March 30, 2026

Craig Brenner - CEO and Co-Tounder of icognio, a technology company built exclusively for law firms

Craig Brenner - CEO and Co-Tounder of icognio, a technology company built exclusively for law firms
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Craig Brenner - CEO and co-founder of icognio - talks about their legal technology company delivering secure, on-premises AI solutions built exclusively for law firms.
With decades of experience across technology, leadership, and enterprise systems, Craig has helped build and scale multiple companies serving high-trust, high-stakes environments. He founded icognio to address the security, governance, and adoption gaps he saw emerging as law firms rushed to adopt cloud-based AI tools.

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The topics and opinions expressed in the following show are

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solely those of the hosts and their guests, and not

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be directed to those show hosts. Thank you for choosing

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W FOURCY Radio.

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Churchill said, those who fail to learn from history are

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condemned to repeat it. Kevin Helen n believes that certainly

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applies to business. Welcome to Winning Business Radio here at

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W four cy Radio. That's W four cy dot com

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and now your host, Kevin.

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Helen Thanks everybody for joining in again today. I'm Kevin

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Hallanan and welcome back to Winning Business TV and radio

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on W four cy dot com. We are streaming live

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on talkfortv dot com. That's the number four, and of

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course we're on Facebook and that's at Winning Business Radio.

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And after the live show, we're available wherever you get

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your podcast content, YouTube by heart Radio, Spotify, Apple, etc.

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The mission of Winning Business radio and TV, as regular

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viewers and listeners know, is to offer insights and advice

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to help people avoid the mistakes of others, right to

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learn best practices. Those are the how tos, the what tows,

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the what not tos. I want you to be challenged

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and hopefully to be inspired by the successes of others.

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Who are those others consultants, coaches, advisors, authors, founders and

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owners and entrepreneurs, people with expertise. But you know, virtually

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every successful person I've ever had a chance to has

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had some form of failure in their lives and careers.

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So while we all have to get our knee skinned

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once in a while, I'm driven to keep those scrapes

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from needing major surgery. Let's endeavor to learn from history

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so we don't repeat it. I've spent the better part

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of my career equipping businesses to grow from solopreneurs to

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small and medium sized companies all the way up to

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the Fortune fifty. I've seen some of those companies win

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and to varying degrees, I've seen some fail, and I've

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had the opportunity to rub elbows with some of the

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highest performing people around and some who probably should have

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found other professions. In my own businesses, I've had lots

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of success, but some failures too, and I like to

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think I've learned a lot. So yeah, you're going to

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hear from me, but mostly I want to hear from

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I want you to hear from guests. And today my

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guest is Craig Brenner, CEO and co founder of Icognio,

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a legal technology company built exclusively for law firms. Here's

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his bio. Craig Brenner is the CEO and co founder

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of Icognio, a legal technology company delivering secure on premise

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AI solutions. With decades of experience across technology leadership and

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enterprise systems, Craig is helped build and scale multiple companies

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serving high trust, high stakes environments. He founded Icognio to

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address the security, governance, and adoption gaps he saw emerging

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his law firms rushed to adopt cloud based based AI tools.

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He's also the owner of Brenner Brothers and has held

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senior technology and technology leadership positions in well known technology companies.

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He holds a bachelor's in Science and business from Eastern

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Nazarene College in Quinsey, mass where he's the captain of

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the cross country team and an MBA with the concentration

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in e Business from the University of Phoenix, and he

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completed Worcester Polytechnic Institute's Technology Leadership Program. He resides in

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the Nashville, Tennessee metro area. He has three grown kids,

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Colin who's twenty seven, Cameron who's twenty five, and Cassidy

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who's twenty two. And he's got three grandkids. And don't

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forget he's got two Standard Poodles, Mindy Loo and Big

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Wayne Craig. Welcome to Winning Business Radio and TV. Thank

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you very much, Kevin, My pleasure. Glad you could be here.

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So tell us a little bit about your background. You

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grew up in Middletown, New York. Tell folks where that

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is and what it was like to grow up there.

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Yeah, Middletown, New York is out an hour and a

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half north of metropolitan New York City in the Catskills region.

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It's in an area a lot of people would know

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of a Poughkeepsie, New York on the Hudson Valley region.

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Yeah, beautiful up there.

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It's a country area, So I kind of grew up

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in the country even though when people here in New York,

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they always think.

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Of big buildings, and you don't have that New York

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city accent. I don't have that Boston, New Jerseys. My

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parents are from Connecticut. So so were you influenced by

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parents or mentors when choosing a direction or career, either

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you know, directly or indirectly.

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Well, I think my biggest mentor was probably my father.

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My father was the incurable entrepreneur. I remember him coming

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home and always having a new idea about, you know,

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what kind of business he could.

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Do or how he could make money.

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Yeah.

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He owned his own milk route when a milk route

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was a thing.

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Yeah, And he would drag my my one of my

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five older brothers out there and two in the morning

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to distribute milk around the neighborhoods.

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And so.

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He he really gave me that concept that if you

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have a great idea, you can go and you can

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build it to have confidence in yourself.

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And my brothers were also.

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All their own business owners as a result of that leadership,

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I'd say my dad was my biggest influence. And my mom,

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obviously she had six kids, so she showed me how

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to manage adversity.

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She gets the award for having all boys too, one girl,

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one girl. If you guys play sports growing.

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Up, yeah, I was on the cross country team and

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the track team. My brothers had pretty much all runners

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in my family. And then I branched out a little

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bit into cycling and triathlon and ultra marathoning.

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Oh very cool. I'd like to hear about that another time.

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But I when I got turned forty, I wanted to

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get in, you know, better shape. I wasn't in terrible shape,

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but I wasn't in shape either, And that's when I

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found I like to run. I didn't like it before that,

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and I've always been active, but you know, I considered

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running that's what you do when you get ready for football,

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you know, right.

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It was painful, you know.

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So, Yes, my coach used to say that it's not

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fun to run. It's fun to have run.

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That's true. That's true.

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You feel great and it's fun to win too when

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you do win. So what made you choose Eastern Nazarene.

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I know that campus, really small campus. I know it

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well down in Quincy.

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Yeah.

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Eastern Nazarene College, which was later changed to Eastern College,

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was a part of the Nazarene Church, extension of the

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Nazrine Church. They have colleges all over the country and

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Quincy was just one of their campuses. My two boys

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went to Treveca in the Nashville region, which is how

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I ended up the Nashville region visited them. So Treveca

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is another one of the Nazarene college You have Point

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Loma out in California, so they have quite an interesting

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college network related to and associated with the Church of

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the Nazarene International. But I think in the last few

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years the Quincy campus has closed down.

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Yeah, it has, unfortunately, but really good education. I know

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a bunch of kids that have gone there. My kids

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went to a Christian school right in Weymouth and saw

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a lot of their front not a lot, but a

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number of their friends went there. And I know adults

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that have gone there. Had a really good friend got

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his as an adult, got his construction certificate, four year degree,

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you know, his construction degree and certificate there. So really

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good school. And then when and why did you decide

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to get an MBA.

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I decided to get an MBA because I realized that

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there was more I wanted to learn about business. There

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were weaknesses. You know, we all have our strengths and

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our weaknesses. I had some weak areas that I wanted

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to shore up when relating to business, some on the

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financial side, some on the you know, accounting side, some

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on the strategy side, some.

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On the leadership side.

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And so I thought that that was a good way

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for me to, you know, just go go one level

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deeper in terms of how businesses operate, how they run,

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what's important and and go ahead and get that. So

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that's why I went from from my MBA. I did

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it remote remotely through university. And some people might say, oh, well,

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you know, you weren't really on a campus, But getting

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your MBA remotely has its own set of challenges, and

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you have to use technology. Technology is your conduit kind

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of to the professor, and so it brings in a

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whole different sense of community because you're interacting with students

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from all over the country and in some cases.

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All over the world.

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I can imagine, yeah, which you know you sometimes do

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on certain local campuses, but you know, they're all distributed,

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and the concept of teamwork in an online environment changes

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and becomes much more important because that's your lifeline too

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to learning. So University Phoenix. They have a nice teamwork program.

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They break the classes up into teams, project teams, and

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you know, you have some strong team members and you

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know you kind of follow them, and then you have

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some weak team members and you kind of bring them along.

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All these business all these are business concepts, you know. Yeah,

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So I did enjoy that program. It was very it

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was very good for me.

