Reinventing Recruiting: SeekOut’s Anoop Gupta on the Rise of Agentic AI
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Focus on outcomes. Focus not on the hype. Because everybody's put AI in their marketing materials. Get to the success stories. Shout those out from the groups. That focus on outcomes is really important. Like in the recruiting space, we have a lot of companies, you know, who would talk about, we are AI, we are agentic AI.

and all they've done is maybe an LLM and give a natural language query and something comes out. That is not the end solution. Part of the vertical AI is looking at the whole workflow and process that results in the outcomes. Welcome to this episode of Founded and Funded. I'm Soma, a Managing Director here at Medrana, and I'm joined by Anup Gupta, the Co-Founder and CEO of SeekOut.

SeekOut is a company that has been redefining how organizations hire and manage talent. SeekOut has been an AI first company from day one, but with the rise of LLMs and more recently, agentic AI,

Today I'm going to get a chance to dig in with Anoop about how Agentik AI is transforming hiring and how Seekout has evolved from an AI first company to including Seekout Spot which is their newest Agentik AI solution. Seekout reduces the time when you start hiring for a particular position to when you can get a slate of qualified candidates from 45 days to three days.

Also, we'll be hearing a little bit about Anoop's journey, both how he went through from academia to startups to large company and then now to a startup. So tune in for this episode, which is going to be a fascinating conversation about how Seacode is using agentic AI and is navigating through the landscape and delivering amazing amounts of value to customers. You have a truly an eclectic background.

Starting with like, you know, initially academic, then a startup, then a large company, and now back to a startup.

Why don't you introduce yourself a little bit to the audience and also talk about what you do at Seacode and what Seacode does. So I'm Anoop. I'm a geek and an entrepreneur. I got my PhD from Carnegie Mellon in computer science. I was in the faculty of computer science at Stanford. And then did my first startup in '95. Be one of the first companies doing streaming media.

Okay. When the modems were still 56K modems and it was just wonderful time from Stanford. That company got acquired by Microsoft in '97. Now, SeekOut is a talent business. We focus on helping companies build winning teams and fill the talent gaps.

We look at talent very holistically from external talent, internal talent, how to retain, grow, recruit people. We are used by some of the top brands. We have over 700 customers, who is who in tech, in defense, in pharma. So we feel really privileged that they used us as their recruiting and talent solution.

Now to remind people

As much as we think AI has been around for the last 100 years kind of thing, it was really five years since the transformer revolution, so to speak, happened and the large language more came into existence. But even before all that happened, you were sort of thinking about SeekOut as an AI-first company. You're sort of going from, hey, how can AI help you? To, hey, how can AI do it for you? So some people refer to it as agentic AI or what have you.

Tell us a little bit about like, you know, what got you started on AI right from day one and how you evolved with the sort of the changes in technology and the innovation that's happening at a pretty fast pace.

If you look at, there's a lot of data. You got to understand the data. The data is noisy. Even if you think about, you went to University of Pennsylvania, do you say Wharton, Pennsylvania? If you're doing diversity classifiers, anything you do. The early AI was in data cleansing and data combining and classifiers and everything and how do you build the most amazing search engine in the world.

So that is where we started. Then as the time has gone along, especially the second thing was, oh, LLMs are there. Can you just give it a job description? I can build searches for you. But it has fundamentally changed with Agentic AI. The thing is that recruiting in some sense, and actually any kind of talent job, whether you're thinking succession planning, anything,

is a very predictable thing. You look at a job description, you talk to the hiring manager to understand the needs, you go and search a large landscape, you go and evaluate hundreds of thousands of people, you reach out in very hyper-personalized ways, and you do that, and that magic happens.

agentic AI is very good. Vertical AI is very good. And that's where we can bring the time from a job description to initial candidates you're interviewing from 30, 45 days to three days. So that is the magic. It's a transformational jump. But I've heard you consistently tell me this, Anup, for a while now, companies that don't take a step back and reimagine

how they are going after recruiting talent and managing talent. They're going to be left behind. Why do you think now is the time for companies to embrace agentic AI solutions to reimagine how they could go about talent acquisition? And what is the urgency here? Yeah. So, Soma, the world is changing. Every industry is changing. Every business is changing. People are refining their strategies and saying, we got to adopt AI or we got to do this.

