[Emerging Tech] Building AI-First CRM for Advisors With Mitchell Bratina
Mitchell Bratina is the Founder and CEO of FinTurk, an AI-native CRM built specifically for financial advisors to automate workflows and deliver more personalized client experiences. A former wealth advisor, he previously helped manage more than 300 client relationships and over $1.1 billion in assets. Mitchell is a CFA charterholder and holds a bachelor’s degree in computer engineering from Iowa State University. He combines his financial advisory experience with software engineering expertise to build technology that reduces administrative work and gives advisors more time to serve clients.
Here’s a glimpse of what you’ll learn:
[2:11] Mitchell Bratina discusses how FinTurk is helping financial advisors personalize client service with an AI-native CRM
[3:08] What makes an AI-native CRM different from traditional platforms with AI add-ons
[5:55] Three ways AI can act, assist, or teach users within FinTurk
[7:23] Building permission systems and safety guardrails around AI agents
[9:23] Mitchell talks about keeping AI within compliance boundaries for financial advisory work
[12:11] FinTurk’s 70% rule for deciding whether to build or integrate features
[14:08] Why integrated platforms can outperform disconnected point solutions for advisors
[18:08] How small engineering teams can use AI to compete with larger software companies
[30:10] Building FinTurk as a customizable second brain for financial advisors
In this episode…
Advisors are under growing pressure to deliver personalized service while managing time-consuming data entry, meeting preparation, follow-up, and disconnected technology. At the same time, clients increasingly use AI to research financial questions and expect faster, more informed responses. How can advisors use AI to become more efficient without sacrificing judgment, compliance, and meaningful client relationships?
Mitchell Bratina, a financial advisor turned technology entrepreneur specializing in AI-powered advisory software, recommends using AI to support rather than replace human judgment. He explains how AI-native systems can automate routine tasks, translate natural language into deterministic workflows, and help advisors customize technology around their individual practices. Mitchell also encourages advisors to respond quickly to AI-generated client questions, uncover the underlying concerns behind those questions, and use conversations to reinforce their value as trusted teachers and advisors.
In this episode of The Customer Wins, Richard Walker interviews Mitchell Bratina, Founder and CEO of FinTurk, about the future of AI-native technology for financial advisors. Mitchell discusses AI guardrails and compliance, systems design and vibe coding, and the use of AI to strengthen advisor-client relationships.
Resources Mentioned in this episode
Quotable Moments:
“I think there needs to be a firewall between the AI and the tools that it has access to.”
“I think larger engineering teams are actually going to become a disadvantage because of the communication across a team.”
“I think there’s still a gap there in the systems design portion.”
“They don’t know the questions to ask. And so I think that’s a very clear signal for an advisor.”
“We’re trying to make FinTurk conform to the advisor's way of thinking.”
Action Steps:
Build AI around clear permission controls: Creating guardrails between AI and the tools it can access helps prevent unauthorized actions while enabling users to benefit safely from automation.
Use AI to support human judgment: Combining AI-powered interactions with deterministic systems can improve efficiency while keeping important financial decisions controlled and compliant.
Prioritize systems thinking before AI-powered development: Spending more time planning architecture and workflows helps teams build stronger products instead of relying on AI to make critical design decisions.
Respond quickly to AI-generated client questions: Fast, personalized responses help advisors demonstrate their value while creating opportunities to uncover what clients truly need to understand.
Customize technology around how advisors work: Building systems that learn an advisor’s processes, preferences, and approach can reduce administrative work while supporting more personalized client relationships.
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Episode Transcript:
Intro: 00:02
Welcome to The Customer Wins podcast, where business leaders discuss their secrets and techniques for helping their customers succeed and in turn, grow their business.
Richard Walker: 00:16
Hi, I'm Rich Walker, the host of The Customer Wins, where I talk to business leaders about how they help their customers win and how they're focused on customer experience leads to growth. Today is a special episode of my series on new and emerging solutions. And today's guest is Mitchell Bratina, CEO and co-founder of FinTurk, Pardon me. FinTech is everywhere, right?
