's so many. But let's see, I think culture is, you know, it's one of those things like trust, like it takes a long time to build but you can lose it instantly, and culture is similar. Like you need to build very resilient cultures means you have to work every day at it. And it's not just about like hey, you write five pretty values on your powerpoint decks or you know, on your, as a mural on your on your office, and and like have employees on the first day like read it or or read a document about it. But it's like how you make decisions every day, right, how you show up, how do you make tough decisions? Are those all aligned with the values? And being extremely intentional, that when they're aligned, to point it, why we made a decision that was aligned with that value.

Harish Abbott: 33:58

You know, like if you say putting customers first, which is one of our values, that's an important value, but you're short-circuiting some customers or telling them something that's not true, well, employees are going to see that very quickly. It's like, no, that's not your value. Like you're saying it it's your value, but you're not. But you have to like, live it. You know, you have to live it every single day. And I think if you do that, then your next 50 employees, your next 100 employees, they become the, I guess, the bearers of your culture for the next 500. And so it's extremely important that you know you get that foundation right, you know, and so, like I think, when I started Augment, like the first two, three days, we just wrote values. There was no code written, you know, we were just shadowing people and we just wrote a set of values. We socialized among ourselves, we debated every single word of it and we said, okay, what are the mechanisms we're going to use to uphold these? How are we going to incorporate that in our hiring processes? How are we going to incorporate that in letting people go, people who are not a fit, and let's just talk about that. Let's just put all of that in a paper so that when we have a disagreement, we can now go back to this and saying, hey, this is what we agreed on. Right, we agreed that we're going to be honest and direct and that's one of our values. And like that means disagree and commit or that means we're separating ideas from people, and like that, like, if there's, let's just go back to that and, like you know, become sort of like our constitution, if you will, that when things can't agree, like hey, this is what our in in america, our founding fathers sort of agreed on, how, when we were building the, the country, I think almost treating it at the same level of reverence, I would say, is one thing that I'm sort of carrying forward Because it pays in dividends.

Harish Abbott: 36:02

You know, once you do that, your hundred, your next few hundred. Now a decision could be made in an office, whether you are there or not, you're maybe several layers removed. It's going to be made in accordance to the values and if you can do that then you're really building a scalable business. But if you have to be in that room to make sure the decision is made well or not made well, then it becomes very hard to build a scalable business. You know, becomes very hard to build a scalable business. You know.

Harish Abbott: 36:31

I think that sort of I would say you know, listen, like focus and customer delight, like all softwares when you start is you know it has edges, it's not perfect, it takes a while to build great, great software. You know, and I think one thing we probably didn't do as well early on in deliverable, but we fixed it I think we're doing a better job here is really supplementing that with customer success teams. So, very early on, you know when people are implementing Augie. You know we have ex brokers in our team who sort of felt the pain, who had those 800 emails, who are then going and implementing Augie. We have ex-brokers in our team who sort of felt the pain, who had those 800 emails, who are then going and implementing Augie and they're like OK, well, and even if the software is not doing like 10 out of 10 things, the 2 out of 10 things it's not doing, or 1 out of 10 things it's not doing, they're able to either tease out the solution for them or bring it back in the real terms, back to the product and engineering team, like, hey, we guys really need to build it. We face it. Our customers are facing it. We're just having that eyes and ears of the customer deeply penetrated in the company.

Harish Abbott: 37:41

Is is probably you know, but but then? But then there's something different, andrew. Like AI is moving faster than anything I've seen so far. You know it's making much easier to write software. You have to write software in a different way though, you don't, you know. So, like all that stuff I had to let go. You know, I had to rethink.

Harish Abbott: 38:06

Like you know, like in a traditional software, you think about unit test cases and you say like, oh, I'm gonna enumerate, I'm gonna write these unit test cases, and then I can just deploy it. You think about unit test cases and you say like, oh, I'm going to enumerate and I'm going to write these unit test cases, and then I can just deploy it and you put those test cases in your CI CD like deployment pipelines. But in the AI world the enumeration is many. Like when the AI talks to somebody or sends an email, the number of cases are infinite on how you will get back the responses, how does it need to respond back.

Harish Abbott: 38:34

And then now you have guardrails. It's like, okay, I want you to achieve this objective, but here's the guardrails for it Don't ever do this, don't ever do this. So the software you're writing is very different because the number of cases it is addressing is certainly a whole lot more. Addressing is certainly a whole lot more, you know. So also had to change and also had to move fast. Because you know, like we it's it's moving so fast that we've gone from zero to like 75 people in a short amount of time and because it's just so much to build so quickly, you know so.

