Identifying Talent Based on Potential

Hosted By Matt Watson

Full Scale

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Fernando Rodriguez-Villa

Today's Guest: Fernando Rodriguez-Villa

CEO and Co-founder - AdeptID

Boston, MA

Ep. #1089 - Identifying Talent Based on Potential

In today’s episode of Startup Hustle, let us assist you in identifying talent based on potential. Matt Watson is here with Fernando Rodriguez-Villa, CEO and co-founder of AdeptID—which is included in our top Boston Startup list. The execs talk about how talent tracking systems can help you, as an employer, find the right talent. And how tech can support applicants in getting connected with their ideal job.

Covered In This Episode

Tech has reached a level that helps employers like you screen applicants effectively. But do you know what talent tracking systems can do for you?

Matt and Fernando are also here to discuss the nitty-gritty details for you. Also, they dive into system integration, industry standard, APIs, and more.

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It’s time to learn more about identifying talent based on potential. Tune in to this Startup Hustle episode today.

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  • Fernando’s background and how he got into tech (01:34)
  • The challenges of transitioning from one job to another (06:24)
  • Data points to look at when screening applicants (13:16)
  • Gaming the system breeds mistrust (19:11)
  • Finding the talent that you don’t want to hire (20:45)
  • On interesting pathways turning into real-life opportunities (21:51)
  • The applicant tracking system that AdeptID integrates with (28:25)
  • About creating an API-driven business (29:45)
  • Convincing companies to integrate with AdeptID (32:07)
  • What is AdeptID’s go-to-marketing strategy? (35:25)
  • What’s the difference between a free API and a paid API? (37:33)
  • Fernando’s advice for entrepreneurs (41:05)

Key Quotes

Talent doesn’t trust the systems that they’re putting these resumes in. There’s no way that they’re going to encourage them to be inauthentic about what they are, who they are. And then it also discourages employers from understanding. So you end up with this kind of arms race of people making increasingly gamified resumes that might not be accurate.

– Fernando Rodriguez-Villa

It’s no one’s interest to stick around in a job that’s a bad fit. So we don’t want to have any barriers to finding a better job.

– Fernando Rodriguez-Villa

I think the problem on the other side, on the talent side, is most people just have no idea what kind of jobs even exist. They’re completely clueless.

– Matt Watson

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Rough Transcript

Following is an auto-generated text transcript of this episode. Apologies for any errors!

Matt Watson 00:00
And we’re back for another episode of the Startup Hustle. This is your host today, Matt Watson, excited to be joined by Fernando Rodriguez-Villa and his company, AdeptID. He’s the CEO and co-founder. We’re going to talk all about identifying talent today. They do some pretty cool stuff. And, you know, they have a lot of expertise in identifying talent, so it’s gonna be a fun conversation. Today’s episode of Startup Hustle is powered by Hiring software developers is difficult. Full Scale can help you build a software team quickly and affordably and has the platform to help you manage the team. Visit to learn more. Fernando, welcome to the show, man.

Fernando Rodriguez-Villa 00:34
Hi, Matt. How are you?

Matt Watson 00:36
You know, I’m so glad you’re here. Because at Full Scale, we are hiring a lot of people. And I’m gonna guess that your company can help us. I think we hired 14 people in January, and it’s a monthly thing. So tell us a little bit about your background and how you got into what you’re doing at AdeptID.

Fernando Rodriguez-Villa 00:54
Sure. So, you know, Matt, I have been thinking about machine learning and using data science to solve kind of complicated, real-world problems for most of my career. But I got started in finance. So I worked for an investment bank for a couple of years and have been kind of trying to repent ever since. I just caught a technology bug. We were working with some of these really impressive companies that were bringing new solutions to market that all kind of revolved around at the time. We were calling it big data. And I was particularly drawn to a company that was using data in the education world to help individuals have personalized learning experiences at scale. So you can effectively kind of recreate the experience of a one-on-one tutor but at the scale of millions of students at once. And so that was the kind of the first AI problem that I got really interested in. And so, you know, I left and joined that company as part of growing it internationally. So this was, you know, as someone in their late 20s, getting to go back and forth from Europe and India and South Africa and kind of grow a technology business to those geographies. That was a ton of fun as a young person, and also just kind of taught me a lot about how to kind of set up business models for success with new technologies and new spaces. I met a girl and moved with her to Boston when she was starting graduate school. And then joined the founding team of a company that was also applying AI. But, this time, to satellite imagery of crops. So, you know, different core data sets but similar sets of technologies. And we were looking at pictures of corn and soy from the states, from space.

Matt Watson 02:51
So, you know, I bet Kansas was in there somewhere.