So FinTurk, some of the other past guests in my series include Ian Karnell, a VastAdvisor, George Swetlitz of RightResponse AI and Mark Ovaska of Precept. And today's episode is brought to you by Quik!, the leader in enterprise forms processing. When your business relies upon processing forms, don't waste your team's valuable time manually reviewing the forms. Instead, get Quik! using Quik!, you'll be able to generate completed forms and get back clean, context rich data that reduces manual reviews to only one out of 1000 submissions. Visit Quickforms.com to get started.
All right, I've been excited to talk to our guest today. He and I have already had a geek session, so this is going to be fun. Mitchell Bratina is the founder, co-founder and CEO of FinTurk, the AI native CRM built for registered investment advisors. Before FinTurk, Mitchell spent years as a financial advisor managing hundreds of client relationships where he lived. The problem he now solves.
Advisors losing their best hours to data entry, meeting, prep, and follow up instead of advice. Mitchell, welcome to The Customer Wins.
Mitchell Bratina: 01:48
Yeah. Thank you Rich. Appreciate you having me on.
Richard Walker: 01:52
Very excited to talk to you. So for my audience who may not have heard my podcast before, I love to talk with business leaders about what they're doing to help their customers win, how they build and deliver a great customer experience, and the challenges to growing their own company. So Mitchell, let's understand your business a lot better. How does your company help people?
Mitchell Bratina: 02:11
Yeah, yeah. Rich. Basically, when I was an advisor, there were a lot of practices and, you know, niche activities that I took that attracted clients to me. You know, it was my own approach to advising. And I think every advisor kind of has their personal touch, their approach.
And that's the reason why their clients approach them, have stayed with them. So what we're trying to do with FinTurk is provide, you know, not only that AI native experience, but the customizability of a platform that allows advisors to really lean into their best practices, their niche, and serving their clients in the best way that they do.
Richard Walker: 02:55
All right. You said an AI native experience. And I think there's a lot of debate about what that actually looks like and feels like. I have my idea. I'm really curious what that means to you.
Mitchell Bratina: 03:08
Yeah. The way that I think about it is there are there are a lot of platforms out there that already exist. You know, CRMs that everybody's familiar with. That had really great infrastructure for a CRM kind of for this previous era when they go to add AI. Either they have to bolt it on.
And so it's kind of a, you know, a sidecar to the platform they already have. And it is useful or they have to, they have to really tear things down and build them up from scratch. And where these AI native platforms, you know, FinTurk, being a native CRM come in is that the platform was designed around the AI at the center of it. So it's one AI system kind of poking its head out in a bunch of different spots on the platform versus bolting on and looking in.
Richard Walker: 04:00
Okay, what does that mean to the actual user experience though? Is it, hey, I'm always chatting with my CRM now I'm going to treat it like the computer on Star Trek. What is the experience like?
Mitchell Bratina: 04:11
Yeah, I think a topic I would love to chat about at some point today is what that, you know, future interface looks like for advisors when they're, when they're using AI platforms. But right now, I think what that looks like is that every, every experience that the advisor has with the AI in a platform is aware of every other interaction that the advisors had with the AI in different spots of the platform or the platform itself. So just a, a small example would be that, you know, the AI within FinTurk, if an advisor is on a page, you know, on their computer and they ask the AI question, the AI actually knows every single component that's on the page. It can spotlight things, highlight things, click on buttons for them. So it makes it really easy for the advisor to operate the platform more quickly or learn the platform.
That's something we've we've found advisors have really liked about that implementation.
Richard Walker: 05:12
Nice. And so that's working today.
Mitchell Bratina: 05:14
It is. Yep.
Richard Walker: 05:16
And the feedback's there. Then the people are like, this is a nicer experience. Oh yeah. No, that's really validating. Mitchell.
I am in the midst of designing a system that is AI first. In fact, it has its own agent that sits there to help you navigate and do anything. If you want to add a user, you don't have to go admin, click user add user button. You can just say, hey agent, add the user Mitchell Bratina to my system as an administrator. Okay.
And it will go do it for you. It can also navigate you there and show you how to do it, if that's what you prefer. But you'd have to ask that like, hey, take me to the user admin screen and it would do that for you. So it sounds like that's what you are doing. Is that similar?