Andrew Silver: 39:09

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And now there's Illuminate, greenscreens' latest product, designed to shine a light on deeper freight market insights. Illuminate provides unparalleled visibility into spot and contract freight trends, giving users a clearer view of pricing fluctuations and market conditions to inform smarter, more profitable decisions. Visit greenscreensai, slash thefreightpod and discover how Greenscreens and Illuminate can help win more business more profitably. I'm curious about the element of change with respect to how technology is built and how AI is built, and or how the technology using AI is built, and I guess, is that concerning at all to you? Or like how do you think about the way to? How do you think about positioning Augment to be like the leader sustainable product, knowing that every three, six months, there's something new and maybe better than what I'm currently scaled and building with?

Harish Abbott: 41:00

Yeah, that's a really good point. So you know, like, if you think about, in that scenario, you know you have you can. Either you have two choices you can lean in or you can wait because the problem is going to get solved, right. So you can say like, oh, I'm going to wait for that next breakthrough, or I will lean in here, but I will adapt. You know, obviously we believe in the latter, which is like, if you lean in here, but I will adapt, Obviously we believe in the latter, which is like, if you lean in here, you learn enough about the space, you learn enough about the quirks, you learn enough about the users that your adaptation would be better than somebody who's coming in six months later with that new tech, for instance, or a new version of OpenAI or ChatGPT or Cloud or underlying LLMs, because, fundamentally, all of us are using one of those, and that's what's changing so fast.

Harish Abbott: 42:06

I think the second piece is. What is not changing, though, andrew, is that, like, like AI is still a tool, right. Like ultimately, you have to either deliver something better, cheaper or faster, like it does not matter, like whether it's AI or not, and so you have to deliver productivity or revenue gain to the business, right, and that's not changing, right. And so staying focused on that, deeply focused on hey, what is the business value? With a viewpoint that this underlying LLM is going to improve radically. So you're also starting to take bets and saying I think the LLMs will be here six months a year from now. I have to start thinking about those use cases today will be here six months a year from now. I have to start thinking about those use cases today, all in line with, like this business use case of like I'm building something better, cheaper or faster. It has to be that you know. And so I think, like your question was like how do you do that? I think you lean in, we do test. Almost We've built a framework where, when new LLMs come, we rapidly test against those and see, in terms of those three dimensions, better, faster, cheaper. Are we improving? If it's not improving on that, we don't actually care. We don't care about the benchmark. It hit on a math test Like, oh, it improved the benchmark on this new math test from 93 to 97. We'll try it and we'll run, you know, thousands of simulations against this new llm and saying, did it make things better, faster or cheaper? If the answer is no, we'll stick with what we have. If the answer is yes, we'll switch.

Harish Abbott: 43:46

But then you have to build. You know infrastructure and technology that can easily switch those things. We can run real life scenarios very fast so we can know like nothing Augie's in the world today that is handling tens of thousands of loads. They're not going to get disrupted when I change this underlying engine that powers their intelligence or their actions. So we had to build a lot of software that can do that and that's a new requirement in the Lord. That, like we didn't, I didn't have to worry about it in Deliver or in my previous businesses. But now you have to. You have to, you know, design your things from day one, assuming that one. You're going to try multiple LLMs and you have to try them differently every three months or six months. You know.

Andrew Silver: 44:31

Yeah, that makes sense and it's interesting you mentioned because everyone's using similar or the same underlying LLMs or technology to build on and I think to kind of broaden that.

Andrew Silver: 44:44

This space has gotten very competitive very quickly and there are every week there's another announcement of a company, either started by some young kid out of silicon valley who is just eager to make his name, or it's someone like yourself, an established, successful previous founder, who sees an opportunity and wants to participate.

Andrew Silver: 45:13

I don't know what the number is, whether there are 30 or 40 or 50 different AI companies coming in to automate work in freight and make brokers more efficient. It seems like everyone has somewhat of a different approach. Some companies are just focused on appointments to start, some are just focused on appointments to start, some are just focused on APAR, some are just focused on phone calls to carriers for tracking, and then some companies are kind of bootstrapping early with small teams, small raises. Others are going big and raising a bunch of money, getting a large team set up and trying to attack several things at once. How do you think about what has been your approach specifically? Obviously, you guys just raised a bunch of money, so definitely not bootstrapping over here, but I'm curious how you have thought about entering into the space if you're approaching one problem at a time or all of them together, and kind of why you're choosing the path you're choosing.