Fernando Rodriguez-Villa 02:53
That’s what brought me to Kansas City, actually, the last time I was around. And so we did as we had these models that were able to predict early in a season how well corn and soy yields would do. And so we were able to share that technology with commodity traders, food companies set kind of folks up in Chicago, and Switzerland. And that was, you know, that was a pretty successful technology successful company. We ended up getting acquired by one of our customers a couple of years in, that gave me a bit of time and space to think about how, you know, where there were opportunities to use some of this technology that I had played a role in commercializing and other spaces but use it towards what felt like a really important societal challenge. And one of the things that I’ve always been really interested in is kind of how people move between jobs and how people find jobs that they find fulfilling and rewarding. And, and that’s kind of a, you know, in the fact that in this country, there are 10s of millions of folks who are underemployed or working in industries that are in structural decline, et cetera, is a social problem that that my co-founder, Brian and I found compelling. I think, you know, what’s really interesting to us is that, on the other hand, on the other end of the aisle, there are massive industries that are really struggling to find talent.

Matt Watson 04:29
And you mentioned it yourself, right? I think, you know, in the technology world, certainly in it and cybersecurity, even manufacturing.

Fernando Rodriguez-Villa 04:30
Oh my goodness, big time, right? Skilled trades, renewable energy, you know, allied health, the list goes on industries that are growing that have, you know, family-sustaining wages and career trajectories, but just are really struggling to find talent and the fact that on the one hand, you have a ton of underrecognized talent and on the other a ton of unmet demand. Felt like a matching problem. And those matching problems are the kinds of things Data Science has been able to solve really well in other verticals. And so yeah, I’ll pause there. And it’s a long story. What kind of that was the thing that motivated us to get started in this space.

Matt Watson 05:10
Yeah, so I help a company that does digital marketing-related stuff for home services for plumbing, HVAC, electrical, and stuff like that. And most of those companies really struggled to hire, but most of their employees make like 100 grand a year, you can be a plumber and stuff like make 100 grand a year, they get all these people going to college for all these degrees that are kind of stupid that you can’t get a job with. So there’s a whole big problem there.

Fernando Rodriguez-Villa 05:35
Well, and I think that was one of the observations was that you know, particularly in there are some something like 80 million working Americans who don’t have a four-year college degree. Right. So that’s actually the majority of our labor force hasn’t done that to a degree. And job transitions, you know, particularly between industries, right, so someone, you know, moving from, say, hospitality into technology, or hospitality into healthcare, cyber, etc., you know, those transitions are really hard to make. And, you know, part of that, and part of the problem that we were really interested in was that, you know, despite the fact that people might have picked up transferable skills, and doing something that seems different, you know, a lot of folks that are hiring will say, Oh, they haven’t had the right job yet, or they have, they don’t already have the kind of the right experience. And so we built our technology to try to look for transferable skills that someone might have picked up in a seemingly different job, right? For example, you know, very early on, we did some work with Boston Medical Center here in town, and they were struggling to find pharmacy technicians, right, you know, the really important job with a lot of demand pretty, really hard to hire for and, and we were able to look at their past hiring data and a set of kind of skills taxonomies that we were able to ingest that we got from a number of sources, and we were able to say, okay, you know, well turns out that a lot of the folks who’ve been successful as pharmacy techs for you, in the past, have been cashiers at Dunkin Donuts. And so, you know, what is it about that experience of handling a cashier at Dunkin Donuts early in the morning, Boston drivers, etc.

Matt Watson 07:19
That prepares you for the high-stakes environment that is. Well, that’s just because everybody works at Dunkin Donuts in Boston at some point in their life, right? Because there’s a Dunkin Donuts on every street.

Fernando Rodriguez-Villa 07:25
It turned out that the entire population of Boston, just everybody worked at Dunkin Donuts. Well, I think at this stage, we’ve all consumed enough Dunkin Donuts that I’m 98% Dunkin Donuts coffee right now, and 2% are running on Dunkin.

Matt Watson 07:36

Fernando Rodriguez-Villa 07:40
So those kinds of non-obvious transitions don’t like well, you know, in that, and that wouldn’t show up in a normal if you say like, Okay, well, what are you looking for in this pharmacy tech? And they’ll say, Oh, well, we want someone who’s already been a pharmacy tech. Well, it turns out that people who haven’t necessarily done that exact job before but have done other things that are similar, you know, have made, you know, successful transitions. Yeah, absolutely. Being able to use data to show that to people is huge. And I think some of what we’re trying to kind of empower.

Matt Watson 08:10
So is that how people AdeptID is? Is it larger companies that have a lot of employees, and you kind of look at all the people that have been hired before and then try to pattern match that? Is that the core of what you do? Or what else?