Mitchell Bratina: 05:55
Yep. That's that's exactly what it is. You know, we want to make sure there's, there's the ability for the user to do it on their own if they want. The AI is able to take that action on their behalf, or the AI can teach them. So there's really kind of three prongs there that we think about when we're designing a user interaction now.
Richard Walker: 06:13
And are you like, I'm thinking of it as an agent that's there to help you. And it, it has a persona and a name and the whole thing is yours, just more the system or is it kind of agent-driven or persona-driven?
Mitchell Bratina: 06:25
Yeah. So we do have Finn. Finn is the central agent that kind of coordinates all of the sub-agents. We're actually rolling out probably next week, the ability for users to create their own custom agents with their own, you know, instructions and tools and access that they can use. But that, that Finn is the main one.
And then we actually have two others that we're rolling out to. And so it'll be kind of a three, you know, triumvirate AI system within the FinTurk platform.
Richard Walker: 06:55
Okay. I am so on the edge of asking really technical questions, and I don't want to bore the audience with such depth. And I'm trying to make sure I don't go too deep. But, you know, one of the things I always concerns me about AI is how do you control it? How do you make sure that a non-admin can't do admin things?
Hey, go add a user and give them admin privileges. In fact, make me an admin. How do you control such things? But this gets into the tech so try to keep us out.
Mitchell Bratina: 07:23
Yeah. I want to bring it up to a high level. I think there needs to be a firewall between the AI and the tools that it has access to that can't be interacted with by the AI in any way. And then if that AI tries to make a request that that user is not enabled for that request, just kind of gets burned, you know, tells the AI, hey, the user doesn't have access to this. So it's really, really piggybacking off of more traditional permission systems.
But, you know, putting it between the AI and its tools in the platform.
Richard Walker: 08:02
Okay. That makes sense to me. Hopefully the audience does too. I think it's important for people to understand that there are safety nets that intelligent people like you are absolutely considering that because you can't run a software product that doesn't have controls and restrictions and constraints around it. Here's the other one.
Hey Finn, how do I make chicken casserole? Like something totally unrelated to what you're supposed to do? How do you stop that behavior?
Mitchell Bratina: 08:29
Yeah. You know, that's one we're less worried about. We do have instructions for Finn. Hey, only, you know, help out with questions related to either Finn or, you know, financial advisory or financial advisory. Adjacent related questions.
If people manage to get around that and ask how to make chicken casserole, you know, good on them. You know, it just costs us a little bit more money to run that. But, you know, it's their platform. If they need to do that to win over a prospect, you know, maybe it is something we need to allow.
Richard Walker: 09:03
Yeah. They're starting to send out custom recipes to their clients. No, actually, I mean, I used a silly example, but I mean, what if Finn gets into the role of actually advising? How do you make sure it's not breaking compliance? And, and some of the things that we really care about with advertising and messaging and other things like that.
Mitchell Bratina: 09:23
Yeah, that's, that's a really good question. And one that we get from a lot of our prospects, you know, where are the guardrails not only to prevent users from misusing Finn to do things within the platform, you know, gain unregistered access like you were mentioning, but how do you keep advisors or users from falling into the trap of letting Finn do the things that really an advisor should be doing. And it is a tricky one. I think we try to remove the ability for it to do that wherever we can. So an example within the FinTurk platform is our portfolio solver capability.
What we're trying to do there is, basically, find the hybrid between model portfolios and completely custom portfolios. And you can talk to Finn and say, you know, John Smith needs $5,000 in his taxable account for a purchase he's about to make. We don't want to realize any taxable gains. And, you know, we need to make sure that we don't take anything out of his large-cap allocation. You know, just a simple example.
Fin is able to take that natural language and then translate those into constraints that get run through a deterministic calculation. So Finn is not actually proposing any trades. It's just taking the human language and turning those into inputs, into a system that we've built that has no AI in it. So from the user's point of view, you know, Finn proposed these trades, but from an SEC and compliance standpoint, all of those trades were produced deterministically. You know, there's no AI involved in the calculation part of the equation.