Think differently otherwise. Now, all of this evolving, changing business strategy, you've got to have a talent strategy. You've got to say, do I have the right people in the seat? Now, the speed of change has become and the speed at which the companies need to change has increased. So in this

kind of world where things are changing, it becomes urgent for the talent organizations to say, what am I going to do differently to deliver talent quickly?

That's high quality, so the right people are in the right seat. One more angle just quickly I would add to that is there is a lot of pressure on all organizations. That is AI is coming. How are you becoming more effective, more efficient? And that is another pressure that people are feeling on how to do more with less. You guys have recently launched SQL Spot.

I'm sort of super excited about that. In fact, I'm proud to say in this forum that we were probably one of the earliest customers of NoSQL Spot and we are happy customers. Yes.

But tell me a little bit about that. Tell me how you sort of came up with that, because there is a growing trend here where people are talking about not just software as service, but service as software with AI playing a key role kind of thing. So tell me a little bit about the genesis of Seekout Spot and what does it do for companies and organizations and talent leaders?

So when we start with the business leader and what they care about is the right hires, you know, with speed and quality that is there. And the magic of AI agents is outcomes as the delivery thing and not here is a tool that your people have to use. So the fundamental thing that from a business model is the focus and outcomes. Now there is a lot of flexibility because it's a combination of people

and the AI agents that are happening. So we have support a lot of different models. We will deliver you a hire and that is pricing costs associated with it. We can say we will augment the sources that you have. So maybe you need fewer sources or they're getting a lot of hard work is getting done. Or when the demand is changing,

We can come and help you. So there's a lot of flexibility of business models, but they're all outcome-based, you know, that we deliver for them. To dig in a little bit, what does the recruiting task look like? How do you engage with the talent? That is interesting. And my, our recruiter sellers, by the time they've done the 10th message, their eyeballs dry out, fall off and roll across the table. It is amazing.

It is crazy the amount of hard work and crazy work that you have to do as a recruiter and with Seek Out Spot.

The recruiters focus on actually the tasks they love, talking to the hiring managers, talking to the humans, selling to the candidates what needs to be done. And Spot takes over everything in the middle, delivering your results faster and with higher quality.

That's awesome. Sounds truly magical, but help us walk through the shift here. Takeout Spot, in my mind, is a classic example of services software. Tell me, what is the business model changes here, and why is it the right thing for your customers? So the business model change is we deliver hires.

or we deliver you strong candidates for this thing. So that is the outcome. Eventually what the talent leader and the business leader are looking for is

Did you get me a hire? Are they great? Are they the right fit? They don't care when it's taking six weeks. You know, the average for a technical hire by Ashby is 83 days for a hire. And for, you know, non-technical, it's around 63. That's a long time. And that's just the median. And many things take longer.

And so this can be so much faster and better. Let's talk about our own example here for a second, right? As you know, Madan, I wanted to hire a data scientist a few months ago. And whenever we think about hiring a position, my mental model is, you know, hey, you know, I'll be happy if we can hire somebody in the next 90 days. 180 days, maybe, but 90 days would be like, I'll be thrilled kind of thing.

And this hire, the data scientist hire, from start to finish, I think took like less than four weeks for us. I was like amazed at the sort of the speed and the quality of the candidates that we saw through the process kind of thing. It all happened like, you know, amazingly well for us. And thankfully, thank you. Thank you to you and to Seacode Spot. We made that hire and that person is on board for the last few months and we are thrilled with them so far. So,

Tell me, you mentioned earlier, like go from 30 days or 45 days to three days, right? So basically what we can do in this technology is from the kickoff meeting with a hiring manager to actually the initial candidates you're interviewing on the fourth day.

