theCUBE + NYSE Wired present the East Coast AI Leaders Executive Series | Tom Petit, Didero

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Tom Petit

Co-Founder & CEO

Didero

play_circle_outline Enterprise AI adoption and potential for growth in the market

play_circle_outline Targeting mid-market companies with 30-300 suppliers for AI solutions

play_circle_outline Vision for autonomous supply chain with gradual implementation of AI capabilities

play_circle_outline Didero AI's focus on automating supply chain workflows for procurement

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Tom Petit, Didero

Tom Petit

Co-Founder & CEO Didero

TheCUBE at NYSC Studios in New York has two sets and is currently in operation. Tom Petit, CEO and co-founder of Didero AI, discusses how they are building AI for the supply chain, automating routine tasks for procurement teams. Didero AI aims to assist mid-market companies in automating workflows like sourcing, supplier onboarding, and invoice management. They employ 20 engineers and are working towards creating an autonomous supply chain. Their approach involves understanding customer workflows, ingesting unstructured data, and suggesting tools and tasks to... Read more

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What is the current adoption rate of AI in the enterprise sector and what potential do you see for rapid growth in the near future? add

What is one real opportunity that is being seen with early customers in the mid-market? add

What is the process of transitioning from manual data management to utilizing AI in the data business? add

What is the recommended approach for implementing AI agents and transitioning to an agentic model within an organization with outdated infrastructure and processes? add

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Tom Petit, Didero

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>> Hello. Welcome back to theCUBE here at the NYSC Studios of our New East Coast location. We've got two sets, one's operation. We're up on the balcony, looking the show floor. I'm John Furrier, your host of theCUBE. Dave Vellante is going to pop in. We should be up and running in early 2025 full time, but we pop it in for media week here, wall-to-wall coverage. Our next guest is Tom Petit CEO and co-founder of Didero AI. Great to see you. We're just chatting before we came on talking to the production team on the 12th floor. Getting ready. Good to see you.

Tom Petit

>> Thanks for having me.

>> So you guys are great example of a startup that's hitting the scene in the perfect time. We're in a super cycle. I love the term super cycle. Dave Vellante and I both love it. We've seen this before, 86 to 96, the web from 97 to 07, and then now we're in the GenAI. We saw the cloud wave, so great time. You guys are in New York. What do you guys do? Give a quick overview about the company and then we'll jump into some AI.

Tom Petit

>> Yeah, happy to. And you're right, this is such a great time to be building an AI company. We're a venture backed company here based in New York. We're about 20 people and we're building AI for the supply chain, helping procurement teams cut through the noise, focus on what matters by automating, being an assistant to a lot of the routine boring work that they have to do.

>> Yeah, enterprise AI is hot. I just came back from and just wrote a couple stories on this week, both on SiliconANGLE and theCUBE Research. Only about 1% of the enterprise is actually using AI right now. Mostly it's a big consumer thing with obviously the OpenAI perplexes of the world and a lot of kind of the big GPU on the infrastructure side, but the huge upside in the enterprise is going to be a massive, I think, very fast movement in AI. Before we get into it, because I want to talk about the workflows that are out there and opportunities to understand these processes and how to make AI kind of automated as they delegate that responsibility to software.

Tom Petit

>> Yeah.

>> But give a quick stats on when you guys were founded. What's the company makeup look like? What's the culture like? How big are you? What round are you in? Give some of the numbers.

Tom Petit

>> Yeah, the quick stats, we were founded last year. We're about a year old. We are seed funded. We rode the wave of AI software for B2B for enterprises and mid-market businesses to raise a very good seed round, $7 million. Some of the largest venture firms in the Valley. 20 people, mostly engineers. We've hired people from the best AI companies, Facebook, from Citadel, from you name it, Microsoft, AWS, and we've brought them in to work on something that few people pay attention to, which is the real economy. It's the $30 trillion of goods that are trading hands, that are changing hands every single year. That's what we're focusing on.