Richard Walker: 11:14
You know what I love about this? I've been saying to people that I think the future of AI is really going to be translated to software with judgment. Because when you say deterministic, you're really saying traditional software, one plus one always equals two in a calculator. Right. And so you cannot the inputs and the outputs are always going to flow the same way.
AI is probabilistic. It's just got this ability to think or do or rationalize, etc.. And so I say software with judgment because you're putting the constraints around what the AI can do within the confines of your software, and it's enabling this experience to feel like, oh, I'm just talking to my computer and it's doing all this stuff. But the reality is it's calling a bunch of software to do this stuff. Okay.
This also leads me to another idea. You know, we got off on the AI native first principle of a CRM and most CRMs are about, oh, I got to manage my contact information. And now you're bringing up portfolio stuff. How expansive is FinTurk? What are all the things you guys are doing?
Mitchell Bratina: 12:11
Yeah, a ton. The rule of thumb that I tell everybody is if a feature or a product is already implemented 70% of the way by the CRM that we've already implemented, then that's a feature that, you know, we'll consider building. If it's, if it's larger than that, you know, somebody else is already doing that better than we are. And, you know, we'd rather integrate with them than try to rebuild that from scratch, you know, and then we're, we're getting outside of the realm of our expertise. So that 70% number is where we we gauge whether we want to build something.
But on the portfolio side, that was actually a tool that I had already built a long time ago before the CRM. So it's a little bit off of the CRM route more than some of our other offerings. And we've, we've just extended that and included that in the CRM platform, but things like, you know, a meeting assistant or a note taker, if you have the fields in the CRM, if you already have an AI assistant, if you have an integration with Zoom, you're, you're really 90% of the way there. And so, you know, we do have the meeting assistant built into the platform, you know, automation, construction, external facing forms, things like that. If you want to embed a form that you've made into your, your company's website that roots into FinTurk, you know, that's something you could do.
Richard Walker: 13:34
So like lead capture stuff.
Mitchell Bratina: 13:36
Exactly. Yep. And then, you know, use that in your automations, use that in your CRM.
Richard Walker: 13:42
Okay. Man. So, you know, if you, if you're, if you're talking about a modern day CRM, which is a lot of things to a lot of people, how do you draw lines of competition in your world? Like, are you competing with Xbox because they're doing great note taking because you have a note taker? Or is it just like you can do 80, 90% of what they can do, therefore you don't need it?
I don't, I'm just kind of curious how you see the competitive landscape then.
Mitchell Bratina: 14:08
Yeah, I, I think it really is the latter. If somebody is completely focused on, you know, a point product, I think they're going to be able to do that point product in isolation better than somebody who's, you know, jack of all trades or jack of a few trades, I guess. But if you can, if you can offer something that's 80 or 90% as good as that point product, but include it in a comprehensive experience and, you know, included in the CRM included with all these other tools that work together. I think the overall experience ends up being better for the advisor than having that point product in a segregated CRM or even a point product in an integrated CRM, because there's just so much more you can do when the foundation is all in one place.
Richard Walker: 14:58
Yeah. All right. I want to ask you a different type of question because I'm thinking about this. You were a financial advisor turned technologist. Did you have a technology background?
This is a short question. Did you have a technology background going into this?
Mitchell Bratina: 15:09
I did, yep. My background, my education is computer engineering.
Richard Walker: 15:13
Okay. That's awesome. Man. I was told in college, take engineers and make them lawyers. Best lawyer, make the most money, right?
Take an engineer and put them into financial services, especially like investment banking. Totally different perspectives. Like that background is amazing. Maybe I'm biased. I have a technology background.
Became a financial advisor, you know, myself, and then went back to tech. But, you know, I've been building software for 24-plus years now. And I know what it was like in 2002. I mean, I went to bookstores to find books on how to code. I didn't have online stuff telling me, just samples and all this stuff.
But here we are with AI, and I'm just wondering, do you actually understand how fast you guys are moving? Because your AI-first, compared to traditional software businesses, do you have a sense of what that really looks like?