So that is the magic. Now, the hiring actually, making the offer takes a little bit of time. So, you know, we have had Discord, which is getting amazing results. We had a startup named Shape.ai, which is getting hires within three weeks with the initial count, and they're amazed at it. So if you look at the quotes on our website, you know, we have Discord, 1Password, HP, you know, Shaped, Madrona. So,

Even though it's early, we are seeing real proofs that there is magic in here. That's awesome. Yeah. You know, the other thing that I've heard you say, Anoop, when I was over to your place for the SKO, you mentioned that, hey, with C-Code Spot, we can deliver a 5 to 10x productivity. Yes. For recruiters.

or talent acquisition people kind of thing, right? Talk to me a little bit about that. Basically, here is how the recruiting process works. The recruiter talks to the hiring manager, understands the role. Then they kind of build a mental model of what needs to do, do some search, come back, do some search, send some messages, and that cycle goes on before. So in SeekOut,

On the first day, after you talk to the hiring manager, you have this success rubric. You have explored automatically thousands of candidates. You've evaluated each one of them and we give you a spider graph and how they're doing across each of the rubric elements. And you have sent out messages.

That thing, I'm saying five to 10x, that takes a long time for a recruiter. And that time is being compressed to the benefit of the recruiter and the customer. Because I'll tell you, so we have specialized in this service. Of course, there's technology, but we also have recruiters who operate this technology because there's some tasks that humans do best.

They're the happiest, most energized recruiters because I'm doing what I love and I'm delivering results quickly. So, you know, it is just pretty amazing how everyone is happier. The business leaders, the talent leader, the recruiter. So it's pretty exciting to us. That is great. You know, we've been talking about like, you know, human in the loop for a while now. Yes. Okay.

And with something like Seek Out Spot, what you're really telling organizations is like, hey, recruiters are highly valuable. Let them focus on things that they need to focus on. And I'm going to give you agentic AI solution or like, you know, sort of agents that is going to work in conjunction with your talent people to be able to get things done better, faster, all that fun stuff. Okay.

So this notion of hybrid model where you have agents working with human beings, that seems like a great model to sort of drive forward as it relates to recruiting and talent acquisition, right? If I'm a recruiter today or a talent acquisition sort of professional, okay, and I see the world of agentic AI, you could argue like, you know, it's going to disrupt my world.

Or you could say it's going to like, you know, reimagine what is possible and get me to do what I need to do much, much, much better, 10x better, whatever it is. What should I sort of take away from this as a recruiter or a talent acquisition person? And how should I be prepared for this wave of innovation to come? So here's the way. Do what is human and only humans can do and become the best at it.

So one is it means, you know, when you talk to the hiring manager, how can you be really advisor? Ask hard questions. Do you really mean this? Do you really want this? What is this person going to do? So if you feel confident, expert, and good at that, that is one side of it. The second is when you're talking to a candidate,

Right? How do you sell? How do you say what is inspiring? How do you say what are you going to do? Why is this a great company for you or not? So I think those are the skills you have to become very good at. A lot of the messy middle, which is critical and important, AI agents will do a great job for you. That's cool. That's a good way to frame and think about it kind of thing. Okay? I always tell this, Anup, to every founder or every startup, okay?

In the history of this world, there isn't a single company which has always had a smooth journey. There are sort of good days, there are amazing days, there are okay days, there are lousy days, and everything in between kind of thing, right? Yes. And in your journey over the last, say, seven years or so, right, you've gone through some amazing highs, some not so great lows, and everything in between.

How did you and your co-founder, Arvind, how did you guys sort of navigate through this? And are there any takeaways or learnings or ahas that you would like to share that will be valuable for other founders? Every founder goes through this. So, you know, we had an early phase of it where we was in hyper growth, exponential growth.

And then, you know, the economic malaise, the market change. And then we had went through some flat portions and now we are on a path to hyper growth again. So what are the things that you need to do? I think the most important thing is continuously watching a product market bed.

When the market changed, the environment changed, what was needed changed, it took us a little while to say, how do we do? Because market always wins. You can have a great team and the market is this thing you're not going to succeed. You have a lousy team, but you're aligned with the market, you're going to win. So one key message is watch for market fit.

Just because you have market fit once doesn't mean you're maintaining, you know, it is there forever to adapt. The other is to have a sense of confidence and always iterating and experimenting and keeping calm so your organization comes along with you.