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What was your takeaway from wp i's Techology Leadership Program.

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Well, the WPI Technology Leadership Program was the name is

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kind of and I'll say deceiving, but doesn't hit the mark.

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The WPI Leadership Training Program is a people management program

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which is focused on leading technology leaders. So how to

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lead those groups that are in the technology realm as

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a CIO or a CTO or even a CEO, and

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how to keep motivation, how to keep innovation moving, and

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how to incent and how to know how to lead.

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So it was an outstanding program. It was right on

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the campus there now in Worster. I think it was

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a remote campus. I forget the exact town, but beautiful campus.

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I was in that class, rather small cohort of about

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twenty folks, but all pretty high performing technology leaders in

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their own companies, and so they really pushed you. I

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mean that's what I that's what I liked about it. Yeah,

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there were moments where you were kind.

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Of, wow, this is a this is a push.

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You know, they'd give you some high pressure team assignments

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that were competitive, and that was kind of a core

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of that curriculum was break up into teams, solve this problem,

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come back and tell all these other really smart people

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how you're going to solve it and do it better

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than them. So you know, that's the pressure cooker that

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is innovation. That's how innovation happens.

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Love to hear that, all right, take us through. You know,

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I don't want to spend a lot of time, but

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I want to I want to get a sense. I

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always like audiences to get the sense of kind of

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how you came up. So just like a quick lesson

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from each of these channel sales manager at NTT Data

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Sure I was.

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I was selling dial up back in the day. Not

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to roll back the film that far. I realized that,

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you know, high speed internet access was something that was

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needed by businesses, and so NTT acquired a company I

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worked for called Verio in downtown Boston.

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I was a channel manager there.

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I later rolled that program out to NFL cities twelve

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cities in the United States other channel managers, and it

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was very successful. I enjoyed selling, you know, I really

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enjoyed the process of some.

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It's the dark side.

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00:12:38.720 --> 00:12:41.879
Well, you know, selling, selling is not the dark side. No,

226
00:12:43.159 --> 00:12:45.679
there's a certain feeling you only get when you close business.

227
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And you know, that's right, that's right, that's really great feeling.

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That's a great feeling.

229
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So that's how I got interested in really and deep

230
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into technology. And I just have an affinity for it.

231
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I always was skilled out in school. So I went

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on to work for a few different startups and then

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I went on to found a few different startups, some

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which made it and some which did not.

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That's the game. That is the game.

236
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Yeah, And so it is for sting when you start

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something and you have a passion for something and it

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doesn't quite go the way you had planned. But I

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would say that you know, you've heard this before many

240
00:13:27.399 --> 00:13:30.559
people have. You really do learn more from your failures

241
00:13:30.600 --> 00:13:31.960
than you do from your successes.

242
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That's a fact, yep, you know.

243
00:13:34.120 --> 00:13:36.960
And you have to have some scars, you have to

244
00:13:36.960 --> 00:13:39.120
be willing to take risks a lot of people are

245
00:13:39.120 --> 00:13:43.519
not that kind of a personality. My personality is is

246
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that I'm not afraid to take the risks. So some

247
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of them, some of the startups I got funded by

248
00:13:50.399 --> 00:13:51.000
other folks.

249
00:13:52.080 --> 00:13:52.559
Some of the.

250
00:13:52.519 --> 00:13:59.159
Startups I fund funded myself. And these were all technology startups,

251
00:13:59.679 --> 00:14:04.399
and some of them were funded by venture capitalists and

252
00:14:04.480 --> 00:14:08.360
were already kind of in motion. And one of those

253
00:14:08.559 --> 00:14:12.919
was Kiva Systems, which was a robotics company. Uh started

254
00:14:12.919 --> 00:14:17.519
out in Wooburn and later relocated to North Redding. I

255
00:14:17.559 --> 00:14:21.799
was there seven years. We were acquired by Amazon. And

256
00:14:21.879 --> 00:14:25.240
that's another great feeling when you are even just a

257
00:14:25.279 --> 00:14:29.440
part of a team that succeeds and gets acquired.

258
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By a larger company.

259
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Yeah, it's a it's a one of a kind feeling

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that it's the high five moment. You know, we did it,

261
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We achieved our goal, We returned our investment to our

262
00:14:40.759 --> 00:14:44.679
investors and then some and uh, you know that that

263
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it's addicting.

264
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I like winning, but I particularly like winning financially. So

265
00:14:50.679 --> 00:14:52.000
that's a good one. All Right, We're going to take

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our first break right here, Craig, everybody, We'll be back

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with Craig Brenner in just about one minute.

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You're listening to Winning Business Radio with Kevin Helene on

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And now back to Winning Business Radio with Kevin helenan

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00:16:33.679 --> 00:16:37.480
presenting exciting topics and expert guests with one goal in

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mind to help you succeed in business. Here once again

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is Kevin Helene.

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We are back with Craig brann oer CEO and co

299
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founder of Icognio. So then you got into some tech,

300
00:16:57.600 --> 00:17:01.919
some let's see some fractional CIO work, and some consulting work.

301
00:17:01.919 --> 00:17:02.519
Talk about that.

302
00:17:04.319 --> 00:17:07.359
Yeah, I wanted to try my hand at consulting. I

303
00:17:07.400 --> 00:17:10.960
had done some government consulting. I was outsourced part time

304
00:17:11.079 --> 00:17:16.960
CIO for the city of Watertown, Massachusetts. I had consulted

305
00:17:17.000 --> 00:17:22.920
for some K through twelve school districts, including Plymouth and

306
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also Shrewsbury. So in the City of Shrewsbury and also

307
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Watertown K through twelve.

308
00:17:32.680 --> 00:17:33.640
So I enjoyed.

309
00:17:33.680 --> 00:17:37.519
I enjoyed the the low hanging fruit of being able

310
00:17:37.559 --> 00:17:41.680
to go in to, let's say, something that wasn't necessarily

311
00:17:41.720 --> 00:17:48.400
a company which ran very efficiently and make improvements that were,

312
00:17:48.599 --> 00:17:52.839
you know, not really able to be observed by those individuals.

313
00:17:53.119 --> 00:17:56.160
And then that lead me into led me into consulting

314
00:17:56.240 --> 00:18:00.799
for businesses. One of my consulting opportunity unities with was

315
00:18:00.839 --> 00:18:06.279
with a large sign company, National Sign Company, and on another.

316
00:18:05.920 --> 00:18:09.119
One was with s VP Worldwide.

317
00:18:08.640 --> 00:18:13.680
Which was Singer Sewing Machines with their Internet of Things

318
00:18:13.720 --> 00:18:17.319
products have product line sewing machines that are that are

319
00:18:17.359 --> 00:18:20.480
networked and people can download designs. And I was a

320
00:18:20.519 --> 00:18:23.960
part of that project and during the during the COVID,

321
00:18:24.200 --> 00:18:27.599
so as you can imagine, a lot of people had

322
00:18:27.680 --> 00:18:30.200
time and they were doing a lot of sewing during COVID,

323
00:18:30.839 --> 00:18:34.960
So that was a very fast moving type opportunity. And

324
00:18:35.039 --> 00:18:38.799
so I did enjoy the consulting and also that you know,

325
00:18:38.799 --> 00:18:42.559
there are some positives and doing technology consulting and there

326
00:18:42.559 --> 00:18:45.400
are some negatives. The positive is, you know, you kind

327
00:18:45.400 --> 00:18:48.640
of come in with a certain agenda to make a

328
00:18:48.880 --> 00:18:52.920
make a sweeping improvement or to innovate something that they

329
00:18:52.920 --> 00:18:56.799
have not noticed and give them advice. The downside is

330
00:18:56.839 --> 00:19:01.480
you're not really a member of the team and it's

331
00:19:01.599 --> 00:19:04.799
very easy for people to create opinions about your performance,

332
00:19:05.119 --> 00:19:09.279
whether it be he's aweso more, he's really doing what

333
00:19:09.319 --> 00:19:12.359
we're paying on that much to do. You know, that

334
00:19:12.480 --> 00:19:15.880
was the downside of consulting, But everything has its goods.

335
00:19:15.880 --> 00:19:19.000
And bads, But I did enjoy the process of it.

336
00:19:19.640 --> 00:19:19.920
All right.

