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Lead With AI

How Ezra AI Is Making Interviews Smarter and Safer (with Ophir Samson)

31 Mar 2026

Transcription

Chapter 1: What is the main problem Ezra AI Labs aims to solve in recruiting?

0.031 - 13.38 Dr. Tamara Nall

Welcome back to Lead with AI. Today's conversation tackles one of the most consequential gates in modern society, hiring. Who gets seen, who gets filtered out, and who gets a real shot?

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14.001 - 30.257 Dr. Tamara Nall

I'm joined by Ophir Sampson, who is the founder and CEO of Ezra AI Labs, a company using AI-driven interviews to surface deeper signals, reduce noise, and bring more consistency and accountability into the hiring process.

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30.237 - 53.276 Dr. Tamara Nall

This episode isn't just about recruiting technology, it's about fairness, trust, and what it means to design AI that helps humans make better decisions, not faster decisions, as well as helping one of the underdogs get to the top. Let's get into it. Welcome to Lead with AI. I'm Dr. Tamara Nall.

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53.536 - 85.678 Dr. Tamara Nall

In each episode, we will take you behind the scenes with the visionary leaders shaping the future of AI across public and private sectors. Join us as we explore groundbreaking projects and innovations that are transforming industries and making a real impact on people's lives. Let's dive in. So hello, everyone. How are you? And welcome back to another episode of Lead with AI.

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Chapter 2: How does voice technology enhance the interview process?

86.138 - 103.817 Dr. Tamara Nall

I'm your host, Dr. Tamara Nall, or some people call me Dr. T. And it is a new year and so many different guests that we have lined up for this year, including the amazing Ophir Sampson, who is the founder and CEO of Ezra AI Labs. Hi, Ophir. How are you?

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103.857 - 105.739 Ophir Samson

Hey, Dr. T. Nice to meet you.

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106.259 - 130.36 Dr. Tamara Nall

Thank you. Nice to meet you, too. And we're so honored to have you. It's because of guests like you and those who are listening that has made us number one in technology on Apple podcast last year, as well as winning gold in the W3 for guests and interview podcast. So I'm really proud of it, but it would not be possible for you and other guests. So thank you for being here.

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130.34 - 136.965 Ophir Samson

Thank you so much for having me. Really, really excited for this conversation. I've been a long-time listener to your podcast.

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137.446 - 150.065 Dr. Tamara Nall

Thank you. Thank you, thank you, thank you. So even though it's a new year, we love to start with the number one question, which is tell us who you are at your core.

Chapter 3: What unique features does Ezra AI offer to recruiters?

150.566 - 161.848 Dr. Tamara Nall

I feel that every great AI product has to start with some vision, some need. So talk us through that. Take us through the journey of how you came up with Ezra AI Labs.

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162.014 - 185.946 Ophir Samson

Yeah, absolutely. So, um, so my, my father was an inventor, um, and every night he would be kind of awake, uh, coming up with different ideas and building prototypes and, manifesting his ideas into real products and putting them out into the world. And that environment surrounded me with, you know, a lot of creativity and science, cuz he was at the core.

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185.926 - 211.807 Ophir Samson

So the core, I'm a technologist who has had to make a lot of very kind of consequential decisions with very little information that's in the realm of a lot of kind of creative thinking for my career. whether it's been in autonomous vehicles or academic mathematics or hedge funds or social impact investing or even magic, because I'm a professional magician in my space.

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211.827 - 227.023 Ophir Samson

And throughout my career, I've hired lots of people. I've built teams and I've realized that that can be the most consequential decision you have on the impact of your life. The people I've hired, I've ended up spending more time with them than I have with my own wife.

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227.864 - 252.366 Ophir Samson

So, you know, I think, you know, being really thoughtful about that decision is so important for like how happy you're going to be on a day to day basis. So what really kind of pushed me over the edge with this idea was just seeing how much, how AI was just kind of making things so much harder in the problem of like selecting good candidates and, you know, who you bring onto the team.