Fernando Rodriguez-Villa 08:24
Yeah, that’s a good question. And I think that’s kind of how we got started. And we’ve evolved a bit, right. So you know, initially it was, can we work directly with the employers to help them identify in their own data, the talent that might have been recognized, and we still do that, to some extent, what we’ve kind of what we’ve evolved into is matching technology that really anyone building a talent application can plug into the back end. So if you’re building a job board or you’re building an applicant tracking system, you can use our algorithms via API to surface candidates. Part of that is because, you know, I kept on running into other founders and the talented future of workspace or product leaders, etc, who, you know, might have been building, you know, a specific staffing solution for nurses or manufacturing, etc. And, you know, they’d say, Oh, we’d love to be able to do matching, like, what were you doing? But you know, we don’t have the data or we don’t have the data scientists, or we don’t have the strategic focus. Would there be a way to kind of plugin or license? I had enough of those conversations that it felt like, you know, where the kind of the big opportunity could be for us would be, you know, building our models and licensing them for others to use as they were kind of touching more of the market. So that’s most of how we work with folks is kind of indirectly through the products that use our models.

Matt Watson 09:56
So like at Full Scale, we get hundreds of job applicants a month. Sometimes over 1000. And so we could feed all those applicants into your system? And then how would we train it on what we like or don’t like? Or what works? Or who do we hire? Or like? How would that be? How would that work?

Fernando Rodriguez-Villa 10:14
So do you have an applicant tracking system? What? Which one do you use? If you don’t mind, give me built-in ourselves?

Matt Watson 10:19
Okay, built it ourselves even better?

Fernando Rodriguez-Villa 10:22
So have you built your own applicant tracking system, right? Or if you have your own database, then you just connect to our API, and we’d be able to train on the historical decisions that you’ve made, right? Who’s applied? Have you hired them or not? But then in real-time, you know, as applicants come in, you pass us parameters on, you know, who the individual is, what the target job is, and then we can return, you know, a score for you to use and a better ranking, we return okay, what are the transferable skills from this person’s past experience to what you’re looking for? And now it all runs by API, and we’ve got no public documentation on our website. Happy to kind of send that out and show notes or whatever for people to check out.

Matt Watson 11:05
Yeah, I think, you know, what you guys are doing is trying to find talent. So it may ultimately, do you give back? Is it about just scoring those? Or is it also about telling us, like, hey, you need to hire more people that went to this college, or they worked at this previous job before? Or? I mean, or is it both of those things?

Fernando Rodriguez-Villa 11:29
So we’d be able to do both. So like, you know, if you showed us an individual, you know, here’s Jane Smith, this is what we know about her, we’d be able to say, you know, okay, based on Jane’s experience, these are the skills that she’s picked up. And this is how that’s relevant to what you’re looking for. So that kind of individual level, scoring or highlighting of talent. But if you just said, Hey, we’re looking for this role, and you pin the API and say, like, you know, this is the geography we’re operating in. This is the role we’re trying to fill. We’d be able to tell you generically, okay, well, these are the other pools of talent that are interesting to you.

Matt Watson 12:07
So then do you have any way to then help them go find those people?

Fernando Rodriguez-Villa 12:11
That’s probably where you have to plug into kind of the right marketing provider or the right outreach thing. I think that’s a partnership that we’d love to build out more. When I’m training providers, right, we do some work with the training providers that are training, call center support or that are training pharmacy techs, wind turbine techs, a lot of kinds of folks in this segment.

Matt Watson 12:36
So we go through enough applicants and we interview enough people over the last five years that we definitely recognize some patterns, right? We know like, Okay, if people go to these a couple different colleges, like there’s a 90% chance 90% Chance they might be a genius, and we should just hire them, no questions asked. Right. But it’s only a couple colleges that end up on that list, right? Yeah. And then, you know, have worked at certain companies. It’s like, oh, they worked at a center or national cash register, or whatever. And it’s like, man, they do a really good job of hiring, they do a good job of training, giving people good experience. It’s transferable to us, right? Yeah. But it took us a long time to figure that out. Yeah, Bert, and it sounds like a product like yours would help. You know, instead of us using our gut instincts to make those decisions, you’d be able to, like, you know, more scientifically tell us that we were right.

Fernando Rodriguez-Villa 13:27
Well, yeah. And I think, you know, in addition to just being able to off the shelf, offer recommendations, like we have with a lot of our partners, trained models that are based on their data, right? So if you had your own, not just not just kind of observations or spidey senses, but you know, okay, here’s, here’s the data on, which schools people have gone to, and then, you know, their success here, you know, we’d be able to train a model that says, actually, this is the kind of the predictive importance of school x versus school y, or Accenture versus, you know, another, another firm.