337
00:19:19.960 --> 00:19:22.920
So in twenty twenty one, you started Brenner Brothers. I

338
00:19:22.920 --> 00:19:24.880
don't know a whole lot about that. Tell us what

339
00:19:24.920 --> 00:19:27.759
Brenner Brothers is or was sounds like it.

340
00:19:28.559 --> 00:19:29.640
Brenner Brothers is.

341
00:19:30.440 --> 00:19:35.000
It's still an entity, but it was a industrial food

342
00:19:35.079 --> 00:19:40.200
service for large corporations to the customers in Tennessee where

343
00:19:40.400 --> 00:19:44.279
General Motors and Ultium Batteries Ultium Cells, which is a

344
00:19:44.359 --> 00:19:50.400
large battery manufacturer owned by General Motors, and my brother

345
00:19:50.599 --> 00:19:54.200
and I started that and he is continuing it in

346
00:19:54.240 --> 00:20:00.640
the South Carolina area servicing large data center construction projects.

347
00:20:00.880 --> 00:20:01.160
Cool.

348
00:20:01.680 --> 00:20:05.720
Yeah, everybody's got to eat. That's pretty dependable, all right.

349
00:20:05.759 --> 00:20:08.160
And then, of course, in January of last year, you

350
00:20:08.359 --> 00:20:12.640
founded Icognio. So first tell us the why behind the

351
00:20:12.640 --> 00:20:15.119
what you know, what did you see, and why did

352
00:20:15.160 --> 00:20:17.640
you decide to Again, there's the risk. I'm sure there

353
00:20:17.680 --> 00:20:21.720
was money that you invested, et cetera. Nothing's free. Take

354
00:20:21.759 --> 00:20:22.880
us through that story.

355
00:20:24.039 --> 00:20:28.759
The way the company was originally envisioned was not what

356
00:20:28.799 --> 00:20:29.480
it is today.

357
00:20:29.960 --> 00:20:32.920
That that's a common theme in technology.

358
00:20:33.160 --> 00:20:36.000
You pivot as the market shows you what's actually going

359
00:20:36.079 --> 00:20:40.519
on and Originally we were shooting for a consumer product

360
00:20:41.039 --> 00:20:47.720
to protect privacy of AI users. But then we you know,

361
00:20:47.799 --> 00:20:51.000
over time, we started to niche down as we saw

362
00:20:51.039 --> 00:20:56.240
the market opportunity growing in certain areas, and that's how

363
00:20:56.240 --> 00:20:58.720
we ended up kind of, you know, in the legal

364
00:20:58.759 --> 00:21:04.680
space because in business and in sports and everything else,

365
00:21:04.799 --> 00:21:08.200
you have to figure out where the puck is going right,

366
00:21:09.400 --> 00:21:13.440
and you have to go there before others go there.

367
00:21:14.559 --> 00:21:15.680
You don't want to go there too.

368
00:21:15.559 --> 00:21:18.680
Early because no one will have interest you just wait

369
00:21:18.720 --> 00:21:20.880
too early. But you don't want to also be too

370
00:21:20.920 --> 00:21:24.920
late and come in behind. So that was kind of

371
00:21:25.039 --> 00:21:27.880
a lot of our early discussions. We started development in

372
00:21:28.279 --> 00:21:31.720
fall of twenty twenty four and then throughout all of

373
00:21:31.720 --> 00:21:35.279
twenty twenty five we continued our development and with a

374
00:21:35.319 --> 00:21:37.599
focus on AI security.

375
00:21:38.160 --> 00:21:40.000
How did you realize there was a need there?

376
00:21:41.119 --> 00:21:46.519
Yes, the AI security space is just a little baby

377
00:21:46.880 --> 00:21:51.279
hasn't even walked yet, and AI is sort of like

378
00:21:51.319 --> 00:21:55.519
the wild West in a lot of ways. Absolutely many

379
00:21:55.559 --> 00:21:59.519
of the listeners might know. And it's the wild West

380
00:21:59.559 --> 00:22:03.960
because it's a petri dish of technology due to the

381
00:22:04.000 --> 00:22:09.640
speed rapid innovation that's taking place and that desire to

382
00:22:10.160 --> 00:22:13.400
you know, have something first and get something out, and

383
00:22:14.000 --> 00:22:18.640
the pressure that companies are under due to large sums

384
00:22:18.680 --> 00:22:24.119
of investment in their companies to innovate, to release and

385
00:22:24.400 --> 00:22:27.680
you know, sort of the term damn the torpedoes comes

386
00:22:27.720 --> 00:22:33.240
to mind. It may not be completely safe, but we

387
00:22:33.359 --> 00:22:36.720
have to do it, you know, And so that was

388
00:22:36.720 --> 00:22:40.319
a that was a lot of our vision was that we.

389
00:22:39.759 --> 00:22:42.319
We saw whether Puck was going and.

390
00:22:42.279 --> 00:22:46.200
It was a little bit scary because we thought this

391
00:22:46.319 --> 00:22:49.559
is probably going to go wrong in a lot of

392
00:22:49.599 --> 00:22:50.359
different ways.

393
00:22:50.440 --> 00:22:52.599
But how is it going to go wrong? I'm not

394
00:22:52.680 --> 00:22:54.880
talking about end of world kind of.

395
00:22:55.039 --> 00:22:59.359
Scenarios, right, not not no, no, uh what I just

396
00:23:00.079 --> 00:23:04.519
lou the reference the name of the the Terminator series.

397
00:23:04.559 --> 00:23:06.599
Anyway, keep going right.

398
00:23:07.000 --> 00:23:10.519
Not end of world go wrong, but go wrong for companies,

399
00:23:11.079 --> 00:23:20.079
go wrong for businesses. Become an unsolvable challenge for security

400
00:23:20.119 --> 00:23:23.799
officers in companies and they, you know, they have to

401
00:23:23.839 --> 00:23:27.359
do what the CEO says, uh, that's their job to

402
00:23:27.680 --> 00:23:31.039
follow the orders. But they're also under pressure to secure

403
00:23:31.559 --> 00:23:36.880
their data, right, that's their other job. Their one job

404
00:23:37.000 --> 00:23:40.759
is innovate and follow instructions from the leadership of the company,

405
00:23:40.799 --> 00:23:44.119
from the board, but their primary job is to secure

406
00:23:44.160 --> 00:23:48.359
the data and so they you know, these security folks

407
00:23:48.480 --> 00:23:50.920
are in a little bit of a jam in a

408
00:23:50.920 --> 00:23:54.759
lot of ways. They probably would admit it that AI

409
00:23:55.359 --> 00:23:58.759
can be. AI is like fire. It can be your

410
00:23:58.799 --> 00:24:01.200
best friend or can be your worst enemy.

411
00:24:01.480 --> 00:24:02.279
That's a good reference.

412
00:24:03.160 --> 00:24:05.240
Yeah, so, and fire.

413
00:24:05.039 --> 00:24:08.720
Is a good thing. You have to control it. And

414
00:24:08.799 --> 00:24:12.440
so that's where we sit. We sit in that control space,

415
00:24:13.559 --> 00:24:18.480
ahead of the competition and deploying in such a fashion

416
00:24:19.000 --> 00:24:22.599
that they do not. And that is our core value

417
00:24:22.640 --> 00:24:26.440
proposition is that we're really not like any of the competitors.

418
00:24:26.440 --> 00:24:31.319
We are a the most secure AI solution for law.

419
00:24:31.759 --> 00:24:34.160
If somebody read a description, they'd say, wow, they're not

420
00:24:34.240 --> 00:24:37.039
cloud based. But there's a very important reason for that.

421
00:24:37.119 --> 00:24:39.799
And what you've created as an appliance, right, an on

422
00:24:39.960 --> 00:24:41.680
premise appliance. So tell us about that.

423
00:24:43.200 --> 00:24:44.359
The reason for our.

424
00:24:44.240 --> 00:24:47.279
Founding team, our founding team and myself we have a

425
00:24:47.400 --> 00:24:53.680
lot of history with infrastructure hardware and managing infrastructure hardware.

426
00:24:54.880 --> 00:24:58.240
And you know, the easiest way I can explain it

427
00:24:58.240 --> 00:25:00.599
to anyone who may meet the in tech knowledge or

428
00:25:00.599 --> 00:25:05.279
not being technology, they probably know what a firewall is, right,

429
00:25:05.680 --> 00:25:07.680
So you may have a firewall in your house.

430
00:25:08.039 --> 00:25:08.960
You probably do.