Okay, that, you know, bad stage shouldn't ruin, though you have to be, you know, very conscious about managing your expenses and how you are doing. And so I want to point to one advice, which was, you know, maybe a thing for the times. When we were raising a Series B, Series C, we had actually not spent any money that we had raised.

And you said, go ahead and raise it anyway. You know, it's good times. And that helped us too. So, you know, we have never had to be in a desperate situation. Not that we...

Don't want to be scrappy, want to be conscious. And so that has given us a comfort and a cushion. And that was very wise advice to us. Thank you. But there are two elements to that. One is you want to raise money when you don't need to raise money. That's always the best time to do it. The second time is what you said is one of the reasons I was excited about us raising that money was because I've seen how you and Arvind have been very scrappy.

So I wasn't worried about like, you know, hey, if there is a little more money than what you need today, would bad behavior set in in terms of spending, right? So it doesn't matter how much money is there in the bank or not in the bank. And I think as entrepreneurs, as founders, as what I call efficient stewards of capital, you have to always be thoughtful about that.

And I say this, right? Hey, your increase in investment should warrant a return on that investment. Yes. And if you're confident about that, go do that. If not, you have to be really thoughtful. Yes. And so to me, like, you know, I'm so glad whenever, you know, you raised your CDC and that has helped you tide through, like, you know, the last year or so.

to put yourself back in a hyper growth mode. And so that's fantastic. But going hand in hand with raising is also a more thoughtful deployment of capital. I totally agree. You know, we always feel like it's our own money. We have a responsibility. And so are there any lessons from your own journey? Because I truly believe that you guys were like, you know, AI first right from day one, as I said, well before the transformers and like, you know, large language models came into existence.

Any guidance or advice that you would give to founders today when people are thinking about like, hey, I want to sort of ride the AI wave. I want to truly be a first company. What should they do or what should they not do? So my advice to founders and actually to the customers that we have our prospects is focus on outcomes, focus not on the hype.

If I was advising this thing, and because everybody's put AI in their marketing materials, I say, look for the outcomes. What are the outcomes you're delivering? Get to the success stories. Shout those out from the groups. That focus on outcomes is really important. Like in the recruiting space, we have a lot of companies, you know, who would talk about, we are AI, we are gigantic AI. And

And, you know, all they have done is maybe an LLM and, you know, give a natural language query and something comes out. That is not the end solution. Part of the vertical AI is looking at the whole workflow and process that results in the outcomes. So what I would say is don't use it as a buzzword. Genuinely create value for people.

your customers, and that is the thing to do. And there is a lot of power in what's coming, but focus on the customer's problems and outcomes. When people are thinking about AI, and I agree with you completely that focus on the outcome and not the activity alone kind of thing. Yes. How important is what I call a data moat?

Do I need to necessarily have either what I call proprietary data or a data moat if I'm an AI first company or I don't need to have that? I think there's different kinds of data. So a lot of data is available. Everybody has data.

So one is the experience mode. So as you work with clients and you get the proprietary data from the customer and the client and how you integrate it and how easily you can do that. So it becomes not your data mode and some base data that you have.

You know, and for our one example would be in recruiting. It's not just external data. How do you integrate with the applicant tracking systems and the data that customers have or their internal employee data? And how do you bring that or how do you integrate with specialized, you know, resources and partners, whether it's health care and nursing data? So.

I think the data mode comes from delivering outcomes and the learnings, and that learnings and the data becomes also a mode. And if I sort of take you at face value, you are really telling this from the rooftop that like, hey, every sort of investor should be talking to their portfolio company about like, what is your talent acquisition strategy? How are you reimagining in this world of agentic AI? I think building a recruiting org too early

It's not good because your demand is going to fluctuate. The quality and the people that you need will fluctuate. These specialized roles. What I would say is what a startup should have is probably one recruiting manager and recruiting coordinator that they have, where the interface to the hiring managers and doing and scheduling interviews and calendaring. Work with somebody like SeekOut.