>> Yeah, you guys got some good VCs first round capitals. There are gals in there too, a bunch of other luminaries and a modest round too, which is great to see that discipline. You take too much cash, you get too drunk on cash and you miss the window, but this is going to be a great wave because the enterprise, I think the enterprise AI is a lot harder than people say it is, because the low-hanging fruit, the difference between a bubble bursting like the .com bubble and the AI bubble is that there's real money to be made in services with AI in the enterprise. You guys targeting procurement kind of as initial beachhead, I'm sure you're going to go beyond that, but there's a lot of manual labor and labor involved in enterprise where workflows can be laid out end to end, and AI can be applied to that if it's trusted and delegated properly is a huge opportunity. And just procurement is a low-hanging fruit. I'm sure you got other vision. Take us through how you guys are approaching this with your customers. As a startup, you've probably got some good design partners. Take us through some of the mechanics of how you guys are engaging your customers.

Tom Petit

>> Yeah, what you're saying is exactly right. We have statistics that show that supply chain managers, supply chain teams spend roughly 80% of their time doing routine manual workflows, not the strategic stuff that they should be spending their time on. What happens if there's tariffs with China next year? What happens if a ship gets stuck in the Suez Canal? All those disruptions that we saw over the last few years have brought to the fore the importance of having a supply chain that's resilient and instead of focusing on that resilience, people are stuck handing purchase orders. 50% of people's time is going back and forth managing purchase orders, so what we do is we enable people to take a step back, put some of that honestly quite boring stuff on the automation so that they can focus on the strategy. And you were talking about enterprise. What I find interesting is some enterprises have very good systems in place. It's very old technology. It's technology from the 70s, the 80s, but they have some systems to automate the sending out of a purchase order. Some of the real opportunity that we're seeing with our early customers is the mid-market. It's companies that have between 30 and 300 suppliers, companies that may have a supply chain team of five to 20 people and who don't have access to those enterprise grade solutions because they're too expensive to set up. They need heavy customization. The step change that AI is enabling is taking those enterprise solutions and making them accessible to the mid-market because you can skip the very long integration process and the very long customization process that's so expensive and that is inaccessible for mid-market companies.

>> Take me through how you guys are thinking about this super cycle around this area, because one of the things we've been talking about on SiliconANGLE and theCUBE is how in this new era, the ecosystem of partners is important in the enterprise because they can partner with a lot of people. And connected and together is an important aspect, partnering and integration. Do you guys see yourselves as more partner friendly in an open ecosystem, or do you see yourselves being kind of just a game changer, brute force in there and just be like that Airbnb, like we're the different new generation and go run the table? What's your view on this?

Tom Petit

>> We're very much the former. We're very much a partner to the other companies, the other systems that people have in place. A lot of the companies that we work with have very established ERP systems. They use NetSuites, they use SAP. They have very established accounting processes. We're not coming in and saying, Hey, we've got this completely different way of doing things. We're telling them, you know how to run a supply chain. That's your competitive advantage. Let us come in and automate the processes that you've set up over the last 10, 20 years. We can sit on top of some of those other systems that you're using. We can leverage your existing NetSuite systems, but instead of having people whose job it is to spend five hours a day in NetSuite clicking buttons, let us automatically create those purchase orders. Let us check your emails to see if there's a tracking number that comes in and a shipping date and import that into your systems. Let us communicate with your suppliers to check that everything is going according to expectations and alert you only if things are going wrong, only if there's an exception. So we're thinking of ourselves not as this full disrupter that rips everything out and puts a new system in. We're sitting on top of what people are using.

>> That's the go big or go home, win or lose, but you're taking more pragmatic. The enterprise is hard.

Tom Petit

>> It's very pragmatic.

>> I like that approach. The next question, so I would say that. So am I correct to say that your strategy as a company is to own the supply chain area, get in there, be experts, be passionate about supply chain. And your entry strategy is procurement, is that, how would you describe that? Is that accurate?

Tom Petit

>> That's right. Procurements for the manufacturers and mid-market companies that we serve is a core aspect of their supply chain, and so what we focus on is the tasks that are the most manual, the most routine for which there are the fewer tools. A lot of what we've seen is it's in the sourcing, it's in the supplier onboarding, it's in purchase order management, invoice management, compliance, supplier performance management, all of those aspects of the work that often require a lot of manual communications, a lot of repetitive tasks which can be automated.