431
00:25:09.279 --> 00:25:13.119
Some people have firewalls in their house, but companies certainly

432
00:25:13.119 --> 00:25:16.920
have firewalls to protect their data. That firewall does not

433
00:25:16.960 --> 00:25:21.599
live in the cloud. There's a reason for that. It

434
00:25:21.680 --> 00:25:25.759
is a device because that is the best way to

435
00:25:25.799 --> 00:25:26.559
secure the.

436
00:25:26.599 --> 00:25:27.920
Data behind it.

437
00:25:29.000 --> 00:25:32.079
So that's basically the approach that we take to our

438
00:25:32.160 --> 00:25:36.559
solution is we take you know, best known practices of

439
00:25:37.160 --> 00:25:42.319
securing devices, and then we build an AI platform on

440
00:25:42.440 --> 00:25:46.119
top of that and we make it one hundred percent

441
00:25:46.200 --> 00:25:51.680
secure and one percent reliable, and it goes inside the

442
00:25:51.720 --> 00:25:55.119
customer's network. It doesn't live in the cloud. And that's

443
00:25:55.160 --> 00:25:58.240
why firewalls don't live in the cloud. That is our

444
00:25:58.279 --> 00:25:59.000
business model.

445
00:26:00.519 --> 00:26:04.119
And so this is for the for law firms. Uh,

446
00:26:04.400 --> 00:26:07.599
law firms have a I don't know if it's regulatory.

447
00:26:07.599 --> 00:26:09.480
I don't think it's regulatory, but they certainly have an

448
00:26:09.519 --> 00:26:14.559
obligation to keep everything secure, and in particular, you know,

449
00:26:14.599 --> 00:26:18.039
they could be not just at risk of you know,

450
00:26:18.079 --> 00:26:21.920
exposing customer data, but I expose competitive data too, right.

451
00:26:23.079 --> 00:26:26.240
So yeah, you know, we've done a lot of interviews

452
00:26:26.279 --> 00:26:29.279
with law firms, but you know, our assumption was that

453
00:26:29.720 --> 00:26:34.079
the risk versus reward benefit of using AI in certain

454
00:26:34.119 --> 00:26:39.559
spaces such as law is it's a slippery slope because

455
00:26:40.440 --> 00:26:43.079
you can get a lot of efficiencies from using AI

456
00:26:43.279 --> 00:26:46.799
in the law environment, but then at the same time,

457
00:26:47.640 --> 00:26:52.319
controlling what the end user actually does with AI is

458
00:26:52.319 --> 00:26:58.000
not so simple, so you get into internal regulatory or

459
00:26:58.440 --> 00:26:59.480
policy creation.

460
00:27:00.079 --> 00:27:00.200
Right.

461
00:27:01.640 --> 00:27:07.480
The American Bar Association has toyed with AI standards for law,

462
00:27:08.279 --> 00:27:09.680
but they have not done that yet.

463
00:27:10.200 --> 00:27:11.920
Yeah, it's not it's not easy, but it's it's a

464
00:27:11.960 --> 00:27:12.400
great idea.

465
00:27:13.279 --> 00:27:18.240
Well, we're counting on it. In fact, we're positive that

466
00:27:18.319 --> 00:27:22.319
it will happen. It's just a matter of time going

467
00:27:22.359 --> 00:27:24.400
by where more and more events occur.

468
00:27:25.240 --> 00:27:28.599
There are many events that have already occurred, so.

469
00:27:30.039 --> 00:27:32.599
You know we're going to be able to guarantee compliance

470
00:27:32.640 --> 00:27:35.960
at a much higher level. I don't want to get

471
00:27:36.000 --> 00:27:42.279
too geek, even if you allow. Companies like Anthropic, who

472
00:27:42.279 --> 00:27:46.200
were really focusing on the slanting a certain products set

473
00:27:46.559 --> 00:27:53.119
towards law, have since decreased their bar for security because

474
00:27:53.160 --> 00:27:56.440
they were getting sued a lot. And so even the

475
00:27:56.480 --> 00:27:59.799
AI companies, I don't want to say they don't really

476
00:27:59.880 --> 00:28:03.160
know how it works, because that's not a right statement.

477
00:28:03.440 --> 00:28:07.680
The AI companies don't really know what mistakes it will make.

478
00:28:08.599 --> 00:28:10.920
Right, So they're.

479
00:28:10.720 --> 00:28:16.519
Cautious because AI does things that are unpredictable by its nature,

480
00:28:17.440 --> 00:28:20.839
and that has to do with the DNA of how

481
00:28:20.880 --> 00:28:25.000
an AI platform is built and how it operates. It

482
00:28:25.000 --> 00:28:30.880
can be unpredictable. Unpredictable and law do not go together.

483
00:28:32.839 --> 00:28:35.559
It makes a lot of sense. So I can imagine

484
00:28:35.559 --> 00:28:42.920
that managing partners or boards are very leary.

485
00:28:43.480 --> 00:28:45.000
Yeah, you have a few different camps.

486
00:28:45.440 --> 00:28:49.839
You have your old school law firms who are hesitant

487
00:28:49.880 --> 00:28:54.640
to get off the dime with AI because AI has

488
00:28:54.640 --> 00:28:59.240
the potential to decrease billings, and billings is what their

489
00:28:59.279 --> 00:29:00.240
companies are built.

490
00:29:00.160 --> 00:29:02.480
Don Okay, So that's interesting.

491
00:29:02.559 --> 00:29:06.160
Yeah, you know, so they're they're at the you're talking

492
00:29:06.160 --> 00:29:07.039
at the board level.

493
00:29:07.079 --> 00:29:08.599
So you're talking at at.

494
00:29:08.440 --> 00:29:09.720
The board at the board level.

495
00:29:10.880 --> 00:29:15.480
Now, they also have efficiencies which can be gained, which

496
00:29:15.599 --> 00:29:19.839
is maybe X number of hours are saved per month

497
00:29:20.000 --> 00:29:25.599
per uh per paralegal or or per junior attorney or

498
00:29:25.680 --> 00:29:29.279
per attorney. I would I would say that the greatest

499
00:29:29.319 --> 00:29:32.960
savings is at the lower end because AI is better

500
00:29:33.000 --> 00:29:34.359
at repetitive tasks.

501
00:29:35.000 --> 00:29:37.319
Well, the argument I think I would think should be Okay,

502
00:29:37.359 --> 00:29:41.200
Now they have more capacity for billible hours.

503
00:29:42.839 --> 00:29:45.240
That's correct. That that's another one of the upsides.

504
00:29:45.279 --> 00:29:47.920
So you see, it's this slippery slope of what are

505
00:29:47.960 --> 00:29:50.400
the benefits and what are the what are the downsides

506
00:29:50.440 --> 00:29:54.640
of fully adopting AI. Now there's a there's another whole

507
00:29:54.720 --> 00:29:59.559
class of law firms that's evolving, which are AI first

508
00:29:59.599 --> 00:30:03.319
law firm Those are the guys that are going to

509
00:30:03.359 --> 00:30:04.519
shake the Apple card up.

510
00:30:05.480 --> 00:30:07.920
What would you say that legal zoom was maybe a

511
00:30:07.960 --> 00:30:09.640
precursor to something like that.

512
00:30:10.599 --> 00:30:14.599
Now this would be a little bit different. Legal legal

513
00:30:14.680 --> 00:30:16.720
Zoom is an automation platform.

514
00:30:16.960 --> 00:30:18.119
I think it's a good product.

515
00:30:18.720 --> 00:30:21.839
It's a it's an automation platform. What we're talking about

516
00:30:21.920 --> 00:30:28.279
is real law, not not just templates. We're talking about litigation. Litigation.

517
00:30:29.240 --> 00:30:33.960
Uh And basically you have AI firms that are now

518
00:30:34.000 --> 00:30:39.640
evolving and they're getting Interestingly, they're getting VC funding. So

519
00:30:39.640 --> 00:30:44.119
you have law firms getting VC funding. That's something new.

520
00:30:44.160 --> 00:30:44.799
I've never heard that.

521
00:30:45.079 --> 00:30:49.440
Yeah, you have AI first law firms getting VC funding

522
00:30:50.079 --> 00:30:55.119
to grow rapidly and the concept there is human in

523
00:30:55.200 --> 00:30:59.680
the middle. Right, So AI does a larger percentage of

524
00:30:59.720 --> 00:31:03.160
the world the law work than they would in a

525
00:31:03.200 --> 00:31:07.519
traditional law firm. Maybe AI does sixty or seventy or

526
00:31:07.559 --> 00:31:11.559
eighty percent of the work by design, the law firm.

