Ratch.ai Hired 2 SDRs From School of SDR. Here’s How They’re Performing

Hi, Bhargav. How you doing, man?

I'm doing very well, Rahul. Hope you are as well.

Yes, I'm dandy. Thank you so much for asking. Bhargav, for everybody who's watching you for the first time, please tell us who you are. What do you do? What does your company do?

Sure. So I'm the founder of a company called Ratch.ai, R-A-T-C-H. It's short form for ratchet. It's a very technical term, very engineered term. So essentially what Ratch is, is it provides an end-to-end hiring service delivered as a software. Essentially, it's service as a software kind of a product. And we cater to, you know, typically product companies that are looking to scale multiple functions. And we take care of the entire process of hiring, which is all orchestrated inside a platform. Very briefly, that's what the company is. So I have about close to 20 years of experience. I would say professional experience started off doing a few corporate roles. And this is my third zero to one, I would say. In terms of founding companies and, you know, trying to scale them from a concept to a real business kind of a stage. So yeah, I'll just, I'll just stop there.

So tell us a little bit about your current company, Raj. What does it do?

So yeah, so Raj helps build decision intelligence through the process of hiring for any given entity. So we manage end-to-end hiring and deliver it as a service. Through a software, of course. The idea here is we manage the entire vertical, conduct all the assessments, how many ever rounds, understand the hiring manager's judgment and basically scale that judgment without them having to expense proportional amount of time and make sure that they're meeting the strongest of any given cohort of applicants for a role.

So you recently hired 2 SDRs from us. Tell us about your hiring process first. Like how does your hiring process look? Because that's very interesting to me.

So yeah, our hiring process, again, we use our own product completely for hiring for ourselves. In fact, the entire team has been built out except for the founders. So the way we go about is firstly, we put the intent written down of any given role. And through that, now we curate the rounds, the ideal amount of rounds required, and each round screens for what type of trait or skills, et cetera. And the idea here is look at it like a very tightened filter. Where we are able to filter out the non-relevant candidates through the funnel and making sure that we hire people with a lot more conviction than go with a little gut-driven sort of a decision-making process. And yeah, and the way we go about it is we typically involve multiple stakeholders in any given role. But for the SDR's role, of course, I kind of took the call myself because There was a real urgency about it. And of course, being a zero-to-one startup, didn't have the luxury of time and bandwidth to include other stakeholders. But yeah, typically this is the hiring process. Get the intent down. We curate the rounds. We orchestrate everything within the product. And then we get something called as a talent pack that has all the evidences stitched up from across the rounds that builds the narrative for the hire for any given candidate.

Wow. Okay. I think it was quite interesting because I know a lot of my students, interviewed at your company. Obviously only 2 got selected, probably the best of the lot. And I remember your AI interviewer was also able to catch when people were cheating.

Right.

How did you do that? How did you, how do you catch that? Because I'm sure I keep talking about this. I'm so sorry. I'll give you more context because I know there are so many companies. I'm forgetting those companies, Thule or something. I don't know. There were millions of companies which came up like a year later where they said, okay, we're going to help you cheat. When I opened my TikTok, when I opened my Instagram, there are so many companies which are just saying, oh, will help you cheat in the interviews. And I'm pretty sure that's what your solution does. You're like, hey, we will not let you cheat. Even if you do, we'll catch you. So how does that happen?

So there's a layered approach and a structure to this. So first, of course, is through the technology itself. So we embed a few mechanisms within that interview session, that AI interview session. So over there, we are looking for speech patterns in the sense we know when somebody is giving an introduction about themselves, of course, they're not reading out from another tool. We, you know, kind of recognize their standard speech pattern. And then we compare it against potential places where they've suddenly become very articulate, very precise. They're using certain AI SLOK-generated terms and it doesn't feel very natural. So that's one step. We look at all of this. Of course, we do it 2 ways. One is, of course, I have the transcription of the entire conversation. And we've recently also reinforced voice detection as well within that same session. Now I'm able to recognize voice patterns over there. Of course, this is a slightly more longer-term solution that gets fortified a little later on. And the second layer, of course, is we also have face detection. So very typically what happens is people are using another device and reading it out. It's close to the laptop or the main device that they're interviewing with. So over there, we look at the eye angle. So there's something called lean angle where we've deployed a certain algorithm and it's able to figure out if somebody is staring at a particular place for a significant amount of time or how frequently are they going there and is it matching to the question and answer sequence. So those are 2 main technological things that we have already in the tool. And of course, wherever it flags, so essentially my AI system will flag that, hey, there's potential cheating because it cannot clearly make it evidential that, hey, this is for sure cheating. So there is a little manual review and the whole point is it directs us to the exact timestamp of the interview where we need to review. So it kind of makes it easy as well. But of course, we make sure that there is a pair of human eyes and a human judgment involved in clearly indicating whether this person has cheated or not. So, so far we're doing it this way, but of course people get a lot more creative and we're looking to fortify that stack more.