Matt Watson 14:03
So what all kinds of data points do you guys look at? When you’re looking at these applicants? You know, besides education, they work at this company? Um, are you guys now natural language processing of all their job descriptions and keywords and all this kind of stuff? Like, how do you? What do you guys do there?

Fernando Rodriguez-Villa 14:19
Yeah, there’s certain Yeah, and I think there’s a, there is a kind of a long, there is a lineage of kind of matching solutions that have done that kind of keyword based etc. And we, you know, we do use some parsing. And so that’s a type of data that we train, train models on, I think, and actually the current moment around, you know, Jack GPT. And some of the potential of large language models, I think, has certainly kind of provoked a moment. And there’s, there are all sorts of interesting ways that we’re kind of already using some of those large language models to take a unstructured data or text that would show up either in a resume or in, you know, other writing samples or, you know, email answers to questions like that that type of information is is very rich, occasionally pretty noisy, but still has some value, particularly in segments of the workforce that, you know, might not have traditionally structured resume, which of which is true of a lot of folks and a lot of very talented folks that just kind of go under recognized. And so there are a lot of kinds of dark horses, if you will, out there that might not have, might not have that, that like perfect LinkedIn. But there are kinds of breadcrumbs suggesting that they’d be really successful.

Matt Watson 15:44
Yeah. Well, before we continue, I do remind everybody that finding expert software developers doesn’t have to be difficult, sounds like you’re gonna be able to help me do that. So that’s gonna be awesome, especially when you visit, where you can build a software team quickly and affordably. Use the Full Scale platform to define your technical needs, and see what developers are available today to join your team visit full to learn more. So one topic that I’ve heard a lot lately is, it feels like applicant tracking systems now are all very digital, and it doesn’t matter where you apply for a job, you’re going into a database somewhere. And there’s all this screening that happens, and you guys are a function of that screening. And almost it feels like there’s people out there that are talking about like, Okay, how do you beat the actual applicant tracking systems to actually get a job interview? Yeah, you know what I mean?

Fernando Rodriguez-Villa 16:35
Yeah, I mean, I think that is absolutely something that has made the talent market worse, right, the ATS is, we’ll have a set of filters there. Or we’ll have more kind of primitive keyword based matching that screens out a lot of applicants that might be a good fit and be encouraged as a kind of gaming of the system. And so, you know, the employers don’t end up trusting what comes through the filter. And so I think it’s, I think it’s more it’s more a question of, you know, how do we improve the filters, make them more inclusive, make them better at predicting, then than it is to kind of get rid of the filters altogether, though, I think, you know, maybe getting rid of the existing ones is a good start. I, you know, my co founder talks about this as a kind of evolving from the kind of pre Moneyball to the post Moneyball version of thinking about talent, where, you know, a lot of these filters just kind of are based on some some pretty rudimentary kind of search and retrieval. Right. So okay, I’ve been told to look for thing X and thingy that looks kind of like our notion of what a successful applicant would be, you know, maybe they, they’ve had this exact job title before they’ve come from this exact place. And we really want to move to treating this as more of a prediction problem. Right? So okay, what what, you know, can we take real examples of people who’ve been successful, have people who are associated with wins and figure out okay, well, what are the real metrics that are predictive? So I don’t know, you know, any of the baseball equivalent is moving from you know, batting average and RBIs. to thinking about no on base percentage and, and VR or any other kind of war. Yeah, how many baseball nerds are among the listeners here? Well,

Matt Watson 18:31
it definitely feels like if I was helping somebody do the resume today, I’d be like, Okay, well, what do we have to put on here that the applicant tracking system is going to pick up and like, what format? Do we put it in? Like, is there a file format? Is there a layout? Is there a like, how do you know what descriptions what keywords what buzzwords like? It definitely feels like you have to almost prepare to game the system just a little bit.

Fernando Rodriguez-Villa 18:54
One, it breeds a lot of mistrust, right? You know, the talent doesn’t trust the systems that they’re putting these resumes in, there’s no way that they’re going to kind of encourage them to be inauthentic about what they are, who they are. And then it also discourages the employers from understanding, and so you end up with this kind of arms race of people making increasingly kind of gamified resumes that might not be accurate. And then, you know, the ATS systems trying to one up them by coming up with better filters and then and so it’s not really in anyone’s interest.

Matt Watson 19:29
Well, I feel like the other part of this is companies are increasingly trying to take less and less risk in their hiring, right? Like they’re putting people through like five levels of job interviews and projects and all these different things and, and I really blame a lot of the laws on this because they make it so hard to fire people. That’s why I would hire people like I’m not going to hire people if I can’t fire them, right. Like, they think that these laws protect the labor because they can’t lose their job, but I almost feel like it’s the other way, because as an employer, it’s like, I don’t want to hire anybody if I know I can’t fire them later.