527
00:31:11.400 --> 00:31:12.279
Is built that way.

528
00:31:13.240 --> 00:31:17.200
That's where you get some serious time savings, right, and

529
00:31:17.240 --> 00:31:20.200
then you have the human in the loop, where the

530
00:31:20.279 --> 00:31:25.960
human is really facilitating the law process. It's very similar

531
00:31:25.960 --> 00:31:30.400
to what's happening with AI and software development. Your lower

532
00:31:30.480 --> 00:31:34.000
end people are now becoming sort of architects in a way.

533
00:31:34.839 --> 00:31:38.759
Here's the same concept that in law that AI first

534
00:31:38.799 --> 00:31:43.599
law firm, the lawyer is more of a facilitator, an

535
00:31:43.720 --> 00:31:47.279
architect of the process. They're not doing the whole process,

536
00:31:47.599 --> 00:31:50.920
they're checking the process. So there's a huge savings there

537
00:31:50.960 --> 00:31:53.160
for the customer AI.

538
00:31:53.319 --> 00:31:56.200
AI can't go to court, they can't do a mediation,

539
00:31:56.440 --> 00:32:00.519
AI can't do a deposition. I suppose it possible, but

540
00:32:00.559 --> 00:32:02.480
you still need that traffic cop you still need that

541
00:32:02.559 --> 00:32:04.799
legality right right.

542
00:32:05.400 --> 00:32:10.119
Yes, And you would think that law firms are cautious

543
00:32:10.200 --> 00:32:13.640
about that, but you would be completely wrong.

544
00:32:13.839 --> 00:32:14.960
Because that's what I went there.

545
00:32:15.839 --> 00:32:18.759
There are I don't want to say hundreds, that's probably

546
00:32:18.759 --> 00:32:22.279
an overstatement. There are more than fifty cases that we're

547
00:32:22.319 --> 00:32:28.799
aware of where law firms have submitted and brought into

548
00:32:28.920 --> 00:32:36.240
court false AI generated content, some of them knowingly, some

549
00:32:36.319 --> 00:32:40.319
of them by a mistake. So it's a very uh

550
00:32:41.559 --> 00:32:44.240
it's like the wild West for law is. If you're

551
00:32:44.240 --> 00:32:47.640
going to use AI, you better have your saddle tight.

552
00:32:50.559 --> 00:32:52.119
All right, that's a good time to take a break.

553
00:32:52.119 --> 00:32:54.599
We'll take our second commercial right here. We'll be right

554
00:32:54.640 --> 00:32:56.880
back in about a minute with Craig Brenner.

555
00:32:57.559 --> 00:33:01.200
Thank you.

556
00:33:01.200 --> 00:33:05.160
You're listening to Winning Business Radio with Kevin Helene on

557
00:33:05.440 --> 00:33:09.400
W four CY Radio. That's W four cy dot com.

558
00:33:09.599 --> 00:33:12.240
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584
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in presenting exciting topics and expert guests with one goal

585
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in mind to help you succeed in business. Here once

586
00:34:40.960 --> 00:34:42.480
again is Kevin Helene.

587
00:34:49.960 --> 00:34:52.840
We're back with Craig Brenner, CEO and co founder of

588
00:34:53.039 --> 00:34:57.480
i Cognio. What makes your solution and you touched on

589
00:34:57.519 --> 00:34:59.679
that a little bit, but this is an opportunity to

590
00:34:59.719 --> 00:35:03.159
really the case what makes your solution better than other

591
00:35:03.239 --> 00:35:04.360
legal ais.

592
00:35:06.480 --> 00:35:11.679
The majority of legle ais are really not legal ais.

593
00:35:12.239 --> 00:35:17.119
They are yet they are a large language model an

594
00:35:17.199 --> 00:35:20.000
l l M. Whether it be anthropic or whether it

595
00:35:20.039 --> 00:35:25.119
be chat, GPT. And then like many products that people

596
00:35:25.159 --> 00:35:28.920
are familiar with that have AI embedded into them, the AI,

597
00:35:29.440 --> 00:35:33.440
you know, is really software around the large language model.

598
00:35:34.519 --> 00:35:40.599
We're completely different. It's basically a wrapper around regular AI.

599
00:35:41.559 --> 00:35:44.360
Our platform is built from the ground up just for law.

600
00:35:45.159 --> 00:35:48.559
It's a it's a major differentiator. Everything that's in our

601
00:35:48.639 --> 00:35:52.440
in our product is built with law in mind. And

602
00:35:52.800 --> 00:35:56.559
that that comes down to safety, That comes down to accuracy,

603
00:35:56.960 --> 00:36:01.559
that comes down to auditability, that comes down to reporting engines,

604
00:36:02.079 --> 00:36:05.880
you know, built for law. So everything in our product

605
00:36:06.079 --> 00:36:09.320
is built from the ground up for law. It's purpose built.

606
00:36:09.599 --> 00:36:13.320
That's the major differentiator. And obviously the second one is

607
00:36:13.599 --> 00:36:19.239
the most important. The security component is it lives inside

608
00:36:19.280 --> 00:36:24.719
the customer's network. Data never their their proprietary data never

609
00:36:24.920 --> 00:36:26.000
leaves their network.

610
00:36:26.960 --> 00:36:27.960
You know, why would it?

611
00:36:28.599 --> 00:36:31.079
Why would why would any company just think about what

612
00:36:31.119 --> 00:36:36.280
I'm saying here, Why would any company allow their proprietary data,

613
00:36:36.320 --> 00:36:38.239
whether it be a customer name, whether it be a

614
00:36:38.280 --> 00:36:43.679
case description, and put that out into the cloud, right

615
00:36:44.199 --> 00:36:46.280
and take a chance that it's going.

616
00:36:46.159 --> 00:36:48.800
To leak, right? They wouldn't.

617
00:36:49.599 --> 00:36:53.760
Why would they count on information coming back? So here's

618
00:36:53.880 --> 00:37:00.679
number three, information coming back from AI that is accurate, right,

619
00:37:01.000 --> 00:37:05.920
and hallucinations are probably the most talked about a problem

620
00:37:06.000 --> 00:37:10.960
in law having to do with AI. AI hallucinates. What

621
00:37:11.079 --> 00:37:11.920
is a hallucination?

622
00:37:12.079 --> 00:37:13.400
For people that are less.

623
00:37:13.199 --> 00:37:17.119
Technical out there, a hallucination is imagine you're going down

624
00:37:17.159 --> 00:37:21.079
a highway and the way AI works is it puts

625
00:37:21.119 --> 00:37:24.800
words together. That's how it gives you your response. It

626
00:37:24.840 --> 00:37:29.079
looks for the next logical word. When it can't find

627
00:37:29.119 --> 00:37:31.960
the next logical word, it does what it's designed to do.

628
00:37:32.599 --> 00:37:37.400
And this process is called probabilistic guessing. It guesses at

629
00:37:37.400 --> 00:37:43.039
the most probable exit on the highway right the next word.

630
00:37:43.320 --> 00:37:46.400
If it can't find it, it goes anyway right, it'll

631
00:37:46.440 --> 00:37:48.960
take it. And you know on the highway when you

632
00:37:48.960 --> 00:37:51.559
get off the wrong exit, now you've got to make

633
00:37:51.599 --> 00:37:55.840
many turns and take many false turns to get back

634
00:37:55.880 --> 00:37:59.880
on track. That is what a hallucination is for the

635
00:38:00.039 --> 00:38:03.679
common person to understand. It makes things up because it

636
00:38:03.719 --> 00:38:08.079
gets lost in the process. And the larger the models get,

637
00:38:09.039 --> 00:38:12.079
this is the important point. The larger the models get,

638
00:38:12.519 --> 00:38:16.440
the worse that problem gets, because now instead of five

639
00:38:16.519 --> 00:38:20.000
exits off the highway, you have five thousand exits off

640
00:38:20.000 --> 00:38:23.239
the highway to choose from. So while it might seem

641
00:38:23.320 --> 00:38:28.320
that AI can get smarter modeled, as the models grow,

642
00:38:28.920 --> 00:38:35.840
the traffic gets more complicated. So we solve that. I

643
00:38:35.880 --> 00:38:38.199
believe we're the only company who actually has a solution

644
00:38:38.320 --> 00:38:40.480
to that problem of hallucination.

