Hariharan Kolam, Findem CEO on AI Agents and the Future of Hiring

Grace Gong (0:02)

We are live. Hi, Hari. Welcome to Venture with Grace.

Hari Kolam (0:06)

Thank you, Grace, and thank you for having me.

Grace Gong (0:09)

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I want to start with, Hari, so I know that you started your career as, at this point, as a MTS, like member of the technical staff at different companies from IBM, some like a system before you founded your last company as a founder and CTO. Now, you're Findem's CEO. Why don't we start with, what were some core lessons that you've learned early on in your career shaped you into who you are today?

Hari Kolam (1:03)

Yeah.

One of the things that will stand out in my background is, I grew from a deeply technical ladder. As an entrepreneur and as a founder, one of my key important lesson here is, you need to stay true to your strengths on what are you rooted into as an expertise and build a team around that actually can complement the necessary ingredients in company building. As a founder, as a CEO, you get to choose whatever you want to choose, and pretty much every part of the job seems pretty attractive. But my core is as an engineer, and I tend to essentially invest in that a whole lot, and then build a team around that can then supplement the company building exercise.

Grace Gong (1:56)

I want to start with, I really like what you said about hiring people around you. Obviously, I met your whole team at this point, not the whole team, but the core team. They're like, oh, amazing. I want to start with, I feel like Findem does such a great job on finding the talent around you. Maybe we could talk about how did the idea started, and since you guys started with consolidating a ton of final activities from talents, teams, bring together the sourcing and all that stuff.

Maybe we will start from the founding journey of Findem, and what were some different pivot that you have done that help it become what it is today?

Hari Kolam (2:38)

Yeah, I mean, pretty much all my companies that I have worked with have very deep data and data related decisions tied to it, right?

One of the interesting things about the people space is it is a data infrastructure problem masquerading as a resume search or resume evaluation problem. And one of the important things to note when we started Findem was the belief that there's a better way to represent people because usually for the past century, possibly more, the way people were found is purely based on what they write about themselves. And the companies essentially attracted them by writing a job description that says what they want. So, usually people are decent at writing about themselves. But in many cases, what the employer looks for is not generally written down because hiring decisions or any people decisions are based on battle scars, are based on latent attributes, those intangibles that you desire in an ideal hire. I mean, we run a young startup. If I'm going to be looking for my next product manager or an engineer, I'd look for somebody who's come from a startup background. It's a very scrappy space where you do away with processes, but you essentially make progress by scrappiness, right? I mean, that is an attribute that is very attractive, right? Now, people don't write these things down because every company is a startup at some point of time. So, in order to essentially really look at an individual, that lived experiences or battle scars are more important and those essentially are not written down, those needs to be derived at the intersection of people, company and time, right? So, the foundation thesis of Findem was, let's think about digitizing a professional's career and create a labeling infrastructure so we can actually represent people well, right? It turned out to be a blessing in disguise because in today's day and age, we have the largest AI ready data set or the largest expert label data set on talent for about a billion people.

Now, it is AI ready. It has also used, it has been traditionally used by recruiters to find very hyper niche talent, right? If I'm looking for a sales leader who's seen a company from early stage to an exit, if I'm looking for that CFO who has come from a private equity background, right? These attributes are easier said than done and this notion of building labels and attributes enabled us to find the requisite talent. As a journey, we started out exposing this core infrastructure to recruiters as a sourcing platform.