Fernando Rodriguez-Villa 20:05
Yeah. Well, and that’s and I mean, there’s a whole lot of issues that are kind of adjacent to that one, you know, I spent a chunk of my career working in Europe. And so my frame of reference on protection is perhaps a bit different than the states is certainly a little bit more range of motion. But I think you know, what, the problem we’re really trying to figure out is, you know, how do you find the right talent that you don’t want to buy? Right? Sure. And so how do you get that relationship up? At the beginning? And then how do you kind of keep the feedback loop between what and what work that an individual is going to be inspired by and do well, and then you know who an employer is gonna want to keep around. So it’s no, it’s no one’s interest to stick around in a job, that’s a bad fit. So we don’t want to we don’t want to have any barriers to finding a better job.

Matt Watson 20:57
So through the AI models and stuff that you build, are there any examples of, like, weird little things that you guys found that, you know, were better employees, like weird things in these models?

Fernando Rodriguez-Villa 21:11
Yeah, I mean, you know, we talked a bit about the Dunkin Donuts cashiers, though, that does count for a lot of the Boston population. You know, we there’s some kind of interesting pathways that we’ve we’ve remarked on between, like service unit operators, on on oil rigs and wind turbine techs, you know, those are two jobs that require a similar tendency towards working with machinery, etc, and are on different kinds of ends of the energy kind of growth and decline spectrum. And so, you know, there’s certainly some encouraging pathways there, also, from the agricultural world into the renewable energy world, I think the wind power role, and also there seem to be some interesting pathways there that, that that that we’ve observed. You know, I think one of the other interesting ones is between a lot of it, kind of junior level it roles and cybersecurity is an interesting pathway. And obviously, the cybersecurity industry is booming. Those jobs pay really well. I think it’s one of the only categories that, you know, CIOs this year are spending more in than they were last year. Right. That’s kind of security, security budget. So there are a couple of kind of interesting pathways that we’re starting to see in the data, that, that our partners are starting to try to kind of turn into turn into real life, you know, I think, to your earlier point around, players feeling kind of anxious or nervous to make hires, you know, there are certain industries that are having such a hard time finding talent, that they’re, they’re more willing to try things, right. Those are kind of our, those are our people, because it takes a bit of a bet to start trusting technology to to kind of show you people that might not look like what you would have expected. And in, you know, certain pockets, certain industries, you know, people are willing to give it a shot.

Matt Watson 23:11
Well, it sounds like the best use case for what you’re, what you’re doing is people that are potentially switching careers, or are there adjacent opportunities, it’s like, you know, it’s easier for like, Oh, I’m hiring a software developer. And yeah, they’ve done a lot of software development, it’s pretty straightforward. It sounds like the goal that you guys are really trying to help with or people that are like, Okay, I’m hiring for this type of manufacturing, or whatever. And they did some other totally different jobs before, we’ve shown that these other weird, random, totally different jobs really translate to this job.

Fernando Rodriguez-Villa 23:43
I think those are the transitions that were the most exciting. We’re just you know, it’s not to say that people can’t kind of make progress within a given field. And that will help them identify where that’s possible. I think, you know, one of the big challenges in the world that we’re really trying to work on is making it easier for people to make those trends right, with more interesting transitions or not more interesting, but certainly more more ambitious, or less obvious transitions.

Matt Watson 24:10
Well, I think the problem on the other side, on the talent side, yeah, is most people just have no idea what kind of jobs even exist. They’re completely clueless, right? They’re like, Okay, I know, people are doctors and lawyers and astronauts, and whatever my mom and dad does, and Uncle Joe does. And I know people obviously work at McDonald’s and Walmart. I have no idea what people do? No clue.

Fernando Rodriguez-Villa 24:31
Yeah, no. And I think, you know, some of the folks using our models are, you know, career navigation applications, right? So right job centers that allow a person to say, Hey, this is what I’ve been doing. And, you know, I’m looking for a job and the application will tell them, Hey, these are different potential pathways for you. And so that kind of career navigation use case is one I think, we’re really excited about because it helps kind of demystify some of these jobs and I think, you know, part of the job there isn’t just part of the responsibility of, of the career navigator isn’t necessarily to say the name of a job, right? Because like what you know, being told that you should be a medical coder means very little Right? Like, well, what is a medical coder doing right? alone even know how to get that job? Yeah, like, what’s the idea? But so I think there’s a bit of a burden to say, Okay, well, you know, this is what a medical coder gets paid. These are the skills that are associated with them. These are people like you, right? Who you know, who people like you with your background, who have been able to transition in and these are the types of courses that they took to get there.

Matt Watson 25:35
That’s fine that, okay, if you worked as an assistant, and an accounting firm, you’d be perfect at medical billing or whatever.