Harish Abbott: 46:17

Yeah. So we're taking sort of a more horizontal, broader approach, right? So we're saying, hey, there are maybe 30 to 40 different workflows, traditionally multiplied that by customer SOPs or configurations. So now I'm dealing with hundreds of different workflows in a business and ultimately Augie needs to handle a good chunk of them. And our reason is that every subsequent email, phone call text or a system login gets smarter when Augie has context over the load, right, like in you ran brokerages, why did you like? There's a reason probably why you said like, hey, you own, you know, this customer for me, right end to end. And I'm assuming the reason was you have the full context, so when the next situation happens you can handle it.

Andrew Silver: 47:20

Yeah, certainly that, and accountability.

Harish Abbott: 47:22

And accountability.

Harish Abbott: 47:24

Yeah, exactly, so our approach is that it's no different, for we're approaching almost Augie to be a teammate and and be accountable, but we think it can only be when it sees hey, it was built, the load was built. This was the customer SOP. It required the following things for the equipment. It required the following things for Lumpur we understand that while building the load Okay. Rescheduling the load based on the requirements oh, okay, we can now help them track and trace load or assign it to a carrier. Or when I'm collecting documents, all of those things are helpful, like if I'm just chasing documents without knowing like, hey, these guys require this customer requires everything to be submitted within 24 hours. Well, I'm going to run at a different pace for that customer because otherwise I'm not getting it. But it helps to have the entirety of the context of the business, the object, whether it's the load or the customer in your case and so our approach is that that makes for a better experience of Augie completing the task. So that's been our thing, and and and, like the other piece, which I'm quite different than the rest of the world and the market here is that you know, a lot of people think about like hey, email automation or phone call automation is like this superpower, right? And I think they're missing the point, which is it's not about phone automation, it's about getting work done. Right, like the best phone call is the call never made. It's a defect that we have to call somebody. It's not a feature, it's a defect that we have to call somebody. It's not a feature, right, like, if you could get the work done without calling anybody, would you prefer that than to actually have more calls, like everybody would prefer. Like, oh, we just want to get the work done without call. You can't do that unless you have an understanding of the load, unless you have the understanding of the customer, right, you can't do that.

Harish Abbott: 49:33

So we think if you start to like do point solutions, saying, oh, just automate my calls, you may be solving the wrong problem. You're reducing defects but you're not reducing. You're like you're handling defects but you're not reducing. You're like you're handling defects but you're not reducing them. You know like the industry would be better off if this were to happen without so many emails and so many calls, right? And so that's maybe quite a bit of a different approach that we take.

Harish Abbott: 50:07

We say like, hey, our job is to get this, you know, load tracked to the specifications of your customer as specified in their 30 page SOP. Ok, what's the best way to do that? You know, maybe it's not to pound the driver every four hours, like where you're at. Maybe it's to better at, like you know, seeing where the ELDs are and why are we not getting that? You know, um and so. So that's one area where I think I I differ quite a bit from some of the noise in this industry, which is like people are just so excited about calls or emails, or, you know, I'm like, no, that's not the problem so it's interesting because, as I've kind of learned about this part of the space and I'm definitely I appreciate that explanation.

Andrew Silver: 50:58

I think that really is helpful for understanding how you think about the problem and, specifically, how you think about the solution. I've heard challenges with let's focus on appointments for a second um, one of the big appointment scheduling companies that has gotten a lot of attention. Um, I've heard challenges from from their customers who've said you know, it's designed to automate the appointment process but when something goes wrong and it breaks for whatever reason, there's an exception which happens with. Whether it's appointments or aparAR or tracking, there are always exceptions. That's the name of the game in this business. But what I've heard is this is a company that has a relatively small team and what it does is essentially just breaks. It kicks it back to the employee at the company and they have to then jump in and deal with it, which and companies like this are touting we've reduced 70% of the need for your employees to be involved in appointments. Okay, that's good, you're solving part of the defect problem there. However, it's not necessarily a fully baked solution or an end-to-end solution if every time there's an exception, it kicks it back to my team to have to deal with it.

Andrew Silver: 52:20

Now, on the other end of the spectrum, some solutions I've heard are kind of like AI-enabled BPO, where you're going to outsource the entire job to us and we will leverage AI to do as much of it as we can, and that which the AI can't do, we have a person who's going to do the job itself. Yeah, it sounds like your business is kind of in the middle there, in that you want Augie. You know, if my operations team has five people with Augie essentially now has six and Augie can do a lot of work and you know, when something breaks, the team sees it because they're working with Augie and they jump in. Am I describing right how you are, or do you feel like you're more on that AI-enabled BPO? End of the spectrum.

Harish Abbott: 53:10

No, we are not sort of a BPO. I think our approach is that when there is an exception, augie has the tools to do a set of emails and phone calls and others that are needed to resolve it. It's going to try that. So let's say the appointment wasn't booked because the windows were too short and there is nothing available on the on the pickup facility to meet those windows. Now we've got a new set of windows, but this is sort of a hard requirement.