Mitchell Bratina: 16:08
Yeah, I, I feel fortunate that I had to go through all of the, the education and even really the early parts of some of the tools I built that became FinTurk before AI and AI-enhanced coding came out because I, I got to learn the, the struggle of that. I appreciate what AI can do now. And I think that this could lead into a conversation about build versus buy, because I think that's a pretty hot topic right now. But I think there is something to be said for people who had to build prior to AI. Just having system design knowledge that a lot of people vibe coding don't have.
And so you're thinking of things that the AI isn't thinking of, and it's not really the fault of the AI. It would be the same if you were trying to communicate an idea to an engineer, and, you know, they can't read your mind and think about all the future features that you want to have and be able to build the foundation that will be able to support that.
Richard Walker: 17:10
Yeah, I mean, my own experience, because in the past over a year now, I decided I needed to understand agentic coding. I still have not written a line of code in a decade-plus. I just looked at it as, like, I've got these amazing elite developers who can do my work for me. And when I started out, and I was the only developer, I did stuff over the weekend, and I introduced new features overnight, and it was amazing. Like, hey, I, my mom was my partner.
Look at this new feature. Boom. It works. It's out. An AI has brought us back to that point.
Whereas, as an individual or a small team, you can have new features overnight, same day in some cases, just because it goes so fast. What do you think this means to, you know, legacy software companies versus what you guys - I mean, you don't have the market share yet, right? You look at the bigger CRMs; they have the market share, they have the entrenched customer base. But if you keep moving faster and building more and more, how are they going to keep up? Where do you see this going?
Mitchell Bratina: 18:08
Yeah, I think there is going to be a leveling of the market there. You know, smaller groups that have smaller design teams are able to come in and build things out that are, you know, meaningfully good for these advisors for, for really any industry. And I think you and I chatted about it when we had our nerd out sesh. I think larger engineering teams are actually going to become a disadvantage because the communication across a team of human engineers actually slows down the engineering process. Whereas, you know, a team of one or a team of two or a team of three, I think, is going to be able to get more done leveraging AI than a team of eight.
So I think, I think really those incumbents are going to be at a little bit of a disadvantage to shipping things as quickly and efficiently as those smaller teams.
Richard Walker: 18:59
Yeah. I don't want to ask you about the details of our conversation before we started recording, but you had said something to the extent of you could spend an enormous amount of time planning before you ever let AI start building. And my rule is to plan ten times harder, ten times more effort and planning than actual building. And it's frustrating. Like, hours and hours and hours go into plan.
And then AI is like ten minutes. It's done. Like, wait, wait, wait, how'd you do it so fast? Well, of course you did the planning, right? Yeah.
I think, you know, the way I look at my own team is they're learning how to use AI to go faster and faster, but I actually want to train them in a different mindset. I want them to be their own unit of work, meaning they take a product, they take a feature set, they own it, they own 100% of it end to end. And what I think might become the limiter is product planning. You know, having ten engineers who can't go fast enough because you don't have enough product to give them, I think will become the limit.
Mitchell Bratina: 19:57
Yeah, it's, it's that it goes back to being able to think through, conceptualize a system, and design and plan that rather than just writing code.
Richard Walker: 20:08
Yeah. But if that is the more important skill and you, but you don't have the systems thinking, how do you succeed if you're just vibe coding your way through this, right?
Mitchell Bratina: 20:19
Yeah, that's, that's the million-dollar question, right? I think there's a huge, huge industry for Products for coders. And I think eventually they will enable coders to create some meaningful products. And you're already seeing some. But I think there's still a gap there in the systems design portion.
Richard Walker: 20:43
Yeah. For sure. All right. Let's spin our heads a little bit towards the future because you had mentioned to me something that nobody has really talked about. And this actually comes back to what's happening.
Like, anybody in marketing can vibe code email campaigns now. And so you had mentioned, like, how do advisors handle this new influx of content they're receiving via email? That's AI-generated. How do you know it's coming from a customer? And what are you guys doing about that?
Mitchell Bratina: 21:13
Yeah, I think, I think the subset of that that I've been thinking about the most is what an advisor should glean from a client or a prospect sending them an AI-written email. You know, I think most people are pretty good at recognizing AI-generated content. Now, you know, there are some clear indicators there, especially if you're not trying to avoid detection, which, you know, these clients really aren't. Why, why avoid detection when you're sending that email to your advisors? And I think that the two things that really came out of my conversation with my CEO when we were talking about it were: one.