>> Okay, so I'm going to ask you the steady state question.

Tom Petit

>> Tell me.

>> So okay, imagine you guys are continuing successfully. You get the next round of funding, you're adding all these awesome talent. In the steady state of you deployed in the customer, what does that look like in your mind's eye? Okay, I can see the customer executing flawlessly with us. What's that steady state business outcome look like with you guys?

Tom Petit

>> What's interesting is our long-term vision and how we get there. So the long-term vision is what we call the autonomous supply chain. Imagine a self-driving car. You tell the car where you want to go, it just takes you there, and our vision is a manufacturing business needs 10,000 widgets. They describe the widgets into our software and we can do everything from sourcing to onboarding the suppliers with the right qualifications to managing the purchase orders and the payments, make sure we have the goods. Now, if you're driving a car from the 70s, you're not going to go straight into the futuristic self-driving car.

>> Exactly. We'll just say Tesla. Right. And an old Mustang, 1965 Mustang.

Tom Petit

>> Right.

>> Now I got a Tesla. Completely different animals.

Tom Petit

>> And you want a bit of a transition. You want to start with a car that may have cruise control and then a car that may have lane assist.

>> So you're in the data business.

Tom Petit

>> We're in the data business.

>> You're in the backend operational sourcing, full operating environment around serving that business process.

Tom Petit

>> Right now, we're in the data business ingesting all the unstructured data that is sitting within our customer's platforms. A lot of it is completely unusable because it's unstructured. We're taking in that data. Right now, we're mostly suggesting tools, suggesting tasks. We're saying, hey, you should be paying attention to this. This is the cruise control, right? We're telling them, hey, let us help you with a few things, but you stay in control and progressively our customers will learn to trust us, to trust the AI to make more and more of those routine decisions on their behalf.

>> Take me through your recommendation. I'm believer, I love the idea of agents. First I'll use assistants and co-pilots, whatever want to call it. Then I'll go to full agentic,-

Tom Petit

>> Exactly.

>> Reasoning, reinforced learning, et cetera, et cetera. Where do I go from here? I've got this antiquated, outdated infrastructure. I got processes that we, well, no I don't want to break anything. What's your recommendation? How would you recommend that I implement the direction and ultimately get to an agentic environment? What do I got to do?

Tom Petit

>> Our customers, our successful customers are very clear-sighted about what's holding back their teams from being more strategic. What are the workflows that people do every day that just keep them in the weeds, and so first you have to understand what people are doing to understand what can be automated, what can be assisted. When we've got a view of that, then we can come in and we can fully understand those workflows. Sometimes we see videos of what those people are doing, which buttons they're clicking on. We can automate them and we can free up a bunch of time for teams to do what matters. Often, this takes the form of looking at how they use their existing ERPs, how they use NetSuite, how they interact with customers. We look at threads with 50 emails of back and forth for a single supplier onboarding, and that's one supplier, but people have to do that hundreds of times. We take those, we train AI agents on that specific data. It can be customer specific, and then we can start automating and assisting so much of those workplaces.

>> It's great to have the co-founder, CEO on because get to ask the questions around culture. Every company has a cadence. Intel used to be Moore's law, faster, doubling every whatever months. What is the culture like? You guys wake up every day, you just eat process for breakfast. How would you describe the DNA of the founders and the company? You guys just love process, love automation. What's the cadence of the mindset of the A team?

Tom Petit

>> Well, the first thing is we're very technical.

>> Yeah.

Tom Petit

>> I lead the business. I'm also the tech co-founder, and I come from a data science AI background. I work for companies like HelloFresh, like Airbnb. I had a previous startup before this, and so I live in the code in the data. We pay very close attention to that and we bring on people who are just as passionate about that, but then we inculcate, we share that passion that we have for the supply chain and the supply chain is a bit like the internet.

>> Yeah.

Tom Petit

>> As long as it's working, everyone just assumes that it's fine. People don't understand what's below the surface. When things break, as we've seen recently, people understand the importance, so we share some of that passion for the supply chain with the people that bring on, and that's a very unique combination in the tech world. People are spending a ton of hours on tech, on consumer tech. There's very few teams that are as passionate about working on the supply chain. So that's the core of what we are, and then we have very quick iteration cycles on technology. Every week we ship new features. We use the latest and greatest from all the open source and closed source AI models, and we can really make a difference pretty quickly in what we built for our customers.