645
00:38:40.639 --> 00:38:42.920
That's a patent that we have.

646
00:38:43.400 --> 00:38:45.519
Nice, Now, is it a fair question? And if you

647
00:38:45.519 --> 00:38:49.119
can't answer this in five minutes, don't how did you

648
00:38:49.159 --> 00:38:49.480
do that?

649
00:38:50.960 --> 00:38:57.000
So I have to be careful what I said that

650
00:38:57.360 --> 00:38:57.920
on that one.

651
00:38:58.800 --> 00:39:04.320
Let's let me describe it from a non technical perspective. Good, right, So, well,

652
00:39:04.480 --> 00:39:08.320
everyone's familiar with how a lie detector works. So you

653
00:39:08.400 --> 00:39:11.159
have someone who's accused of something and you know, they

654
00:39:11.199 --> 00:39:15.719
want want to maybe eliminate them as a as a suspect,

655
00:39:16.199 --> 00:39:18.480
or they want to say, oh, well, this person's lying.

656
00:39:18.880 --> 00:39:22.000
You know, this may not be completely accurate, right, A

657
00:39:22.000 --> 00:39:26.039
lie detector is not always completely accurate, but we have

658
00:39:26.119 --> 00:39:30.519
a better chance of knowing if the person's discepted. Right,

659
00:39:31.159 --> 00:39:35.880
that's exactly what we build. That's exactly exactly what we build.

660
00:39:36.559 --> 00:39:39.880
So could you say one hundred percent? You can't say

661
00:39:39.880 --> 00:39:43.039
one hundred percent with a lie detector. The way a

662
00:39:43.079 --> 00:39:48.239
lie detector works is that it looks for patterns in

663
00:39:48.280 --> 00:39:53.159
the response. Right, That's exactly what we do. That's exactly

664
00:39:53.199 --> 00:39:56.599
what our technology does. There are certain patterns that an

665
00:39:56.639 --> 00:40:00.960
honest response from AI have, and there are certain patterns

666
00:40:01.000 --> 00:40:05.760
that a hallucination had. In other words, something doesn't go

667
00:40:06.000 --> 00:40:10.159
with the question. So when you compare the question or

668
00:40:10.159 --> 00:40:12.719
the prompt in this case for those who use AI,

669
00:40:13.320 --> 00:40:17.599
you compare prompt to the response like a lie detector

670
00:40:17.920 --> 00:40:22.719
compares the question to the body signals, you can see

671
00:40:22.719 --> 00:40:25.000
deception or you can sense it.

672
00:40:25.960 --> 00:40:28.320
That's exactly what we've built before.

673
00:40:28.360 --> 00:40:30.119
It provides unanswered response.

674
00:40:30.880 --> 00:40:32.719
Yes, accuracy response.

675
00:40:32.960 --> 00:40:37.599
An accuracy response is probably the biggest flaw.

676
00:40:37.360 --> 00:40:38.199
That AI has.

677
00:40:40.760 --> 00:40:43.639
Now, who's on your team? I mean this seems like

678
00:40:43.800 --> 00:40:46.119
really forward thinking stuff. And I'm not saying that to

679
00:40:46.280 --> 00:40:48.639
you know, stroke you or anything like that. I'm just

680
00:40:48.639 --> 00:40:51.920
saying that it just does really seem advanced. Who are

681
00:40:51.920 --> 00:40:54.360
the folks on your team? Not by name, but by

682
00:40:54.440 --> 00:40:56.679
background that made this possible?

683
00:40:57.639 --> 00:41:01.840
Sure, you know, like myself, the team members are folks

684
00:41:01.840 --> 00:41:04.679
that have worked together for and we have many years

685
00:41:04.679 --> 00:41:07.679
of experience. You know, we're kind of like I like

686
00:41:07.719 --> 00:41:09.440
to make the joke that we're the you know, we're

687
00:41:09.480 --> 00:41:12.440
the non startup group. You know, the twenty two year

688
00:41:12.440 --> 00:41:15.039
old kid who works one hundred hours a week and

689
00:41:15.079 --> 00:41:19.239
never sleeps. We have none of those. We sleep because

690
00:41:19.280 --> 00:41:21.920
we know sleep's important. With a twenty two year old kid,

691
00:41:21.960 --> 00:41:25.119
he doesn't know yet got to sleep. But what we

692
00:41:25.159 --> 00:41:27.880
do have is we have that pedigree and we have

693
00:41:28.000 --> 00:41:31.960
it in the areas of hardware development and management, which

694
00:41:32.000 --> 00:41:34.760
is our core. We have it in the area of

695
00:41:34.840 --> 00:41:38.559
scaling with our Chief Scaling Advisor, so we have a CTO,

696
00:41:38.840 --> 00:41:42.760
we have a CSO, a chief scaling advisor. Obviously, we

697
00:41:42.840 --> 00:41:45.400
have a great finance person out of Canada.

698
00:41:45.760 --> 00:41:49.480
He joined the team. He's magnificent. He really knows his stuff.

699
00:41:50.119 --> 00:41:53.599
And then we have a chief scientist who is working

700
00:41:53.599 --> 00:41:57.679
on you know, things that I can't talk about or

701
00:41:57.719 --> 00:42:00.400
he'll get upset with me, but he's work working on

702
00:42:00.440 --> 00:42:04.199
some cool stuff. We call him Uncle Fester because he's

703
00:42:04.199 --> 00:42:07.199
good at testing and experimenting. You have to have one

704
00:42:07.199 --> 00:42:09.000
of those on your team if you're going to innovate.

705
00:42:09.400 --> 00:42:11.000
She's great. And then we.

706
00:42:10.960 --> 00:42:14.320
Also have our Chief Marketing Officer and if you want

707
00:42:14.320 --> 00:42:16.159
to visit the website you can see some of his

708
00:42:16.280 --> 00:42:19.519
great great vision for our messaging and our marketing.

709
00:42:20.000 --> 00:42:23.519
And so that's the team. We have an experienced team.

710
00:42:24.159 --> 00:42:28.880
We also have a new member of the team. She's

711
00:42:29.800 --> 00:42:31.119
out of college.

712
00:42:31.119 --> 00:42:33.280
She is out of college and she was actually a

713
00:42:33.320 --> 00:42:36.280
founder of her own AI legal company. And we went

714
00:42:36.320 --> 00:42:38.840
and found her and she just said, she loves what

715
00:42:38.880 --> 00:42:41.039
we're doing. She gets the problem, she wants to solve

716
00:42:41.079 --> 00:42:43.599
the problem. Had nothing to do with her other company.

717
00:42:44.000 --> 00:42:47.360
She just thought, your guys are solving it properly, and

718
00:42:47.440 --> 00:42:47.880
I want.

719
00:42:47.760 --> 00:42:48.519
To be a part of that.

720
00:42:49.039 --> 00:42:51.599
So I guess you know, we've got six people now

721
00:42:51.960 --> 00:42:54.079
on the core founding team.

722
00:42:53.960 --> 00:42:58.400
Remote pardon me disparate, Yes, we are.

723
00:42:58.320 --> 00:42:59.800
One hundred percent remote company.

724
00:43:00.079 --> 00:43:00.480
Yeah.

725
00:43:00.760 --> 00:43:04.039
And you know, I say, if some investor wants to

726
00:43:04.199 --> 00:43:07.400
make us have an office, you know, it's if they

727
00:43:07.440 --> 00:43:09.639
have a good reason to have an office, we'll have

728
00:43:09.719 --> 00:43:12.719
an office. But right now we don't see good reason

729
00:43:12.679 --> 00:43:14.880
to have an office. We'd rather save money and be efficient.

730
00:43:15.199 --> 00:43:18.519
Yeah, our team for most well, same, What would you

731
00:43:18.559 --> 00:43:21.519
say is a speed of adoption here of the of

732
00:43:21.599 --> 00:43:23.800
law firms? And by the way, this is commercially.

733
00:43:23.320 --> 00:43:26.440
Available, correct, Yes, it's available.

734
00:43:26.639 --> 00:43:30.719
Yep, that was my understanding. Speed of adoption is it

735
00:43:30.719 --> 00:43:33.719
getting better. Is it a hard uphill slog to get

736
00:43:34.119 --> 00:43:36.119
law firms to adopt this? Is there a hunger and

737
00:43:36.159 --> 00:43:36.559
a need?