You know, that's a clear indicator to the advisor that there's a section of the client's investment portfolio or their financial plan, or just the advisory services in general, that they don't understand. And, you know, it sounds obvious, right? Because they're asking a question. Obviously they don't understand it. But if they're using AI, they really don't even understand what they don't understand.
They don't know the questions to ask. And so I think that's a very clear signal for an advisor to, you know, try to set up a call with us, understand what that client doesn't know about what they don't know. And, you know, it's an opportunity for them to build that relationship, show that they can be a teacher to that client rather than just, you know, answering the question outright. The second is that I think advisors need to be extremely quick about responding to AI-generated questions from clients. Because if they're asking those questions of you, you know, their natural next prompt to that AI is, well, what do you think about those questions?
How would you answer those? Right. And so right there, they're going to have an answer in hand from that AI. And if it takes the advisor, you know, even a day to get back to them and that answers anything like that. AI's answer, you know, immediately, immediately, that client is thinking, you know, why am I paying this advisor when I can get the same questions answered in the same way by an AI much faster?
And, you know, I think there's a lot of debate on whether that's the correct way that a client should think, but it is the way that they're thinking. And we have to come to where the client is rather than, you know, being frustrated about the way it should be. So those are the two things that we've, we've really discussed on our side. We're, we're working on a few ways to, to help with that process via the FinTurk platform, but it's something we've seen and heard from advisors. We work with more and more.
Richard Walker: 24:11
I think there's a really, really important conversation, and I'm going to admit I'm a terrible customer for my advisor because a, I've been an advisor. It's been a long time, but I've been an advisor and I got my degree in finance, so I know enough. Right? And two, I, I'm very adept at using AI, but I think what a lot of people don't know, consumers don't really understand is how much bias AI has towards them. They're trying to be pleased by the AI.
So if I say, hey, my advisor thinks I should rebalance my portfolio and it means I'm going to have, you know, tax event and things like that, and I don't want to do it. And I'm and I'm expressing fear, anger, frustration, whatever, I'm going to pick up on that and try to defend me and say, oh, no, do it this way, do it this way. You know, and this is actually a true story. My advisor says, hey, you got to rebalance your portfolios here. And the choices are this with these expenses or just choose different mutual funds in the same thing.
So I went to AI. I'm like, hey, here's what I want to do. And I went back and I said, I, I had AI do this for me. I was very honest and like, this is AI driven, but this is what I want to do. And I could tell he wasn't happy about that.
So I think.
Mitchell Bratina: 25:23
Oh, go ahead.
Richard Walker: 25:24
No, I just think it's a challenge because more and more people are going to lean that way and say, " This is what AI told me to do. And so now we have a different psychological problem. You know, as an advisor, you were competing psychologically against market dynamics. Now you're competing against a third-party kind of persona called AI. And so how do you defend, how does the advisor defend their value and their worth and their position in that client's life?
And I think you're right, responding faster, but does that mean they're going to use AI to respond faster?
Mitchell Bratina: 25:57
I think you can. I think you can use AI to help you respond faster. It shouldn't be the response if you're responding with AI, I think the client's going to be able to tell as well. And then again, you know, well, why would I pay my advisor to be a ChatGPT wrapper, you know?
Richard Walker: 26:16
Oh, no. Entirely. I know, I think they're really interesting, and they're, they're challenging problems because you also get into compliance with what you can say in these emails and whatnot. But you know, your number one point: get them on the phone call, talk to them. I mean, this happens all the time.
My wife was frustrated two days ago. Our, our, the person that comes to clean our house was like, hey, can we do something different? And then we found out the reason they want to do something different is not the thing they want to do differently. When you get to the underlying cause, you're like, oh, well, let's solve that problem. Yeah.
And people don't communicate with the problem. They communicate with the solution. And I think that's where a lot of advisors have to focus is on what the real problem is here. What's the real driver of this behavior, and what are we really after here? You know, I've had conversations with others on the show that really talk about financial advice as more psychology than tech.
How are you as an advisor? Did you lean really heavy on tech and metrics and numbers? Or did you see the psychology part of the problem too?