Fernando Rodriguez-Villa 25:43
Yeah, well, that’s and I think that’s, I think that kind of an impostor syndrome is like a term that gets thrown around. But that does help, right? And being able to say, like, you know, cuz, cuz, because part of it is, you know, you hear you hear about certain types of jobs, and you think, Well, that can’t be me, like, I don’t know, I don’t like computers. But like, okay, what are you spending, you know, seven hours a day, on your phone doing something else, like, hey, probably be able to do this job. Right. Like, they’re kind of ways to demystify some of that for folks.

Matt Watson 26:13
I know, for like one of my sisters, she would be that person that’s terrified to think that she could do any job, like she has no competence to do any of those things. But she could probably do a lot of them. And I think there’s, there’s a lot of people that are that way,

Fernando Rodriguez-Villa 26:26
ya know, and I think it’s a, I think, you know, particularly jobs that require working with, you know, computers or working with certain forms of technology or programming like there. There are a ton of folks who can do them. And I think, part of theirs, and this isn’t the kind of thing that AdeptIDX can do alone, right, like you actually need, you know, coordination with the right vocational training institutions and the right, you know, public sector players and the right employers who will take a bet on, you know, not obvious candidates, so it actually needs to be it needs to be a coordinated effort.

Matt Watson 27:09
So, is your guys’ product, your company and the services that you do? Is it almost entirely an API? Yeah, like, we are API first, I would say, you know, we have occasionally built dashboards for folks too but those are, you know, pretty rudimentary things that call the call or API.

Fernando Rodriguez-Villa 27:17
You know, we see really important really awesome businesses out there, like Twilio, like Stripe have been able to, you know, create a lot of impact, mostly behind the scenes. And I think that’s kind of what we’re what we’re aspiring for.

Matt Watson 27:45
So for those who aren’t as familiar with an applicant tracking system, what are some examples of applicant tracking systems out there that you guys integrate with?

Fernando Rodriguez-Villa 27:54
Yes, you know, a greenhouse is a big one. Workday has a very large applicant tracking system; the lever is a big one, ADP, these are all kinds of big names probably going to hit and miss out on so but we’ve actually we use, we’re able to integrate with anything over 40. ATS is at this point.

Matt Watson 28:13
Wow. Okay. So they’re not quite the Full Scale one yet. We’ll have to work on that.

Fernando Rodriguez-Villa 28:18
I know, we gotta wait. Yeah, so we can figure that one out. But, um,

Matt Watson 28:23
but no, we have a lot of companies so you’re integrating these 40? But then do you have a lot of companies that just integrate directly as well, separately?

Fernando Rodriguez-Villa 28:30
As employers? Not not not as not that many? We do that, we’ve done some, but it usually takes a pretty, you know, the company has to have built a pretty interesting tech stack to directly consume an API from someone like us, right? Most companies will rather use workday or would rather use ADP. And so then we have to integrate with that one. Right? Well, for what we can do pretty well, what we’ve made very easy as a company exporting data from their ATS. Right, so that data out has gotten a lot more straightforward.

Matt Watson 29:05
So a lot of people listen and probably never, never thought of or heard of creating a company that is API driven only, right. So those who are listening, you know, basically, you don’t sign up and use your product, you don’t log into it, right? It’s only really consumed through these other API’s, right, like, you have to use workday or something like that. And your guys’ product is like an add on to that and an additional service to that. And so, you know, tell, I guess, tell the listeners a little more about like, what it’s like to have a business like that, right? Because you’re heavily dependent on your partners, potentially, right? Like, you go to somebody like Full Scale and like, Hey, you could sign up, but you’re like, you don’t use an applicant tracking system that we work with. So I’m sorry, rolling. Don’t tell us about that.

Fernando Rodriguez-Villa 29:53
Yeah, I mean, you know, it’s the type of business that wouldn’t have been possible 10 or 15 years ago. Right, I think like they’re there, and still have trade offs, right? On the one hand, you’re right. You know, in order for someone to access our technology, they need to use a tool that uses our technology. Yeah. Or they need to be good enough at coding that they can directly code our API. And you know, we have our docs publicly. And so all you need is an off key, and you’d be able to use your code or like yourself would be able to get up and running and, you know, an hour or two, I’m sure on your own. And so and so, you know, it does, it does have some implications for who we sell to and how we distribute. You know, the flip side is, I think the end user adoption has a much higher upside this way. A lot of folks don’t want another thing to log into that Sure. The challenge is, is like, you know, there are all sorts of really interesting, you know, HR tech offerings that, you know, do a good job selling to the head of HR, or the CIO of a company, and then the company’s like, great, we sign this big contract, we now use, you know, service X, and no one logs in, no one uses it. And so, I think what we’re trying to kind of solve is that problem of like, well, how do we kind of get embedded in the workflows and meet people where they are? So logging into workday? Because they have to check their payroll because they have to do their whatever? Well, that’s where they should be getting their insights through navigation.