Harish Abbott: 53:44

Now it requires a quick message to either the customer or the customer rep and saying, hey, I'm not getting an appointment. This is the next best we can do. What do you want to do? Now? That's a message, right? Augie can take that and say, okay, let me run that message internally or externally, get the response, then maybe pass it to either the scheduling system or its own scheduling system and saying, oh, let me see if I can get that so it can at least handle a higher percentage of these exceptions. And only after it has failed on some of those it will then say, okay, I need to know and I need to know Escalate.

Harish Abbott: 54:27

Think of it as a junior level employee who've tried my best based on what I was given as an SOP. Now I need to report to my manager that, hey, I've tried these things and I'm at a standstill. You need to get involved. And so we hope to reduce those exception handlings to a much smaller percentage, because it has these communication tools, both internal and external, right. It sits on Slack or Teams in your employee stack. It's not an app, it's on your employee stack. It sits there and it has access to your customer groups and it will message them and they'll respond back and then it can take that message and say, ok, I know what to do next. You know, almost very similar to what a remote employee would do, you know.

Andrew Silver: 55:13

And what's been the initial feedback in terms of well, I'm curious both about soliciting new business and existing. Let's start with soliciting new business. What I'm curious about is do we have AI fatigue yet? Like, are there as you reach out to brokers saying, hey, you know I'm Harish. Or your team says, hey, we want to show you Augment? Are there people who are like I've had seven demos for AI companies in the last few weeks. I just can't do any more. I've already got three demos ongoing. Are we there yet?

Harish Abbott: 55:46

I think we're very close. I think we're very close. There is just a lot. There's a lot, yeah, and like we were having a prospect call this week and we finished it and that's what the person said like guys, just fii, this is my fifth demo of this week, you know. So, uh, it's very easy to build solutions in the ai, like not only like how ai is helping you know logistics, like it's helping engineers to build things very fast, right, so, um, so there's lots of companies in this space and um, and you know, I can, like I would sympathize with the decision makers on the other side, like like, how do you separate? You know, what do you really need? Um, so, yeah, I think they're there. They're almost there in my view and for you.

Andrew Silver: 56:32

How are you navigating that kind of fatigue to stand out like? How do you take that situation where someone tells you this is the fifth one I've had this week and turn that into at least a trial?

Harish Abbott: 56:45

Yeah, well, I think a couple of things. I think one is, you know, fortunately so far I think we are one of the few, or maybe the only one, like who's sort of looking at a very holistic order-to-cash system versus a point solution, and so I think that message and value prop is connecting that if they do that over time they can think about an order-to-cash transformation here for the business. They can think about, you know, in order to cash transformation here for the business. But two is we're sort of saying, hey, like to see how, like Augie can internally communicate, externally communicate, let's get started with a couple of simple workflows without you having to spend a lot of time into integrations, you know. So it could be like, hey, give us some flat files and we'll spin it up and you get to see it in action, hopefully in days, because, as you know, the TMSs are not fully well designed for, they're not the most friendly in terms of integration. The APIs are not the cleanest, I would say For sure, and some are good, some are not For sure, you know, and some are good, some are not.

Harish Abbott: 58:05

So and so and and and, like freight's been in a tough, in a tough space in the last three years, like it's been really tough market for freight and you know every, every business is, you know, feeling it in some way or the other Right and so for them, any initiative, as promising as it is, it's a new investment. They have to put people in it to make it successful, they have to put engineering behind it, and so that's like the biggest hurdle, where they see the promise and like, okay, I see the promise, but how do I justify putting a few engineering resources or a third-party engineering firm or even our own business time to see this through, like if it's all just you know, shiny tech which has been pitched to freight along a lot of times, you know it's not like, you know they'd like and like, why is this not one of those you know? And so we get to say like, okay, maybe we can do like a simple flat file. You get to see it, you get to feel it, you know, and I think those between those two things. But you know, so far, like you know, we're fortunate, we have some very large businesses that have trusted us early on and opened their doors and almost co-building, and so taking some of those case studies has helped a lot where you're showing real, meaningful productivity improvements.

Harish Abbott: 59:29

Operator happiness and operator happiness as you know, like just the recruiting and training costs in this industry is very high. If your operators are burning out Like, that itself is a very massive boost. You know if your operators are happy they're producing more revenue, but they're also quitting less. You have to train less people. Your classes are shorter, smaller, and so you know taking those metrics have been helpful.

Andrew Silver: 59:54

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Andrew Silver: 1:00:47

Yeah, so turnover and tribal knowledge are two significant issues in brokerage and they're way bigger when you pair them together, because having accounts that are run on tribal knowledge by people who've done it for a long time, it goes well until you have the turnover and sometimes it's employees quitting and so that account loses its rep.