Because in a startups, the right hires are really important. The cost of a bad hire is so much more than just, you know, here is what I did. So because if you can get high quality hires,

Two weeks, three weeks, that's make a difference to your business outcome. So I would invite, you know, it'll sound a little bit selfish as I am saying it, you know, come and check us out. Talk to us. I think it can make a big difference. I want to sort of underscore one point that you just made.

For every organization, every company, this is true. Yes. But it is even more true for a startup because you've got so finite asset of resources kind of thing. And every right hire can be a true force multiplier. Yes. Okay? Yes. And so, and conversely, every...

A wrong hire can set you on a wrong path for a long time. So I sort of truly believe in like, hey, it's extremely important for startups, particularly the early stages of the company to ensure that everybody sort of goes through this way. You do make it, nobody bats thousands of kind of thing. There's always hiring mistakes, but you want to minimize that and truly understand that

Every great hire is going to be a true force multiplier for your organization, for your company. Yes. Yes. It is so important. But from your vantage point, particularly as a hiring manager, okay, what do you think the biggest hiring mistakes that companies today are making? One is...

Company strategies change, the precise thing. So hiring strong, fungible engineers, marketers who can change as your strategy changes is really important. So, you know, that is the thing you need to do. The second thing is,

We have found is attitude is really important. People who understand the ambiguity, who can take the punches, roll with the punches, you know, adapt and adjust and are there and get shit done. Those things are also super critical in the hires that you make.

So now the other side of the audience is like, you know, usually founders, either sort of, you know, existing founders or new founders or people who are thinking that in the next six to 12 months they want to be founders. What is your sort of, you know, message to founders? My message to founders

Founders actually is. One is before you hire, try and do the job yourself in some of the cases. So, you know, I did a lot of sales. I've never done sales before. And I became an expert because you don't know how to hire a sales person. That was one thing on the talent side that I did. Then there were many cases where I had no expertise. You know, let's say on a sales leader CRO. I leveraged

People at Matrona said, would you interview this person for me? So you want to leverage your connections and contacts who are experts in that so that you can get a good sense of what it needs to be. So my recommendation is to the people who are thinking to be founders that the initial team is super critical.

Become familiar yourself before you jump into hiring all those people at a level of detail so that you know what is the right thing you need. Because the salesperson you need for one startup versus another varies a lot.

You have to say what is your selling motion, who is you need, and understand deeply. And then second, leverage your friends to do that. And then leverage the right people who can feed you that talent. How can I get in touch with you, Anup, if I'm a founder or investor and want to learn more?

Okay, it's simple. My email is anoop at seekout.com. You can find me on LinkedIn, connect with me, and we'll come and love to talk to you and show you, right? Because that's when you can, seeing is believing. You know, everybody talks so much. I'm just such a passionate thinker that seeing is believing. Come and see, come and experience, and we would love to partner with you.

As we come to an end in this episode, Anup, I want to congratulate you on sort of, you know, pushing the boundaries and pushing the envelope on what AI can do for talent acquisition for organizations of all sizes and in all industries. Is there a final word that you would want to say to people, whether they are in a smaller environment like a startup or a bigger environment like an enterprise, as to what they should do about talent management and talent acquisition as they look ahead?

Agentic AI for Recruiting is here and now. And I would say experiment with it. This is the time. Be early before the change is thrust upon you. Be the lean forward leader, experimenting and adapting and flowing with the transformation versus being hit by it, you know, when somebody comes and says, you're too late.

the world is changing and it is changing in amazing, wonderful ways. That is, don't get stuck in the old world to the extent you can avoid that and look broadly on what needs to be done. So especially for the large enterprises, the transformation is going to be very huge.

And even for a small company. So we have my final word, contact us. We'll show you what we can do for you as you explore all of the different options that are out there so that, you know, you're getting the right hires and kicking the ball out of the field.

First of all, even before I wrap this up here, thank you for allowing me to partner with you and Arvind over the last seven years or so. It's been just a fabulous journey. So many learnings and so much successes. For all the progress we've made, I think we are still in early stages and there is so much more that we can do and looking forward to that. Thank you so much for joining us here today. And thanks to everybody for listening. And we'll see you again soon.

Thank you, Soma. It has been wonderful to have you as a partner in our journey.