Matt Watson 31:27
But a couple years ago, was that like, a giant hurdle for you? Right? You’re like, how do I convince a workday to integrate with us?

Fernando Rodriguez-Villa 31:34
Oh, it’s still it’s I mean, you know, it’s still, it still means that there’s a certain type of partner for us that, you know, is tech savvy enough to work with an API that has interest in our capabilities. And those are the folks we work with, but you know, as a relatively small company, right. I think, you know, there’s a saying around like, you know, strategy is, when you start saying no, right, like, like, right, we have to kind of know who we are and who we’re not. And, and right now, you know, that means that we get to work with a certain type of company, the good news is that that group of companies is big and growing and bigger than it was five years ago. And so, as AdeptID, it continues to grow, you know, hopefully the market continues to, to grow it and we’re a part.

Matt Watson 32:24
So does this follow some certain standards for what you guys do? Or did you have to go to somebody like Workday? And ADP, and like, there’s like a totally one off API that they’ve never done before? Or was there kind of an industry standard for this thing?

Fernando Rodriguez-Villa 32:38
Yeah, you know, and actually, there’s a really amazing, I’m gonna give some free ads out for this other company, there’s this really amazing company called merge dot dev that has done a lot of the work of going to the different ATS and HRIS systems, integrated with them. So that we can mostly just work through merging and nice, there you go, we get to that kind of one too many, because that’s a part of the plumbing that, you know, the nightmare, we could spend all our day on that we could go and steal they are. And there are other folks in the ecosystem that have solved that problem for us, which is, you know, I guess, as a macro point, right? I think the way that the kind of the talent stack is going right, the ecosystem is going, it’s going to be more of that have different solutions talking to each other in the back end, in the same way that if you look at the FinTech stack, right, or the ad tech stack, versus where it was 15 years ago, there are a ton of services that are all kind of invisible to the end consumer, but that are all really important parts of the puzzle.

Matt Watson 33:37
So you were able to integrate with merge Dev, and then that enabled you to get into 20-30. Different platforms that allow us to do mostly a couple of them, we’ve integrated directly, because we have a relationship with the provider.

Fernando Rodriguez-Villa 33:44
With that software company, that’s always, you know, makes things a little bit easier. But you know, this allows us to cover, you know, 90% of the market.

Matt Watson 33:57
That’s awesome. I mean, and that’s huge. I mean, for somebody who’s listening, like, hey, I can create an API to do this weird, special thing, you know, and then if you can integrate into something like this, it gives you access. Because otherwise, if you had to go to 40 different providers, and like, hey, I need you to do this custom API, they’re all going to be like, no, every one.

Fernando Rodriguez-Villa 34:15
We’ve got to find we got to find ways around that. I mean, so much of the entrepreneurial journey is like figuring out who else has solved the part of the problem that’s getting you in the way of what you know. I think we want to be the very best in the world at algorithms that identify talent, right?

Matt Watson 34:35
Yeah. Not integrating with 40.

Fernando Rodriguez-Villa 34:38
ATS systems, the plumbing between ATS systems is a hard problem. Yeah, other people can solve that. And if they have done great, we can pay them.

Matt Watson 34:45
So now that you’ve had this integration, were they able to help be like a co-marketing go to market strategy or any of that, like, are you able to work out deals with ADP or workday or any of these kinds of people to help promote you.

Fernando Rodriguez-Villa 34:59
Well, so for some of the folks that we’ve done, so those folks have app stores. And you know, we haven’t because we don’t have a front end, we haven’t really gotten involved in the App Store game. There are folks that we’ve integrated with on the back end that use us for matching. Right? So it’s a two way kind of street. And they’re, they’re using the algorithms. And those guys are a little different than the one. Yeah.

Matt Watson 35:24
Yeah, I just wonder if they help. If they help be like reseller partners for you, like they’re part of your go to market strategy, then?

Fernando Rodriguez-Villa 35:30
They haven’t. So our partners don’t have a couple of partners that market, you know, that include us as ingredient branding in the way that they go to market and they are employers, but our business model is based on the number of placements that we’re touching. And so, you know, as their products grow and help individuals get into jobs, then we get to monetize more critically. So it’s more I mean, we’ve tried as much as possible for the business model to share value as it’s being created.

Matt Watson 36:03
So you know, if you have a job overnight, yeah, so is your business model based on consumption. So it’s based on volume?