738
00:43:38.519 --> 00:43:42.679
Well, the rate of adoption in general in this market

739
00:43:44.119 --> 00:43:48.880
has fluctuated, and the reason is fluctuated has nothing really

740
00:43:48.920 --> 00:43:52.800
to do with technology. It's fluctuated having to do with

741
00:43:52.920 --> 00:43:59.519
organizational change. Right. So certain organizations are very entrenched in

742
00:43:59.559 --> 00:44:04.920
their current legal processes like you do have other large

743
00:44:05.239 --> 00:44:09.159
legal organizations that are in more repetitive markets, such as

744
00:44:09.840 --> 00:44:15.559
accident litigation, right, right, like Morgan and Morgan. Morgan and

745
00:44:15.599 --> 00:44:19.480
Morgan was a plug for them. They were one of

746
00:44:19.519 --> 00:44:25.079
the early AI adopters with something called x AI that

747
00:44:25.239 --> 00:44:28.599
was in late twenty twenty three or early twenty twenty four.

748
00:44:28.679 --> 00:44:32.159
They released it and started using it, and they lost

749
00:44:32.159 --> 00:44:35.840
a major lawsuit to Walmart due to hallucinations, and then

750
00:44:35.920 --> 00:44:38.920
they kind of backed off. So when I say fits

751
00:44:38.920 --> 00:44:41.960
and starts, it's like they backed off and they said, Okay, wait,

752
00:44:42.039 --> 00:44:44.039
we've got to we've got to make sure we're doing

753
00:44:44.079 --> 00:44:45.320
this you know better.

754
00:44:46.159 --> 00:44:47.239
And since then.

755
00:44:47.199 --> 00:44:51.920
They've they've actually launched a new startup which is focused

756
00:44:52.519 --> 00:44:57.400
clearly on features and functions of that space. Right, So

757
00:44:57.719 --> 00:45:01.000
you're going to have a niche down effect over time

758
00:45:01.559 --> 00:45:06.320
where more and more companies can niche down. We're going

759
00:45:06.400 --> 00:45:10.719
to do that with modules, right, Different kinds of law

760
00:45:10.840 --> 00:45:12.159
require different kinds.

761
00:45:11.920 --> 00:45:12.760
Of feature sets.

762
00:45:13.480 --> 00:45:18.639
An example is for Morgan and Morgan, who does accident litigation.

763
00:45:19.519 --> 00:45:24.000
A big thing is hospital records right when you would think.

764
00:45:23.800 --> 00:45:26.920
A hospital records, because hospital.

765
00:45:26.480 --> 00:45:30.239
Records show costs and hospital records show damage. And so

766
00:45:30.880 --> 00:45:33.320
they've built a whole part of that solution just around

767
00:45:33.320 --> 00:45:40.239
hospital records. Yeah, so other companies are more afraid of AI.

768
00:45:40.440 --> 00:45:43.599
I've talked to some companies that are They literally said

769
00:45:43.599 --> 00:45:44.360
the word afraid.

770
00:45:45.079 --> 00:45:47.400
You know, so, well, we're afraid of AI.

771
00:45:47.559 --> 00:45:50.679
We hear all these cases that we hear about sanctions

772
00:45:50.719 --> 00:45:53.519
in the courts, We hear about judges throwing cases out

773
00:45:53.559 --> 00:45:55.880
where you know, we want to do it the old

774
00:45:55.880 --> 00:45:58.039
fashioned way because we don't want to be in that group.

775
00:45:58.920 --> 00:45:59.119
Right.

776
00:45:59.239 --> 00:46:02.320
So, and then you have the ones who want to adopt,

777
00:46:03.599 --> 00:46:07.960
but they don't know how to adjust their processes to

778
00:46:08.000 --> 00:46:13.159
maximize AI, if that makes any sense. Their processes are old,

779
00:46:13.159 --> 00:46:17.320
so their processes need to change to maximize AI, or

780
00:46:17.360 --> 00:46:20.320
else they're spending a bunch of money for something and

781
00:46:20.360 --> 00:46:22.159
they're not really getting a lot out of it, and

782
00:46:22.159 --> 00:46:24.800
that is happening often.

783
00:46:25.199 --> 00:46:27.039
All right, there's also a term and you know, my

784
00:46:27.119 --> 00:46:33.440
guess is, well, before this discussion, my assumption was, uh,

785
00:46:33.480 --> 00:46:36.239
there are people using AI at law firms already. They're

786
00:46:36.280 --> 00:46:38.079
just using it on their own, their own chat, GPT,

787
00:46:38.199 --> 00:46:39.840
their own Gemini, their own whatever.

788
00:46:39.960 --> 00:46:41.159
And shadow AI.

789
00:46:42.239 --> 00:46:47.039
Yeah, talk about it. Yeah, very risky, yeah.

790
00:46:46.679 --> 00:46:53.159
Shadow AI and also operating without an AI company policy governance,

791
00:46:54.079 --> 00:46:58.280
a governance policy to let the to let the employees

792
00:46:58.320 --> 00:47:00.519
know that, hey, when you come to work, it's not

793
00:47:00.679 --> 00:47:04.679
okay to just use AI to speed up your work

794
00:47:05.119 --> 00:47:09.760
or make your work more accurate and use anything you want. Now,

795
00:47:10.719 --> 00:47:14.199
the challenge then becomes, let's say you have a governance policy,

796
00:47:14.760 --> 00:47:18.559
and let's say you know you have good training. They

797
00:47:18.559 --> 00:47:21.280
can still do it on their own, and in general,

798
00:47:23.000 --> 00:47:26.960
human nature dictates that they will. Human nature dictates that

799
00:47:27.280 --> 00:47:31.840
unless you give them a better tool, they will do

800
00:47:32.000 --> 00:47:35.719
the thing that makes them do their job faster because

801
00:47:35.719 --> 00:47:36.599
that gets praised.

802
00:47:36.840 --> 00:47:38.079
Sure, and they will do.

803
00:47:38.079 --> 00:47:41.119
The thing that helps them do their job better than

804
00:47:41.159 --> 00:47:45.280
the other person in their same position because that gets praise.

805
00:47:46.039 --> 00:47:47.639
And if you do your job better, and you do

806
00:47:47.679 --> 00:47:52.840
your job faster. It also equals performance reviews. So now

807
00:47:52.840 --> 00:47:55.559
you're telling someone, well, you know, don't do the thing

808
00:47:55.599 --> 00:47:57.800
that's going to make you look great, do this other

809
00:47:57.840 --> 00:48:01.159
thing that we bought, even though it's not quite good good. Right,

810
00:48:01.559 --> 00:48:03.320
that's a that's a tough one. That's a that's a

811
00:48:03.360 --> 00:48:05.639
tough one to solve. So you have to give them

812
00:48:05.639 --> 00:48:09.840
a better tool and every The problem with human nature

813
00:48:09.880 --> 00:48:13.519
also is that I know it from managing technology for

814
00:48:13.679 --> 00:48:19.719
many different companies, is everyone has their favorite tool, right,

815
00:48:19.760 --> 00:48:22.880
You have your favorite tools for sure, yep, I have

816
00:48:22.960 --> 00:48:27.239
my favorite tools. Everyone has their favorite tool. So when

817
00:48:27.239 --> 00:48:30.119
they go to work and they get a tool that's

818
00:48:30.119 --> 00:48:33.920
not as good as their favorite, which many of them aren't,

819
00:48:34.079 --> 00:48:38.119
they say, why would I use this, you know, inferior

820
00:48:38.199 --> 00:48:40.599
tool when my tool that I use at home for

821
00:48:40.679 --> 00:48:42.159
AI is so much.

822
00:48:41.960 --> 00:48:45.280
Better and I'm used to it, I'm comfortable with it, right.

823
00:48:45.559 --> 00:48:46.360
So so that's it.

824
00:48:46.480 --> 00:48:49.440
Those are the those are the real Uh what do

825
00:48:49.440 --> 00:48:54.599
you call cultural challenges that any company adopting AI has?

826
00:48:55.800 --> 00:48:57.480
Yeah, you refer to it as behavior change?

827
00:48:58.679 --> 00:49:02.599
Yes, I human nature. Human nature is very hard to manage.

828
00:49:04.039 --> 00:49:06.559
All right, we are on we're almost out of time.