252.346 - 281.188 Ophir Samson

and that kind of brought me over to voice because I believe that voice is the most kind of natural interface we have we speak more than we write we have been speaking for hundreds of thousands of years we've been typing for tens of years and so if you really want to get to understand someone you talk to them and so I wanted to kind of apply that to hiring so that we can make better hiring decisions so that we surround ourselves with kind of better people for us and

281.168 - 285.773 Ophir Samson

and generally lead happier, healthier, more fulfilling lives.

286.734 - 288.016 Dr. Tamara Nall

Wow, that's amazing.

Chapter 4: How does Ezra AI ensure fairness and eliminate bias in hiring?

288.056 - 304.915 Dr. Tamara Nall

So I'm going to jump because this is like creating my curiosity here. So let's jump to that and we'll come back to some of the other questions. So how does it work? Like if we were to open up the hood, look in the brain, how does it work? How does it use voice to figure out whether or not this candidate is a good one and a genuine at that?

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305.013 - 329.721 Ophir Samson

Yeah, absolutely. So the way it works is if you're a recruiter, you set up Ezra to do an interview for you. And it doesn't just work out of the box. You have to train it in the same way that you would train a real recruiter on your team. You tell it about the job description, which questions you wanted to ask. You talk to it. You literally have a voice. It interviews you.

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329.701 - 337.791 Ophir Samson

and your hiring managers and other people in the team to understand what is Dr. T really looking for in the ideal candidate for this role.

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Chapter 5: What success stories highlight the effectiveness of Ezra AI?

338.431 - 357.656 Ophir Samson

It takes a bunch of information about the company, culture documents, compensation documents. You can arm it with the much information you want. Then we'll go and talk to candidates. So when the candidate has a conversation with it, It will ask all the questions that you wanted it to ask, but then it will also ask detailed follow up questions.

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358.116 - 378.405 Ophir Samson

It's been trained on about 200 leading talent experts, so it knows how to ask detailed follow up questions, how to apply rubrics, how to apply frameworks, when to probe deeper, when to move on to the next question. There's a lot of kind of thinking into what makes a perfect interview and creates really great candidate experience.

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378.385 - 393.12 Ophir Samson

And so under the hood, it's a translation of a lot of cutting edge voice AI into the signals that you really care about as a recruiter to understand, is this candidate right for me or not?

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393.826 - 399.157 Dr. Tamara Nall

And it's only using voice, not like, am I looking up? Am I scratching my head? Am I doing just.

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399.878 - 421.199 Ophir Samson

No, because people, as I mentioned, I'm a magician in my spare time. And so I studied a lot how people act visually, you know, through the art of misdirection and things like that. And people just look in random places. They move their hands. It's very difficult to extract meaningful signal from that.

421.32 - 433.722 Ophir Samson

And there's also lots of regulatory compliance around that as well that we want to be mindful of. Because it's built in a way that eliminates bias. So we're very thoughtful about what to do.

433.702 - 435.305 Dr. Tamara Nall

Yeah, we'll get to that.

Chapter 6: How does Ezra AI identify genuine candidates amidst AI-generated resumes?

435.325 - 448.453 Dr. Tamara Nall

Well, that just shatters everything that I think because I sit across people and I'm like, who are they looking up? Are they scratching their neck? And you're telling me that that has nothing at all to do with like genuineness or lying or telling the truth.

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448.653 - 469.025 Ophir Samson

It's very, it's a very noisy signal. So there are, you know, misconceptions about when people are looking to the left, they're lying. I mean, that might be true if you look at it over millions of people on average, but to apply it to like this conversation this time, it's very risky.

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469.285 - 476.196 Dr. Tamara Nall

Wow. Okay. Now a follow up. So Ezra is conducting the interviews, not your recruiter.