Fernando Rodriguez-Villa 36:10
Well, it’s actually based on employment outcomes. So in this change, we initially had a very kind of standard flat SAS VI. And then we went straight to this kind of outcomes based one, which is the number of placements or recommendations that kind of lead to placements is how we get paid. So we kind of skip through the volume of like, paying by number of API calls, which is how other API businesses do it and it works well for Stripe or Twilio or some of the other folks, you know, what we’re, we’re still early enough that we want to encourage people to use the API as much as possible to get certain outcomes, right?

Matt Watson 36:53
And so, like, and so a good example of this right now is Twitter, right? Because their API’s were free. And now they’re like, oh, no, you’re gonna have to pay for him. And it’s like the same thing. You’re like, well, if you want more people to use Twitter, then you would make them free. But at the same time, it’s like, people should be getting some kind of value out of using these apis. And it makes sense that they would pay for him. Yeah, if you want more adoption, ultimately, you want them to be free.

Fernando Rodriguez-Villa 37:15
Yeah. So you know, maybe the maybe the, maybe the more value sharing way to think about the Twitter API is, you know, when when you use the Twitter API to show a tweet, and someone clicks on it, or someone gets traffic, you get traffic because of it, then you pay Twitter, you know, like, what, when does someone benefit, that’s when you want to, which is tough, because it means that, you know, we we would get paid a little later in the game right? Then upfront, or and we have a little less control over how much we get paid in. But I think in the long run, it gives us a bigger upside, because we’re able to, you know, grow as the impact grows.

Matt Watson 37:51
It’s based on the scale, right? So if you have a little client or a big client, it just kind of naturally scales, which is great. Well, I appreciate you telling us more about the API business and stuff, it’s a different kind of business model. Most listeners are probably not very familiar with and, and, but it’s definitely a business model that exists. And my last company stack, like we weren’t an API based business directly, but we were building was consumption oriented, kind of like this, like the more data that we had. And what’s cool is there are companies like yours that are 100% API based, like you don’t even log into your software. The only way you can even use it is as an API. And actually one of the other examples, this one of the companies that I do some work with. We use API for things like geolocation data, like addressing data and cities and states and zip codes and things like that. And the same kind of thing. It’s like it’s just an API, the only way you can use this thing is the API. And there’s software out there. There are companies out there like yours that do this. And it’s cool.

Fernando Rodriguez-Villa 38:51
Yeah, I mean, and actually, I think I’m sure a lot of the listeners are part of API products without knowing, right? Yeah. If you got an if you use your credit card online to buy something, the Stripe was probably part of that, right? If you got a text message from credit card processing, for example, that you know, if you got a text message from the restaurant, you want to know, Twilio probably sent it to you. And that’s why I think people in the tech community know who Stripe is. You know who Twilio is with people outside of them. Don’t, despite the fact that we’ve all probably a good part of them as part of those businesses, as well.

Matt Watson 39:27
And if you’re building any kind of software today, anybody who’s listening is building any kind of software. Odds are you’re using a lot of APIs, like you just described, right?

Fernando Rodriguez-Villa 39:42
Like, there’s a lot of different building blocks now for when you go to build software, like using all these different things, all these different APIs and stuff, so API’s all the way down, all the way down.

Matt Watson 39:45
Well, if you need to hire software engineers, testers are leaders. Full Scale can help us have the people in the platform to help you build and manage a team of experts. When you visit All you need to do is answer a few questions and let our platform match you up to our full vet and highly experienced team of software engineers, testers, and leaders. I don’t know if I’d quite call it AI, but it’s a pretty good algorithm. Full Scale specializes in building long-term teams that work only for you to learn more when you visit Well, thank you so much for being on the show today. As we round out the show today, I was wondering if you have any other final suggestions or tips out there for entrepreneurs, maybe those who are looking to hire people or just general? You know, just being an entrepreneur?

Fernando Rodriguez-Villa 40:25
Yeah, I mean, you know, we are growing the team. And so, if there are some really excellent Senior Software engineers out there or account executives that are willing to hustle and do some great selling to get our technology out there, we’d love to meet you. We’d love to see if we can enlist you to help the AdeptID mission.

Matt Watson 40:47
So that’s remote or just in Boston.

Fernando Rodriguez-Villa 40:49
You know, we’re based in Boston, but we have remote employees. And if you’re, if you’re comfortable working remotely and you’re accountable, and you’re doing an awesome job, then you could be wherever.

Matt Watson 40:59
All right. All right. Well, again, this is Fernando Rodriguez-Villa, and his company adapts ID, which is just adapt dash Check them out. And maybe you need to plug their API into your applicant tracking system, and you guys use this product to help you out.

Fernando Rodriguez-Villa 41:18
So that’d be a lot of fun. All right. Well, Matt, thanks so much for having me. This was great.

Matt Watson 41:22
All right. Thank you.