829
00:49:06.559 --> 00:49:09.440
A couple questions. Is there a size law firm that's

830
00:49:09.480 --> 00:49:12.360
a sweet spot? Is somebody too small too big? Tell

831
00:49:12.400 --> 00:49:15.519
the audience that, and then what's the best way or

832
00:49:15.559 --> 00:49:17.599
excuse me, I won't even say that question yet. You

833
00:49:17.599 --> 00:49:18.480
answer that one first.

834
00:49:18.760 --> 00:49:21.360
Yeah, Well, we're steering away from the lower end of

835
00:49:21.400 --> 00:49:23.880
the market. If you look at the total addressable market,

836
00:49:24.159 --> 00:49:26.679
it's about a nine billion dollar a year market.

837
00:49:26.679 --> 00:49:30.760
Right for law in general law, and you've got three stratas.

838
00:49:30.800 --> 00:49:34.440
You've got your larger enterprise corporations, then you've got your

839
00:49:34.480 --> 00:49:37.719
smaller you know, five and ten and fifteen person shops,

840
00:49:37.840 --> 00:49:41.559
or I'll also put in that your legal departments for

841
00:49:41.679 --> 00:49:42.480
larger companies.

842
00:49:42.559 --> 00:49:44.360
Oh okay, right, you know.

843
00:49:44.519 --> 00:49:46.119
Fewer seats, fewer seats.

844
00:49:46.679 --> 00:49:51.159
We're targeting the middle, the middle of the middle to

845
00:49:51.280 --> 00:49:53.719
the middle of the upper if that makes any sense, No,

846
00:49:53.800 --> 00:49:57.760
it does. Yeah, So we're targeting the upper half of

847
00:49:57.840 --> 00:50:00.559
the of the middle strata and the low or half

848
00:50:00.719 --> 00:50:04.079
of the enterprise strata. And the reason why we were

849
00:50:04.119 --> 00:50:07.639
doing that is because we believe that that's the place where

850
00:50:07.639 --> 00:50:11.480
you can succeed best when you get into enterprise of

851
00:50:11.760 --> 00:50:14.920
you know, law offices that have you know, you know,

852
00:50:15.079 --> 00:50:18.800
hundreds of thousands employees, you know which they are offices

853
00:50:18.840 --> 00:50:21.320
all over the world. You're in a whole new it's

854
00:50:21.360 --> 00:50:24.239
a different operation and there and there are competitors who

855
00:50:24.280 --> 00:50:27.239
are going after that market and they've raised a lot

856
00:50:27.280 --> 00:50:27.719
of money.

857
00:50:28.320 --> 00:50:30.559
We've decided, you know, not to do that.

858
00:50:31.559 --> 00:50:33.880
All right, here's the last question. Who in the viewing,

859
00:50:34.079 --> 00:50:37.960
viewing and listening audiences should reach out to you and why?

860
00:50:39.360 --> 00:50:41.679
I think I think anyone who's looking for a great

861
00:50:41.719 --> 00:50:44.039
investment should should reach out to us.

862
00:50:45.239 --> 00:50:46.719
We're we're right now.

863
00:50:47.000 --> 00:50:52.480
Just you know, began our fundraising campaign and there's no

864
00:50:52.559 --> 00:50:55.599
other opportunity like this in the market. We're one of

865
00:50:55.639 --> 00:50:59.239
a kind solution with a great management team. We're we're

866
00:50:59.280 --> 00:51:03.639
targeting on mart that's ripe for AI. In fact, any

867
00:51:03.760 --> 00:51:07.039
any law firm that doesn't adopt AI will will go

868
00:51:07.159 --> 00:51:07.840
out of business.

869
00:51:08.239 --> 00:51:09.960
So you have to adopt it.

870
00:51:09.960 --> 00:51:13.280
It's not a it's not an if, right, and then

871
00:51:13.320 --> 00:51:17.320
it's a when, Well, when is when is now? So

872
00:51:17.519 --> 00:51:21.079
the timing couldn't be better, and our technology is well

873
00:51:21.079 --> 00:51:23.599
thought out and we've got an experienced management team. So

874
00:51:23.920 --> 00:51:26.360
those are the people that should contact me. The second

875
00:51:26.360 --> 00:51:28.880
people that should contact me is anyone who's looking for

876
00:51:28.920 --> 00:51:32.760
something that does the things that I've described. You know,

877
00:51:32.800 --> 00:51:35.400
any law firm that's looking you know, any law firm

878
00:51:35.440 --> 00:51:39.679
that has say, fifty attorneys, thirty attorneys, twenty five attorneys,

879
00:51:39.800 --> 00:51:42.440
up to one hundred attorneys. That's kind of our sweet spot.

880
00:51:42.840 --> 00:51:45.599
And they're saying, hey, you know, maybe we are afraid

881
00:51:45.760 --> 00:51:48.480
of AI. You know, give us a call. We can

882
00:51:48.519 --> 00:51:49.079
help you with that.

883
00:51:50.480 --> 00:51:52.639
And your email address one more time. The website is

884
00:51:52.920 --> 00:51:54.280
icognio dot com.

885
00:51:54.880 --> 00:51:55.880
It's Icognio.

886
00:51:56.159 --> 00:52:00.599
I see O g n Io, not Incognio.

887
00:52:00.079 --> 00:52:03.000
But hi I Cognio. Yeah, and my.

888
00:52:03.159 --> 00:52:07.039
Email address is CRAIGT. Brenner at icognio dot com.

889
00:52:07.039 --> 00:52:07.440
Perfect.

890
00:52:07.480 --> 00:52:09.239
Well, thank you so much for the time. We really

891
00:52:09.280 --> 00:52:11.239
appreciate you being here. I enjoyed it, and.

892
00:52:11.519 --> 00:52:12.800
Yeah, I enjoyed it too as well.

893
00:52:12.840 --> 00:52:15.639
Thank you very cool, You're very welcome, and thanks everybody

894
00:52:15.719 --> 00:52:18.440
for watching and listening. This is a show about business

895
00:52:18.480 --> 00:52:20.039
and business challenges.

896
00:52:20.119 --> 00:52:20.320
Right.

897
00:52:20.440 --> 00:52:24.320
If you've got concerns about the sales effectiveness of your company,

898
00:52:24.320 --> 00:52:26.440
whether your sales team is you or very small or

899
00:52:26.440 --> 00:52:28.599
it's very large, feel free to reach out to me

900
00:52:28.679 --> 00:52:31.519
on Facebook or LinkedIn. One of my easy email addresses

901
00:52:31.599 --> 00:52:34.960
is Kevin at Winning Business Radio dot com. We are

902
00:52:35.119 --> 00:52:38.920
Winning Incorporated, part of Sandler Training. We develop salespeople and

903
00:52:38.960 --> 00:52:42.760
sales teams at the high achievers and sales leaders into

904
00:52:42.800 --> 00:52:45.119
true coaches and mentors. We're not a fit for everybody,

905
00:52:45.119 --> 00:52:47.400
but hey, maybe we should have a conversation. Thank you

906
00:52:47.519 --> 00:52:49.960
one for another job well done. Our producer and engineer

907
00:52:50.239 --> 00:52:52.960
join us again next Monday, April sixth. We'll do it

908
00:52:52.960 --> 00:52:55.159
all over again with a great guest. Until then, this

909
00:52:55.280 --> 00:52:56.039
is Kevin Hallinan.

910
00:52:58.599 --> 00:53:01.400
You've been listening to Winning Business Radio with your host,

911
00:53:01.480 --> 00:53:04.599
Kevin Helenan. If you missed any part of this episode,

912
00:53:04.679 --> 00:53:08.840
The podcast is available on top for podcasting and iHeartRadio.

913
00:53:09.280 --> 00:53:13.000
For more information and questions, go to Winning Business Radio

914
00:53:13.119 --> 00:53:16.119
dot com or check us out on social media. Tune

915
00:53:16.159 --> 00:53:18.239
in again next week and every Monday at four pm

916
00:53:18.280 --> 00:53:21.760
Eastern Time to listen live to Winning Business Radio on

917
00:53:22.039 --> 00:53:26.320
W four CY Radio W four cy dot com. Until then,

918
00:53:26.679 --> 00:53:30.280
let's succeed where others have failed and win in business

919
00:53:30.559 --> 00:53:34.360
with Kevin Helenan and Winning Business Radio