Dell Technologies Capital: How To Build A Deep-Tech Startup For A Market That Isn’t Ready Yet And Why AI Won’t Kill SaaS

Daniel Docter , managing director at Dell Technologies Capital , began his career as a technologist. He holds degrees in electrical engineering and computer science, as well as a Ph.D., but early on found himself gravitating away from purely technical work toward translating technology into business and commercial use cases. Docter also proved adept at securing funding for research and other projects, a skill that ultimately caught the attention of venture capital firms and led him into the industry 26 years ago. His technical roots are reflective of Palo Alto, California-based Dell Technologies Capital’s broader team. Its investors have degrees in fields including electrical engineering, computer engineering, computer science and data science, and many have worked at both large technology companies and startups. Daniel Docter, managing director at Dell Technologies Capital. (Courtesy photo) That experience shapes the firm’s affinity for deeply technical founders and its approach to early-stage investing. When evaluating seed and Series A companies, the team focuses heavily on the potential impact of a technology: what problem it solves, what it could disrupt, and how well it works, often before traditional financial metrics become the central consideration. Since its 2012 inception, Dell Technologies Capital has invested $1.8 billion across the enterprise stack and saw six high-profile exits at the end of 2025 alone. In this interview with Crunchbase News, Docter also discussed how AI is reshaping SaaS and why he doesn’t believe the business model is headed for extinction. He also shared why he thinks distribution may ultimately separate the winners from the losers among AI startups, and more. The interview has been edited for clarity and brevity. Crunchbase News: When you evaluate companies, do they all have to tie into what Dell does? Docter: Not necessarily. I usually describe it as Dell Technologies Capital having a unique network you don’t get at any other VC firm. I’m using my words carefully because I’m not saying we’re better. I’m just saying we’re unique. That unique network is that we have access to Michael Dell’s network and his company network, which has become even more relevant in this AI world but has always been very much in the middle of technology. We leverage that network in two ways. One is to get another perspective on what’s going on in the world and understand technology and how it’s being used. What do Fortune 500 companies want or need? What is Goldman Sachs asking for? We have that perspective. If you look at the other side of the coin, those are also the areas where Dell Technologies Capital can best help our portfolio companies. We have this perspective and this network that are really valuable. We can use those to the benefit of our portfolio companies, and that defines our investment philosophy. Warren Buffett classically said, “Invest in what you know.” The way I look at it is that we’re trying to invest in what we know because of who we are, our technical background and our unique network. But if I turn that over, that’s also where we can help. Invest in what you know, but also in what you can help with. For founders building deep tech, there’s a fear of being on the right track, but too early. Some companies have had to wait more than a decade before they really took off. As an investor, how do you evaluate a team that is clearly building technology with incredible potential but is years ahead of the adoption curve? How do you help them survive that stretch of time? Docter: You asked two questions in one. One is: How do you identify the founders you think can be successful? The second is: How do you keep them alive long enough to get to the finish line? The answer to the first question hasn’t changed from how we’ve always thought about it and how venture capital always thinks about it. First and foremost, you’re really betting on the people. This is a people business. I know you hear that all the time, but you really are betting on the people and the founders. It’s not purely about the technical capability of the founders. There’s definitely an EQ part of the equation, which I think our team is really good at. Our group is good at quickly getting an opinion on a founder and whether he or she is capable. Then we usually spend additional time trying to pressure-test our initial thesis on that founder’s ability to be agile — to understand when they’re wrong and change directions or to be willing to get input from somebody else who might be way less smart than they are but has a different approach or way of thinking about the problem that opens up new avenues. I think that’s qualitative. It’s EQ more than IQ, but a lot of times that determines success. I don’t think this AI era has changed that. That’s consistently true. The answer to the second question is even harder. How do you know if you’re betting on a deep-tech company and you know going in that this is a five-, seven-, 10-, 15-, or 20-year problem? It’s really, really hard to sustain that company. You have to do a bunch of things smartly. You have to make sure you don’t overspend, because overspending can really kill a startup. You also have to have really good co-investor partners. We feel like we are part of a venture capital ecosystem, and we always strive to partner and play nicely with others. As Michael says, “Play nice but win.” We always try to play nice but win. It takes a village for these things to work, so it’s important to have the right constituents and partners around the table who can continue to fund the company for years and years. The timeline is absolutely compressed, so I think it is getting harder for that to happen. The classic venture playbook often considers first-mover advantage to be everything. But the “sleeping giants” thesis suggests the second wave — the companies with the foundational architecture in place when a catalyst like generative AI hits — may be the ones that win. Is being a first mover still the same advantage it used to be? Docter: I think it can cut both ways. One of the things we talk about is whether a company is doing category creation — which means it’s creating a brand-new category of business or software product that doesn’t exist today and is going to be huge — or category disruption, meaning there’s already a very large category that exists and I’m going to disrupt it with my technology. I’m doing something much better, faster, cheaper or stronger. It’s important to have a sense of whether a company is doing category disruption or category creation. If you’re doing category creation, being first means you have to educate everybody. It’s a heavy lift. It’s a daunting amount of work, capital and effort that goes into explaining something that doesn’t currently exist and why it’s going to be needed in the future. A lot of times, first-mover advantage isn’t an advantage there. Category creation is often where the second, third or fourth company hasn’t had to spend all the effort. They can piggyback off the heavy lifting the first mover had to do. But in cases of category disruption, I think there’s value in first-mover advantage. You’re disrupting a big, existing, multibillion-dollar category and doing something in a new or better way. Being first there is very beneficial. There’s a lot of talk about AI agents replacing SaaS models. Do you feel that panic is overhyped? If so, why? Docter: AI is disruptive to the SaaS world, without a doubt. It’s disruptive because it will change how software is built and consumed. Maybe even more importantly, it’s going to change how it’s priced. The per-seat pricing model is probably outdated and going to die. It’s going to be priced based on consumption or outcomes. Everything is disrupted, but I fundamentally don’t believe all SaaS companies are going to die because of this. I believe the SaaS companies with smart, effective management will look at what AI can do for their busi