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476.378 - 505.862 Ophir Samson

That's right. And one thing to say is we take a very different approach to many other companies and generally a lot of AI companies. Let's face it, a lot of AI companies, their core pitch is we're going to replace you. We're going to take jobs away and you can save money and we will take that money instead. That's not what we are about. We're actually not trying to eliminate any human interviews.

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505.842 - 528.95 Ophir Samson

So the interview, the companies that we work with, they're actually doing exactly the same number of interviews as they were before. However, the people that they're interviewing, the candidates they're interviewing are the ones which are more appropriate for the role. So for example, let's say... you advertise a job, you'll get a thousand people that apply overnight.

Chapter 7: What ethical considerations guide the development of Ezra AI?

529.35 - 553.872 Ophir Samson

And now because of AI, it's so easy for candidates to apply. They write an AI-generated resume, they send it off, and everyone looks amazing on paper because ChatGPT has written their resume. You've got a thousand AI-generated resumes in front of you. You know that somewhere in those thousand, there are 20 people who are really worth your time that you should be engaging with.

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553.852 - 573.008 Ophir Samson

They're needles in the haystack. How do you find those 20 needles? And so that's what Ezra does. So you'll end up having the same 20. You still end up doing 20 interviews like you did 20 interviews before. But those 20 people are those needles rather than, you know, hay in the haystack.

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573.41 - 580.737 Dr. Tamara Nall

Got it. So Ezra doesn't just start at the interview where you're listening to the voice. It helps screen people to even get to the interview.

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580.897 - 599.535 Ophir Samson

Exactly. Yeah. So it happens before you. If you're the recruiter, you would have Ezra have a conversation before. And that means that when you meet the candidate, you know that Ezra thinks they're a good fit.

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599.515 - 601.42 Dr. Tamara Nall

Got it. Yeah.

Chapter 8: What does the future of recruiting look like with AI integration?

601.44 - 615.195 Dr. Tamara Nall

Okay. I was thinking, okay, got it. So Ezra is screaming. And then you as the HR manager is still interviewing the same 20 that you would without Ezra, but just with, you know, you have those, those needles.

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615.513 - 630.511 Ophir Samson

Exactly. So before you interviewed basically 20 random people from the thousand. Now you're interviewing the 20 people that Ezra has determined, you know, are a really good fit because Ezra has spoken to all of the thousand people.

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630.571 - 631.654 Dr. Tamara Nall

Yes.

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631.674 - 632.155 Ophir Samson

Yeah.

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632.135 - 652.303 Dr. Tamara Nall

Awesome. Okay. Thank you for clarifying that. Sounds amazing. So tell us about like that holy smokes moment where a customer, a test user or somebody experienced Ezra and it blew their mind. They're like, whoa, this is amazing. This is more than I thought it ever would be.

652.486 - 674.716 Ophir Samson

Yeah, it was a customer of ours is hiring, uh, for a senior engineer for the, uh, for the front end development team. And they had 1200 applicants, um, over the course of two days. Normally what they do is they just look to the LinkedIn profiles and resumes and, and really what they, they, they have like two or three seconds per resume. So they were just looking for keywords, logos.

674.777 - 700.374 Ophir Samson

Did this person work at Meta or Google? Did they go to college? The person that that team ends up hiring is someone who if they were judged by their resume would never have gotten a look. He didn't go to college. He had no formal degree. He had not worked as a single company that anyone had ever heard of. And so if he was just judged on his resume would not have been accepted.

700.874 - 722.488 Ophir Samson

However, he did that conversation with Ezra, just like everyone else. And the recruiter saw that this candidate got a 3.8 out of four. And so that kind of piqued the interest. Then the recruiter had watched the video of the interview and read the answers. And they thought, wow, this person is really legit. They ended up meeting the person and that person ended up getting the job.

723.01 - 743.732 Ophir Samson

So this is someone who was better, was at the top of the, like the best candidate out of 1,200 candidates. But he would have been completely missed if he was just judged on his resume. So that was a kind of holy smokes. We would have missed this if it wasn't for Ezra.

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