Andrew Silver: 1:01:13

Sometimes it's something bigger than that and it's a company org change and all of a sudden you've got 50, 100 accounts that are changing hands and all the tribal knowledge can be lost, or the game of telephone by which everyone plays to disseminate information, doesn't go well. I think one of the biggest concerns I've heard shippers have one of the things that they start to look at over time within a business or a provider of theirs is how often the team is changing, because it's almost a guarantee when you make a change on the account and at least one person changes, there's almost guaranteed to be a problem, and it could be a small one, but at least one load will be messed up because one bit of information was not effectively passed from person A to person B. So I do see how the right AI technology it's Augie, or hopefully it's Augie can help both of those problems.

Harish Abbott: 1:02:13

Yeah, yeah, yeah, I think that you've sort of summarized it better than I have. Like you know, we're really like when we like all given it sees travel knowledge, it tries to retain it. Now, you know, when it sees like a dispatcher phone number that's not in the tms, it will grab it, it will persist it, um, or the dispatcher says I'm no longer the guy, like you've got to contact this person now. Like it just won't be, like oh, I'm going to call this person, move on, it would actually oh, I've got a new number, new contact, I'm going to save it. You know, just, the directory information is so dynamic and it's moving, but if you look at the tms itself, it doesn't represent the dynamism of what's happening in the real world. Like people move their, their numbers change, their emails change, their roles change, but TMS is relatively static because it's like burdensome to go and find something in an email and then replace it. You know, these are the areas where Augie is good at like it's gonna, it's gonna get that info and it's going to update your TMS. So you always have like the most recent. You know update.

Harish Abbott: 1:03:16

But yeah, turnover, and I mean I went deep into understanding like the P&Ls of different size brokerages and just the cost of training and turnover really surprised me. If you ask me for the surprise, that was the second part, I did not imagine to be. Just the cohorts when you know, really surprised me. Like, if you ask me for the surprise, like that was the second part, I did not imagine to be, you know, just the cohorts when you hire, especially on the sales side, and then those cohorts, how many you know, stay with you within 60 days, 90 days, 180 days. Just the amount of money you spend for 180 days to get them trained before they actually start producing for you and then you know, it's like it's just, it was a much higher number than I had envisioned before.

Andrew Silver: 1:04:03

So you make a great point and what that has me wondering is how do you take that insight and apply it to a revenue model? Because what essentially you're getting at is the solution you're creating. It has this kind of immediate impact in solving the physical problem that you assign it, which is to okay. You've now made the operator's job less monotonous. You've made the operator's job less time consuming, demanding, so it doesn't have to be 15 hour days, which means you've reduced turnover. You've reduced the amount of training that has to be done. So you see, like once you zoom out a little bit, you're saving a company a lot more money than just the dollars it takes to schedule an appointment. And I'm just curious how to think about that from the revenue side when you have these kind of second, third tier efficiencies you're creating for the business.

Harish Abbott: 1:05:17

Yeah, short answer is today we are not. Today we are really thinking of like amount of work Augie does and ensuring that the businesses get, like you know, 7x ROI on that. Basically, you know, I treat that as more like you know, if you're producing the second third order effects, which I believe would be pretty meaningful, they might take 12 months to fully pan out. My thinking is that that should hopefully make Augie very sticky and the most tenured employee in the company. That's enough payback. If Augie remains the most tenured employee in the company, that's enough payback. If Augie remains the most tenured employee in the company, that's a good payback.

Andrew Silver: 1:06:02

Yeah, it maybe is just most helpful on the front end in how you solicit and communicate the opportunity, because two years from now, for example, I think you could go through. I know Arrive is a public design partner of yours. Yeah, I bet, if all goes to plan and you build this thing the way you want to, in two years I bet you could look at Arrive's business and, outside of the very specific things that Augie worked on, you could zoom out and see some of the effects to turnover and cost of training going down. And then maybe you're just selling that on the front end to other providers, like hey for other providers, like hey for other companies. We've reduced turnover by. We've seen turnover reduced by 20% in the first 24 months that Augie was implemented and it helps you because I'm just I don't like you, I don't know that.

Harish Abbott: 1:06:52

I see a way to actually charge for that, but yeah, I hate charging for things that are just so first, far out in future, but to you yourself don't know, you know, you don't know the total impact of it. Right, like you know, great businesses get built when they leave a lot of money on the table.

Andrew Silver: 1:07:14

It's a good point. It's an interesting comment.