Yeah. Makes sense. I actually did a video a couple of days ago on the same thing, like why not to use AI in the interview. And I did not know any of the stuff which you told me, but I think I was able to figure out this is exactly how it's happening. Because what I do is whenever I'm in a regular interview, like for example, with you, I also keep paying attention to this, like how frequently your eyes are moving. And I think the other part was, I think you and I probably discussed, or I don't know, I just figured out that that's the only way to figure it out. Because if I'm speaking right now, I have a lot of fillers and all of a sudden fillers goes away when you ask me a complicated question or ask me to describe a situation. That naturally is compared and that's how you catch it.

Okay.

Yeah, I think, but now you explained to me in a detailed way, so it's pretty good. All right, awesome. So these 2 people cleared I believe 2 AI interviews, and then of course, one full interview with you and your team. What did you see in these SDRs, which you probably did not see in other SDRs, or I'm sure you also had other applications coming from different people from around the world. Right.

So, so firstly, the interviews themselves, the assessments themselves were structured to, like I mentioned earlier, to filter out signals as such, weak, weak signals. So what we started off with was first was a Kind of like a take-home exercise where I'm giving a hypothetical scenario and they're going to articulate about how they're going to go about a cold outreach exercise. Over there, even if they've used AI, I don't mind because I'm able to understand their thought process because how you prompt to the AI, you know, will dictate what kind of results come out of it, right? So over there, I saw a distinct, I would say a muscle memory of sorts across most of your candidates where I found that there was a little better acumen outbound. I'm talking specifically outbound, a little acumen about the outbound, what that motion means. It felt like it was like second nature to all of them because most of them cleared those rounds, that particular round with good scores. Then in the next round was of course my AI agent, AI interviewer agent. Over there again, I made it very specific to my company's context, gave them certain fundamental questions and also gave some hypothetical scenarios. And there were also certain Objection handling sort of mini session as well within that session. So over there as well, I found about four odd people. I think about four people who cleared those rounds well. Of course, the rest as well were borderline. It was not bad performance, but they had some weaknesses compared to the others. But speaking specifically about the two people that I chose, one was of course Manikya, and with him it was fairly straightforward once. I'd interviewed him in person. I really liked the temperament and the fact that he had a lot of resilience for rejections, because when you're doing cold calls, there'll be lots and lots of rejections compared to yeses. Nos will be more. I mean, that's the nature of the game. And he was very objective about it, did not take it very personally. And also what really tipped the scale was he had shown me a recording of his, of one particular cold call to a slightly senior person somewhere. I think this was a large company. I can't remember the company name. Could be Pfizer, if I'm not mistaken. There, I really liked his skill of how he was able to hold that conversation with the person who wanted to hang up in the beginning of the call. And he managed to get her to book a meeting at the end of it, even though if it was a 2-minute call, it was very structured and measured in terms of how to keep the other person to hang on to it. You know, the cues he was giving, I felt was quite relevant. And I really liked that about him. The second person, of course, is Diya. Again, she was actually my third choice from your cohort. I had another person, you know, shortlisted above her, but nonetheless, I was very interested with Diya as well. Over there, what I really liked about her was, yes, the first 2 rounds, the performance was strong. And in the in-person round, I think she'd come very prepared, even though she did not know the domain.

Yeah.

I can get a little more specific there as well. So essentially I probed a little bit about GCCs, what a GCC is and how would Ratch be a fit and why are you recommending Ratch go and excavate that particular market segment. So even though she did not have a clear concept of what GCC is, she did not understand the full meaning of it. She'd come well prepared. She gave some examples. She had an approach towards how to go and enter that market and start the penetration aspect of it. But yes, there, there, and I also saw a propensity to learn. She definitely showcased a lot of learning mindset. And again, over there, what tipped the scale for me was her entire background. I probed for a circumstance where she was constantly getting rejected and, you know, she decided to pursue it nonetheless and not really give in or rather give up. So she narrated her story of her NCC program where she had to, you know, she got rejected for 3 consecutive years, I believe. And in the 4th year, she really took it upon herself and She was hell-bent upon clearing that and, you know, getting, you know, getting inducted into that NCC program. And I felt that story was very genuine and I really liked that aspect of it. And I think that that exact quality is what is being showcased here as well on the job.

Awesome. And I'm pretty sure there would be other people who may have applied directly to you outside School of SDR who may have also reached your final round. Anything in particular about these 2 people? Which made you sure, yeah, I really want them?

So I would say the energy, number one, the energy levels were very high. They seemed very genuine and genuinely hungry for opportunities.

How do you measure that? Because I'm sure everybody would have their own radar. How would you?

