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The Playbook With David Meltzer

Making Facial Recognition Affordable and Practical

The Playbook With David Meltzer

David Meltzer, Entrepreneur.com

Careers, Entrepreneurship, Business

4.91.9K Ratings

🗓️ 14 February 2026

⏱️ 13 minutes

🧾️ Download transcript

Summary

In today’s episode, I sit down with Michael Doherty, founder and CEO of Verifyfaces, to break down how facial recognition can be affordable, fast, and practical without relying on expensive AI. We talk about his shift to facial geometry, turning faces into mathematical data that runs on existing cameras while cutting costs by up to 90%. Michael explains how this approach improves search speed, reduces operator fatigue, and enables real-time alerts for schools, retailers, monitoring centers, and domestic violence prevention. We also cover rare use cases like biometric-triggered emergency alerts and how smarter architecture can prevent incidents before they escalate.

Transcript

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0:00.0

Welcome to Entrepreneurs to Playbook. I'm David Meltzer. And I'm here with Michael

0:03.3

Geordy. He is the CEO and founder of Verify Faces. It's a space that's filled with

0:09.4

competitors in those places because they don't have the technology in the ease of use

0:14.8

in order to facilitate, to make it easy to identify people and who they are in their backgrounds.

0:22.3

Michael, welcome to the Playbook.

0:25.1

Thank you very much, David. Pleasure to be here.

0:28.4

Well, let's talk about the issues concerning faces.

0:34.0

There's a lot of different people with a lot of different products

0:36.9

and a lot of different technologies to use facial recognition.

0:41.5

You are using verified faces specifically in a different way to help people identify problems before they happen and also to alert people of those problems.

0:55.9

Yes, certainly.

0:57.0

Well, first, in facial recognition, just about everybody uses AI.

1:02.3

Now, the AI is very good, but it's also very expensive to run because of its data requirement.

1:08.4

And in doing so, that really restricts the market. So you predominantly only

1:13.0

see facial recognition now at airports, you know, high-end businesses like casinos and government

1:19.6

applications. But in our line of business, we started this journey. We actually run a refuge. And there's a lot of vulnerable people in there.

1:29.8

So to bring facial recognition down to a price where it could actually start to help people

1:35.1

that are domestic violence or are targeted by dealers, we had to develop a system that could be

1:42.4

affordable, easily deployed and easily managed.

1:46.2

So we pivoted early and we moved away from AI and we moved to facial geometry.

1:51.7

So we actually turned the face into a mathematical equation, which turns out to be equally

1:58.1

if not as accurate, but it's easily deployed and it's 80 to 90% less in costs.

...

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