Harish Abbott: 1:07:17

Yeah, if you look at some of the biggest businesses, I don't know like Netflix, it's a great business. The value that the Netflix offers to a person who is a big consumer of movies is certainly way more than I don't know $12 or $20 a month that they're charging you. You know way more right the value, but they're just they're not going to. I think. Or, like you know, google has a great business where you know you're getting so much information from them, or chat GPT today, like at $20 a month and it's making your life like 20 more productive and like that's a lot of value it creates. You know they don't want to capture most of it, um, but it it sort of, I think, pans out in retention like yeah the stickiness is what matters, right?

Andrew Silver: 1:08:13

yeah? Yeah so you did raise, I think, 25 million bucks or more, 25. Yeah, yeah, 25. I'm just curious again. This is more me thinking about the general approach and how everyone's kind of had this different entry point to this industry. I get why, with a more holistic approach, a horizontal that you know, you probably do need to go bigger. But how are you thinking about why did you pick 25 million, why did you pick 8VC, and how did you get to that number and how's it gonna be deployed? Yeah, Okay.

Harish Abbott: 1:08:53

So I think 8VC I work with 8VC folks for Deliver and so it was sort of an easier. We both know each other's styles on how we build businesses. They've been a big supporter at the Deliver journey from very early on. Their philosophy is very founder-centric, which appeals to me. So that was sort of an easier decision in at least early phases of building Augment and they were interested in this space, the amount I think you know in early days. It's like we know there's a like there's a potential to build a large business.

Harish Abbott: 1:09:46

You know we're starting off with freight, which is a big industry, but the long-term goal for Augment is beyond freight too. We're, you know, we're building for the logistics world, like warehousing and so on and so forth, like warehousing and so on and so forth, and so we knew that we needed a broader footprint for some of the very complex communication problems. So I'll give you an instance where, let's say, when you run a business, or even in your media business, you probably get 20 pings a day. Now, a week later, later somebody else will ping you on same thing, and now you're able to connect those contexts in your mind. Right, okay, this happened, this happened, this happened, and then you're able to respond with those contexts that are being connected. You know, um, it's uniquely human. We never stop to think about it. But that's so cool that we can, like, have hundreds of contexts going and a month later, sometimes a year later, a friend of yours might ask you about something and you're like, oh exactly, yeah, this is what I did, you know, and just respond and just instantly connect. And Augie needs to do the same. There is no difference, right? If Augie needs to be a useful teammate to somebody in a brokerage that has 2,000 people, there is at least 2,000 contacts going maybe more, right? And it has to keep track of every single context over time, so that two months from now, if somebody asks Augie about something which started two months ago, it could respond just like a human would.

Harish Abbott: 1:11:25

So we knew like these problems are very complex problems. They take a lot of engineering work to like actually architect, think and write and then solve for it, right, and so for that we required, you know, a reasonable amount of money to get started to build sort of a broader team, you know. So now we have, like, and the use of the money is engineering, it is like we have 75 people. Of that, I think close to 60 are engineers, and so it is purely, you know, building very talented mission-driven engineering teams. But yeah, I mean exactly, it was 30, 45.

Harish Abbott: 1:12:06

I mean, I think it's sort of this dance between you want to raise enough but like, give as little dilution as possible, and you know, you trade it with your VC or your partner to say like okay, we're building for a bigger mission, we're solving some very complex engineering problems. It's going to take some significant investment to solve these problems. Well, okay, but we also don't want to be diluting ourselves before too much right now, because we know we can start to show revenue traction, customer traction fairly shortly. And so it's a judgment call Andrew, at some point You've got to make one. But I knew that a $7, $10 million round at this stage for what we want to do just wouldn't even get us far enough to show the proof points.

Andrew Silver: 1:13:01

And so what's your timeline in your head that you think? What's the next milestone for you in terms of how you think about the business growth and the deployment of these funds and how long they should last you versus another raise? How are you thinking about the next few years?

Harish Abbott: 1:13:19

I always think about. I like run for my business, like to at least have 18 to 24 months of runway. You know that's sort of a mental model in my that I carry forward, um, and so at every point I'm sort of evaluating that and saying, okay, do I have that? If not, maybe we need to raise or we need to cut the burn or we do increase revenue, whatever we need to do. So we have enough time because markets can change. But the big milestones for us is it's basically very simple, early, early stages.

Harish Abbott: 1:13:58

It's about delivering customer delight, which in our case is actually very straightforward, which is tremendous ROI and our ROI, fortunately in this business, is highly measurable your operator happiness. Do you need too many offshore or not that many offshore people? Are you running more loads with the same number of people? They're very measurable things. That's one good thing about freight which I also learned after spending time is that you know how measurable everything is. Not many industries are like so unitized at the fundamental, like business object level. In this case, everything is unitized at the fundamental, like business object level. In this case, everything is unitized at the load level.