This typically happens in a face-to-face conversation where I kind of try to understand What they've been through throughout their career or throughout their journey need not be career. One is, of course, I was looking for specific type of age band. I wanted young folks and a lot of your, a lot of people from your cohort were in that bracket. Yes, there were exceptions. Of course, even Manikya was an exception. I ideally wanted somebody who's 26 and below who's had that 1-2 years of experience doing cold calls. So Diya fit that bracket. And coming back to your question was how do you identify hunger and energy? I think it's more, you understand face-to-face if somebody is faking it or they're being very real. And when they get very, when I ask them to articulate about a specific tough situation and they're able to articulate it well in the sense it's painting a picture in my head and they're just not objectively telling a one-sentence, two-sentence kind of an answer. And they're able to give some details both about the situation, what they were going through emotionally. I think those things are slightly harder to fake and That's how I'm able to filter out who's actually gone through rejections and they've come about it. And the hunger aspect comes out through that as well. You, when, when I probe for, hey, why are you taking this risk coming to a 0 to 1 when there is absolutely no guarantees whether the company will survive or not? They're a fairly legit answer for it. So they wanted to take risk. And I believe that was quite convincing to me.

I think yours is definitely one of the most interesting processes we have seen so far. We never had any other company. I don't think so. We haven't had any company who has Introduce AI interview interviewer. Is that what you call it? What do you call it? Sorry.

So it's called RACH. It means the same across all stages of the hiring process. So this is one of the agents, one avatar of RACH. It does voice interviews. Yeah. So it's called RACH. Basically that persona is RACH.

Okay. So interviewing well, I believe is one thing, Gargav, but once they actually joined, do you think that reality matched what you saw during the interview?

I think so to a very large extent. Yes. So. I can say confidently that, so there are a few fundamental qualities that, you know, I kind of judged on, and I think those are turning out to be true. Of course, they're just one month in, I would say a little over a month in. And so what I like about both of them is, so both of them are acting as a team. So they attack any given account together and they're able to amongst themselves decide Who's going to choose what account. And they have a certain kind of camaraderie and they have a certain kind of a playbook between themselves that, you know, I'm happy for them to, you know, run it their way. What matters is the outcome. Of course, the outcome is whether to get a yes or no for a meeting. So what I like about them is they're adaptable in the sense they came with a certain kind of know-how or an approach towards cold calling. I think both had inclination towards covering more calls in a day. But when I circumvented that and I said, hey, no, we will do a little thorough research. We'll filter out through our market intelligence. So I have a team called market intelligence. Their core thing is to weed out the irrelevant in any given market segment for any ICP. So we spend a lot more time there and make sure that our probability of outreach success is a lot more and tend to avoid this pray and pray sort of a strategy where I speak to a large volume of people to convert 2 out of, let's say, 300, 400 versus I would rather convert 2 out of 10 and spend more time. And that adaptable nature was there. They were quickly able to rejig their approach and go with the direction that I was giving them. And 2, of course, that bias to action for sure is very visible. They're very eager to contribute and they do cover a lot of ground. And 3, of course, they don't take rejection personally, which is I think the topmost trait required for an SDR specifically, when they don't take the rejection personally, I think they're able to evolve and improve their craft as well. And yeah, and yes, they're gelling well with the team and they're able to also make more friends and, you know, create a certain kind of an atmosphere and they have their own group as well created now. So I'm happy things are going.

Yeah. Yeah. I'm very happy too. I think Diya did reach out to me after she booked her first meeting. So yeah, she was very excited and I think you confirmed that too. So thank you. My last and final question, if a founder who's in the same stage as you is considering setting up an SDR team, what would you tell them about School of SDR, which should excite them about? Yeah, let me speak to Rahul.

No, certainly I would absolutely say it's worth the money, whatever is going to be the fee they're going to pay. I think the curation is quite good. I mean, I don't know if it's the curation, but at least there is a certain kind of muscle memory built. In terms of outbound motion, certain fundamentals are understood by these people, which makes it a faster ramp-up once you onboard these guys. So yeah, I would say that could be a mix of how you're curating your audience as well as your training program. The curriculum of it may be more practical than theoretical is my assumption.

I say this with no boasting. I don't think so anybody can match what we do because We are packing a lot of stuff, a lot of practical exercise. It's more practical. It's 80% now and more on cold calling than 20% only on the research and the understanding part. And that's what makes it interesting. A lot of people actually give up. I'm not going to lie to you. More than 40% of people give up because they're like, hey, I can't match the pace. I can't do all of these things. Some people also have a full-time job. I think Diya had a full-time job. So if she was able to manage this, I think The rest should be easy. So yeah, thank you so much, Marga. This was super helpful. I'm sure it's gonna inspire some more founders to, you know, probably take a look at School of SDR.

Absolutely. Absolutely. I'll just leave you with one thought. I mean, if your audience is going to listen, I think, yes, there is a lot of this AI SDR that's kind of ramping up everywhere. But I'm sure I've seen the difference myself. AI outreach versus human outreach is a world of a difference. And I think Human SDRs definitely is going to be the major pillar of any outbound motion going forward, especially in the AI world.