In this Tech Optimist podcast episode, host Sam Herrick interviews Pete Mathias, a partner at Alumni Ventures, and Fernando Rodriguez Villa, co‑founder and CEO of AdeptID. The conversation introduces AdeptID’s AI‑driven talent‑matching infrastructure, which sits as an API‑first layer beneath applicant tracking systems, HRIS platforms, and job boards. Fernando explains the company’s mission to identify talent based on potential rather than past titles, addressing the massive under‑employment and skill‑gap challenges in sectors such as healthcare, cybersecurity, and renewable energy. He outlines his background in AI applied to large, messy economic datasets and the decision to build a back‑end‑only solution akin to Stripe or Plaid. The discussion highlights market and technology tailwinds: a shift toward skills‑based hiring and the emergence of large language models that can parse semi‑structured recruiter notes. Fernando shares rapid growth metrics—3.6 million users in 2023 and a projected 16 million in 2024—driven by integration into existing workflows rather than direct sales. The episode also presents 2024 hiring statistics (e.g., 8.1 million U.S. job openings, high sourcing difficulty, long interview cycles) that underscore the pain points AdeptID aims to solve. Finally, Pete asks how the Alumni Ventures community can help, emphasizing broader awareness of AI‑based potential hiring and alignment of tech stacks with data‑driven talent identification. The episode closes with a call to action for listeners to rate, subscribe, and engage with the Tech Optimist community.
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Can AI help you get your next job? Let's find out.
And so the more we can work the technology into existing workflows, that felt like the right way to kind of get to scale faster and get to impact faster.
There will be many, many more of these, these roles that are hyper-niche, that are hyper-specialized. In other words, that, that AI cannot simply duplicate.
But also that systems like ours can make sense of Hello, everyone.
Welcome back to this episode of The Tech Optimist Meet the Startup, AdeptID. We have an awesome episode planned for you, and the voices you'll hear today are from Pete Mathias, our partner here at Alumni Ventures, who you've heard before, and Fernando Rodriguez Villa, co-founder and CEO of the startup, AdeptID. And then, of course, myself, your Tech Note writer, Sam Herrick, here and ready to take you along this journey. So, join me. Let's get started. All right. Let's go. In a world captivated by criticism, it's easy to overlook the groundbreaking technologies shaping our future. Let's shine a light on innovators who are propelling us forward. As the most active venture capital firm in the US, we have an exceptional view of tech's real-world impact. Join us as we explore, celebrate, and contribute to the stories of those creating tomorrow. Welcome to The Tech Optimist. As a reminder, the Tech Optimist podcast is for informational purposes only. It is not personalized advice, and it is not an offer to buy or sell securities. For additional important details, please see the text description accompanying this episode.
Welcome to another episode of The Tech Optimist. Today we have a special guest, Fernando Rodriguez Villa, and we are talking future of work. Adept ID is the brainchild of Fernando and his team, and we are going to dig into one of the greatest assets that we have in the world. That is the workforce. Fernando, thank you for joining us. Give us the background. Give us the elevator pitch. What is AdeptID building?
Sure. So we are AI talent matching infrastructure for the talent industry. My co-founder Brian and I started the company in 2020 because we felt like there was an opportunity to harness AI to identify talent in the majority of the workforce that is poorly served by the existing kind of companies and also like tech tools. And so, you know, it is, as you alluded to, Pete, you know, common knowledge that there are tens of millions of folks that are underemployed in this country, while at the same time there are these kind of structural skill gaps, or at least perceived skill gaps, in critical industries like healthcare, cybersecurity, renewable energy. These are all really big problems in the economy and society that have huge workforce components, but these kind of perceived shortages. And I think, you know, a lot of energy and thought has gone into what are the changes that kind of companies can make in the way that they look at talent, or what is the type of training or education that's required to kind of provide some better economic mobility or better pathways for individuals to go from jobs where they're underemployed to jobs that are of critical need. But less attention has been paid on the actual tools. Even with a lot of, I think, positive energy and will behind trying to improve job mobility in this country and around the world, we're still using applicant tracking systems and job boards, and certainly a lot of kind of education infrastructure that just kind of exacerbates the problem because it has a very simplistic way of looking at someone's work history or their education or their potential. And so Brian and I have been building AdeptID as kind of a technology layer that sits underneath all of those ATSs, HRISs, job boards, etc., and then allows them via API to identify talent on the basis of potential.