Harish Abbott: 1:14:42

And like, you know, loads per rep, or spread per load, or you know anything, you, every brokerage, we may not have the highest fidelity, but they do have a measure of that, you know. And so so those are, I would say, the metrics, and. But but really I'm like and I'm not even saying it to be like this you know, we, we, we, we just hired our head of ops and either he we I just this morning at the chat, like the only goal is customer delight. There is no other goal. You know, if you do that, everything follows.

Andrew Silver: 1:15:20

There is no other goal. If you do that, everything follows. Yeah, I prescribe to that medicine, so I can pick up what you're putting down there. How about, like five years from now? What does Augment look like?

Harish Abbott: 1:15:37

What does a successful five-year trajectory look like for you? Well, hopefully we're serving many more industries in the broader logistics supply chain area. You know we're impacting a lot more business, but really I think like, if you look at the size of the logistics industry that's 3 point, some trillion in the US, 10 trillion broadly I think there's at least 10% waste. Would you agree? Yes, 10%, at least At least.

Andrew Silver: 1:16:04

There's so much.

Harish Abbott: 1:16:06

There's trucks running empty, there's trucks laying over, there's a lot, there's scheduling labor, but the truck doesn't show up. There's just so much waste, right? So if you look at a $10 trillion global world with at least 10%, that's like a trillion dollar of waste. Could we cut that In five years? Hopefully we've made. Cut 10% of that. That would be a cool goal. It's a hundred billion. That's what we're going for here.

Andrew Silver: 1:16:42

No one will say you're not ambitious. If you can cut $100 billion of waste in five years, you're going to be hired as the next Doge leader to go to the government and cut waste there. Yeah.

Harish Abbott: 1:16:59

Well, I think, I mean, I think there's some that's like it's exciting. You know, like that's what got me started with Augment, which was like hey, like there is, in our own little way, a shot at at at making this, this word that powers everything we do better. Reduce the waste here. And if you've seen everywhere, when you cut the waste, more of it happens, it actually doesn't shrink the industry ever, it just makes more usage of it. And it's a very simple thing which is like, if you think about, there was, you know, there's like printing presses and there's a bunch of books being written, and then internet came and then, like the number of content just exploded. You know, because we sort of reduced any of the waste that was part of. Like you know, because we sort of used any of the waste that was that was part of.

Harish Abbott: 1:17:59

Like you know, when you printed a bunch of books, some of them were never read and so there was a cost borne by everybody. It was very hard to access and distribute. Now, you know so, anytime, like you know, if you think about like these big platforms, like before, like Shopify type platforms, they were just like maybe 30,000 online businesses selling online, you know, and now there's like 3 million and because Shopify like reduced the cost of, you know, setting up a store and running a world-class store and setting up the payments. So every time you do that, just the market like grabs it and like expands in ways that nobody ever imagines. You know, and I think the same is true for logistics I don't think people would think that it's a fixed power industry. I actually don't think it is. I think the more efficient we make it, the more of it will be.

Andrew Silver: 1:18:55

Yeah, I'm trying to. It's hard to like visualize it, but I think I'm with you.

Harish Abbott: 1:19:11

I'm just trying to see what comes as waste reduces, but I definitely I see how it leads to much as we have access to. There is probably a coffee mug maker somewhere in the world who's unable to reach you because logistics is so cumbersome and expensive. Yeah, but if you cut the waste, that person will be able to reach you.

Andrew Silver: 1:19:35

Yeah, I'm with you, there will be more. Yeah, yeah, okay, I see.

Harish Abbott: 1:19:40

And so I think that's where the exciting part is. And it enables commerce and you know, trade and commerce is what civilizations are based off. Right, like ultimately, you will be kind of like need trade and commerce to, to try so and need trade and commerce to thrive. Okay, well, you went a lot in philosophy here.

Andrew Silver: 1:20:08

Yeah, we're getting deep there. I was trying to think of how to wrap coming off of that. As we wind our time, I think I usually go to some advice and I definitely want some from you. So give our audience a piece of advice on building businesses in the logistics space. What's your cardinal rule, that kind of your most important guiding principle, that every day when you wake up you're thinking I got to do this or the business has to do this, that aspiring entrepreneurs can maybe grab from you and carry into their own world.

Harish Abbott: 1:20:45

Yeah, listen, my learning in logistics is that it's messy, it's complex, it humbles you like no other industry. You know it is a very, very like. You know it is. It is a very, very like. You know my.