>> Yeah, and the code. I mean everything is code and services now, microservices and cut services, and that's helpful. A lot of people don't understand operations is technical too. I mean, you talk about whether it's running a big monster hyperscaler data center or cloud, IT or whatever operations, operations is workflows. It's code.

Tom Petit

>> It's workflows, and yet those teams that matter so much have been ignored by mainstream technology. If you go to Silicon Valley, there's very few founders who are focused on helping those teams that day in and day out get us the goods that we need or get the goods that manufacturing teams need to get their revenue to manufacture their own products. Bringing more attention to this space is really, really fun.

>> We've been saying for years in our last podcast last Friday. Folks, if your want to hear it was about IBM and others in the enterprise. We've been saying for years that software economics applied to services, professional services changes the game. The old way to transform and do a transformation in procurement was you called the big consultants to come in. It's going to be a 10-week project. We're going to bill you tons of cash.

Tom Petit

>> 10 weeks if you're lucky.

>> We'll have another 10 month action plan, and after 10 months, we'll maybe have a recommendation. I mean, I'm over the top, but the point was it was very long-drawn-out. Give me your watch. I'll tell you what time it is consultant, professional, I mean, I'm being a little bit hyperbole there, but the point is professional services used to be, oh my God, if it's not a platform that scales exponentially, I don't want to invest in professional service. Or professional service is not a good area to invest. What you guys are doing is what we're seeing as the AI trend where services, could be web services, cloud services, app services, AI services, and the professionals getting blended into the platforms where there's operating leverage that have software economics.

Tom Petit

>> That's right. That's right.

>> Do you see that? Do you really, don't really care about whether you're called professional services? Because you're basically providing a professional service with software. It's not like a SaaS app where it's like, Hey, I download the app and I'm like whatever, self-serving. Your platform is part of the delivery of the service.

Tom Petit

>> That's exactly right. So there's two extremes to the spectrum. There's the SaaS software platforms, old fashion. They just tell you take it, you use it, you configure it, you're on your own, and then there's the full-blown professional services where you don't even have access to a platform. We see a great middle ground where we give access to a platform, but we provide the underlying services that make the process of using the platform completely seamless. A lot of what happens on the platform would formally have had to be run by the customers and we can do it on their behalf.

>> And the agents become the service delivery.

Tom Petit

>> And the agents become, exactly. That's right. I've got two co-founders. They're both incredible. One is from a consulting background from McKinsey, and so he saw those long implementations and he saw what could be made better. Another comes from a manufacturing background and he was looking for software that could help him run his company.

>> Yeah.

Tom Petit

>> He didn't find anything that didn't have those half-million-dollar budgets and six-month implementation periods, so we're really building what he would've wanted to have when he was running his manufacturing business.

>> So your competitive strategy, if I could maybe guess and connect the dots, is to be agile on the delivery of the value faster than anyone else.

Tom Petit

>> That's exactly right. We've onboarded customers in 24 hours and that's something that just was not possible before GenAI came along.

>> Well, Tom, great to have you here on theCUBE. Great conversation. We're in New York. We're going to be here with a team, so we'll probably see you at some of our events and meet us. We're going to have probably kind of, do a cool social meetup situation here. I love New York, love the action. It reminds me,-

Tom Petit

>> Best place to be.

>> Yeah, it's a great place to be and of course we'll connect it through content. We'll certainly have you back on theCUBE. Thanks for coming on.

Tom Petit

>> Thanks for having me.

>> And congratulations.

Tom Petit

>> Thank you so much.

>> Okay. theCUBE is here inside the New York Stock Exchange for our kicking off of another media week talking with AI leaders. Startups, speed, and agility to deliver the value, software economics in the model is what's key. AI is just another application, and so we're going to see a lot of sea change, a lot of transformation, new brands emerging. You're going to get it all here on theCUBE. I'm John Furrier, your host. Thanks for watching.