A little bit more on AdeptID. I am currently on their website on their Our Missions page at adept-id.com/our-mission. And I'm just going to read it all because I think it really adds to, you know, What Fernando is saying here and what their company does. So our mission. Adept ID's mission is to get more people into better jobs faster. We believe that everyone is adept. All individuals have skills, capabilities, and aspirations that make them able to succeed in jobs, even jobs that are different from what they've done before. We believe that technology can be used to identify potential and make connections to benefit all stakeholders. Our transformational matching technology connects people, training, and jobs. As we connect the diverse applications in the talent ecosystem, we serve as a keystone to get more people into better jobs faster. Inclusivity, collaboration, and transparency are not only a requirement for our technology, but also for our work with each other. We are a public benefit corporation headquartered in Boston, Massachusetts, and active worldwide. So the definition of adept is very skilled or proficient at something. A person who is skilled or proficient at something. So it really makes you think about their company name, right? It's, uh, helping stakeholders ID those people or individuals who are very skilled or proficient at something. And that something obviously is tailored per company and per position opening. All right, everyone. You know the drill. We're gonna hop into a quick break and then straight into the interview. Don't go anywhere. Trust me.
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2020 is an early time to be thinking about AI at the intersection of workforce. The talent gap is an observation that became obvious after COVID, how profound it is. How did you come to this insight? Tell us your origin story, the Fernando inception.
Yeah, so I've been working at this kind of intersection of AI and large kind of messy economic datasets for most of my career. After a stint in finance a long time ago, worked for a company called Newton that was applying AI to education proficiency data to try to power personalized learning at scale. And so I've been really attracted to this idea that you can connect that technology with large, poorly understood datasets with a lot of kind of messy and complicated stakeholders to solve these problems and to do it kind of under the hood, right? So that company, like AdeptID, doesn't have a front end or a thing to log into. We interact with our users in the back end, much like a Stripe or a Twilio or a Plaid. And so that has, I think, always been an attractive kind of business and product model for me. And as Brian and I started really kind of thinking about, okay, what is the right way to get this type of technology into the bloodstream of the talent industry to impact the most people the most profoundly, really building a kind of— building our own ATS or building a point solution felt like it would just it just wouldn't be big enough and it wouldn't really meet folks where they are. You know, I think a lot of individual job seekers or talent seekers, right, employers alike, don't want other things to log into. They don't necessarily want to go out and procure a new point solution. There's a lot of vendor fatigue, particularly in the kind of the HR space. And so the more we can work the technology into existing workflows, that felt like the right way to kind of get to scale faster and get to impact faster. So, you know, last year in 2023, there were 3.6 million people who used tools that used AdeptID. And so, you know, none of those people necessarily knew who AdeptID was, but because they were interacting with an iSolve or UKG or whatever it is, they were getting kind of surfaced for their skills because of our technology. This year we're on pace to 16 million. And so that kind of dramatic uptick wouldn't have been possible if we were going out and selling employer to employer. Our ability to partner and sell into these kind of nodes in the network has allowed us to get to a lot of scale, which for the purposes of what we're trying to do, right, which is train on a lot of information of people going from job to job successfully or not, the kind of the bigger footprint and the more training data we have access to, The better our solution gets.
Fernando, let's, let's talk about tailwinds. You've talked about the scale that you've achieved at this point. Zoom us out, market level, global trends level. What are really, really the energies that are electrifying AdeptID into this exciting future of work frontier?