Harish Abbott: 1:21:07

I tell you I'm perpetually humbled by the complexity of logistics. Like there has not been a single day where you, like you wake up like I think I had the answer. Then, oh, there's another edge case. Oops, never thought about it, you know. And but I think in that is this beauty, right, it's just this messiness and complexities, but this opportunity and the beauty is that if you want to go deep and truly understand it, like why? And I think, like wrestle with it, like there is so much to be done here, it's such a big industry, um, but but like don't approach it with like hey, my views. Like don't approach it with like hey, my views. Don't approach it like I've got it figured out from like 50,000 feet and like I know the answer. No, like, go in, you know, go super deep. Like spend time with the operators, spend time with the frontline guys, really understand what they do, why they do it. You know there is a reason for it and work with them to make it better, reason for it and work with them to make it better. You know, like, don't like design a solution, like in a room, and then like, hey, I've got the shiniest. And then, like you know, come and use it. It's just very hard because the complexity is so high and it's for a reason. You know, I think my biggest rule in building businesses is that get close to the operator, just get close, just spend time with them. You learn so much People who are actually doing the work.

Harish Abbott: 1:22:29

Maybe the CEO buys your product, Maybe they are the ones who pay for it, but the real test is is your operator loving it? Are they using it? But the real test is is your operator loving it? Are they using it? You know, and guess what, like, if you can make that, set the ladder happen where they love it, they use it and they get value from it. Yes, the CEOs will pay for it, you know. But, like, don't get the CEOs to pay for it. Just forget the operator At that point.

Harish Abbott: 1:22:57

At some point in a few years, the shine's going to come off and then it's like it will be unused, paid license, which there are plenty in this industry. That's another thing. Oh my gosh, the amount of unused paid licenses is a lot in this industry. And so that's my big thing, which is like get close to the operator, like get as close, feel the problem, be in their shoes, build for them, and then I think you work, work, work upwards. If you do that, like roi comes, customer delight comes. You know all the business metrics sort of start to hopefully take shape.

Andrew Silver: 1:23:39

Great advice. Know that customer. Yeah, know that customer Live in your customer's office.

Harish Abbott: 1:23:46

Yeah, exactly Exactly. Yeah, I mean, we have people who are like batched in, you know they're indistinguishable today from they are an augment employee, or you know one of the one of our customers' employees. But also, don't just stop at the prioritization of the leadership, because these businesses are so complex and they're so large. The leadership could think of hey, I think these are my top four priorities, that's great, but, like, go to the level where they're actually using it and then connect the two. You know, sometimes there is a separation, right, like or like dissonance between those two. Yeah, and it's important to bridge that dissonance.

Harish Abbott: 1:24:34

But you can't do that unless you like you know spend time. You know that, unless you like you know spend time, you know with, uh, with with the operators, you know, like there was one, one business we were at, like they're like, oh, we don't, like we ban telegram, we don't use it. Okay, we, it's like that's not of use to us. Like we know how you can telegram, but we don't use it. And I'm like, okay, we spent like six hours with your operators. Every single one uses it, every single one uses it.

Andrew Silver: 1:25:07

We didn't even talk about that. The difference between what the leaders think the team is doing and what the team is actually doing.

Harish Abbott: 1:25:16

Yeah, it is because the dispatchers are in Eastern Europe, because that's the only tool they use, you know. And so, and they don't they hate calling the driver when on the road. So they say we want to just telegram the dispatcher and always get the response. And well, you have to recognize that as a true need, you know right. And so now, if you start to call the driver through an AI bot, who's not happy? It's the operator. So you're going above me, doing something that I hate doing. It's annoying my carriers. You're calling their drivers when I have a method that's working. So lean in that method that's working, and so I think you have to break that dissonance quite a bit, in my view.

Andrew Silver: 1:26:03

Yeah, I'm with you 100%. That's a great point. It's a good one to end on. We're coming up on time here, so listen, this was great. I appreciate you playing the game with me. It's funny. I had an idea I wanted to talk about your past and these companies, and then we started with. Logistics is Broken. That took us to Augment, and we just spent an hour and a half talking about that, which was a great conversation. At least I enjoyed it, so I hope you did too.

Harish Abbott: 1:26:30

Yeah, I loved it too. No, you learn from all and sometimes, when you're even speaking, you're like rethinking and learning, but it's always good to talk to. You know an operator like you. You've built businesses, you've seen the pain, you've seen. You know the highs and lows of this business right. So it's always good to talk with someone like you. So thanks, andrew.

Andrew Silver: 1:26:51

Well, I appreciate you coming on cheering for you and your team. You've hired one of the best in Haley Weiner. Shout out, haley, she won't listen to this, but she's one of my favorites that I've ever worked with. She'll do great for you. No-transcript.