Well, there are a couple that are market, and then there are a couple that are technology-based. I think kind of from a market perspective, you know, we talked a bit about certain industries are really feeling the pain of not having access to a workforce that's kind of appropriately skilled. And they historically have been kind of defaulting on this very 20th century notion that they have to find talent that has kind of done the job before. But if the job is so new, that there just aren't people out there who've done it, then you need to have a more predictive way of finding talent. And so there's a bit of tailwind behind the, you know, the wind turbine techs, which like, hey, if you're going out and trying to find someone who's done that job, you're just gonna have a really hard time, right? And so there's already a bit of kind of changing minds and hearts around finding more predictive ways, which technically is actually pretty complex. And so there is a need for technology to play a role in addition to— That changing mindset. And that's been a positive tailwind for us. That gets described often as skills-based hiring, which has become a huge theme within the HR and workforce world. I think, you know, on the technology side, this kind of recent advent of the— call it the kind of GPT-3 and beyond availability of LLMs. has meant not just that things like chatbots are easier and more personable to interact with, but also that systems like ours can make sense of vast amounts of semi-structured data. So until a couple of years ago, most of the learning that we did from a technology basis came from much more kind of readable data points, like whether someone got a job or not, right? And that's, that's Easier to quantify, it's easier to make sense of, the systems could kind of crunch it at more scale. Now we're looking at things like notes between recruiters and each other, notes between recruiters and talent, which gets into kind of intent and preference, which is much more powerful in trying to kind of map the likelihood of job transitions and spot talent that's a fit. And so that's a technology kind of why now that complements, I think, the market why now.
Undeniably, the convergence of AI and the manifestation of this talent gap will mean that there are so many roles that not only become duplicative, but actually become novel and new. And so, certainly, The wind turbine tax specialist. There will be many, many more of these, these roles that are hyper-niche, that are hyper-specialized. In other words, that, that AI cannot simply duplicate. So clearly, clearly tailwinds, clearly tailwinds for you.
All right. I'm hopping in here quick to provide some hiring statistics for the year of 2024 so far. So some sources for this Are the U.S. Bureau of Labor Statistics and recruiterflow.com. So job openings in the labor market as of May 2024, there were 8.1 million job openings in the U.S., which was down by 1.2 million compared to the previous year. The job openings rate was 4.9% in May. Hires were at a 5.8 million in May. And the quits rates were at 2.2% in May. Now, some challenges with this. 90% of hiring managers find it difficult to source skilled candidates. Therefore, AdeptID might be a solution for them. 52% of recruiters face challenges in hiring top choices before competitors, and the average cost per hire is approximately $4,700. It costs 3 to 4 times a position's salary to hire a new resource. Um, as far as candidate experience, 60% of job seekers do not finish an application process due to its length or complexity. 55% of candidates believe it should take 1 to 2 weeks to go from first interview to job offer. On average, it takes about 23 days for an interview process to finish. That's absolutely bonkers and absolutely wild.
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When you look at Alumni Ventures, a firm that has tentacles in all markets in the United States, that has a very diversified group of investors from all areas of American business, what asks do you have for a community like ours? What are the top-of-mind things on Fernando's plate where a firm like us can help?
Well, I think for starters, there's always just spreading the word that there is now technology available to identify talent based on potential and that all of us, and, you know, describing the kind of the broader AV community here, like as employers, as decision makers in business, you know, beyond kind of talking the talk of, oh, we're starting to look for talent based on potential because we're removing a degree requirement or because we're trying to kind of change our interview format. I think those are all noble first steps, but really we need to kind of follow through to making sure that the tech stack that we're using to identify and support talent is on the same page that we are and is data-driven and is kind of thinking about talent this way. And so I think that, you know, That's something that I think everyone can do independent of whether you're an AdeptID customer or an investor or not. We're always looking for those. So definitely, that keeps them on the list too. But our hope, and given some of the numbers that I shared earlier, if we're impacting 16 million workers in the United States, it's very likely that there are people who are listening to this podcast who either applied for a job where an AdeptID recommendation played a role or might be hiring using a platform that is using AdeptID. And we get a kick out of that, and hopefully that continues.
Well, Fernando, at one point, AdeptID was a whiteboard idea. It was nothing. And today, you now impact the lives of 6 million in— 16 million in the workforce. Thank you for that contribution, not just a tech contribution, but a civic contribution. And thank you very much for joining us today on The Tech Optimist.
Right on.
Thanks, Fernando.
Thank you, Pete.
Thanks again for tuning into The Tech Optimist. If you enjoyed this episode, we'd really appreciate it if you'd give us a rating on whichever podcast app you're using, and remember to subscribe to keep up with each episode. The Tech Optimist welcomes any questions, comments, or segment suggestions, so please email us at info@techoptimist.vc with any of those, and be sure to visit our website at av.vc. As always, keep building.