Mitchell Bratina: 27:23
Yeah. You know, even when I was an advisor, I was writing tools for myself, for my, you know, colleagues, for the, for the advisory firm where I worked. So there was a lot of effort that went into leveraging technologies. But I think they were to facilitate the psychological side, the personalization side, the portfolio solver, for example; the early version of that we called the allocation tool. And I think it might even be called that on the website still.
But the reason I built that is that there weren't any offerings in the market to help facilitate completely personalized, by-hand custom portfolios. And that was, that was our approach. You know, we would sit down with the client, we'd really listen to their situation, their fears, their preferences, and then we would use, you know, our judgment as advisors to construct those portfolios. You know, we had lists of like, hey, here are things that we, we do and don't like. Here's why these are cases where they'd be helpful for a client that, you know, kind of meets these, you know, metrics.
But a lot of it was, you know, taking those conversations and using our judgment as advisors; you know, that's, that's what we're there for. And I really did like the relationship side of the business too. You know, I, I do enjoy the, you know, sitting in front of a computer and coding; you know, that's all fun. But the reason I went into financial advising originally instead of going into a career in computer engineering was that I had, you know, a job early on where I sat in front of a computer and didn't talk to anybody for, you know, ten, 12 hours a day and just didn't like that. So having that, you know, psychological that person-to-person relationship was a big part of what I was doing.
Richard Walker: 29:15
Oh, but come on now. You're talking to AI. Now you have that I don't, you.
Mitchell Bratina: 29:19
It's just the same. Yeah, that's a very brave take.
Richard Walker: 29:24
Yeah. Okay. There's one other thing I want to ask about with, with FinTurk, you know, because you guys are so future focused and I don't know if this will make sense, but I think different people have different cognitive models, you know, different advisors think in different ways, and you gravitate towards an advisor for how they behave, think, and show off, etc. Do you think that FinTurk will ever try to help advisors get their second brain built in FinTurk to be the cognitive model, to be better at answering and surfacing problems? Is that something you guys look at?
Mitchell Bratina: 30:00
It is. Yep. So I like that you asked that. It kind of opens the door for me to do a little bit of a shameless pitch on my end.
Richard Walker: 30:08
Do it. I want to hear it, man.
Mitchell Bratina: 30:10
So, when we've built FinTurk. We're all about enabling that customization for, you know, like I mentioned at the beginning, advisors to lean into what they're good at, you know, their niche, their approach to advising. So we have, you know, custom records and field types. We have automations that can be built on those reports and dashboards, custom pages. And so really, you can make FinTurk your own.
We're supplying all of these building blocks that can be assembled in a lot of different ways. And I think providing a service like that, you know, even five years ago or three years ago, it would have just been too much work for an advisor to fully harness and utilize that. But now that we have AI, we can provide those building blocks to an AI that's been instructed on, you know, here's exactly how these blocks work. And then when an advisor comes to the AI and says, hey, I need a way to track, you know, recruiting for other advisors; maybe their business is recruiting other advisors into their, into their advisory firm.
I need a way to track that. I need a way to automate that process. The AI can interview them, you know, get to the root of what they're trying to do, figure out how their business operates in those processes, the pain points they have now, and then assemble those blocks that already exist in the FinTurk platform into, you know, this customized process that fits into the rest of their business and, and really operates in their approach. So we're trying to make FinTurk conform to the advisors' way of thinking. And then there are all kinds of things you can layer on top of that, you know, like AI, self-improvement systems, and, you know, learning the advisors' tones and preferences.
We have a memory system in there. So if the advisor corrects the AI, it'll, you know, remember that next time. But I think, I think there are a lot of people out there trying to create the, you know, second brain. And a lot of those are really for personal use. You know, there's like the open claw systems and cloudbot that were out there.
I think Hermes is a new one that's out now. And we're really trying to take that to more of a, more of an enterprise and a business case for advisors to be able to, you know, take advantage of systems like that in their business.
Richard Walker: 32:37
Yeah, I think you guys are at an interesting position because if you're already capturing notes from conversations with clients, it's not a far cry to say to the advisory team, hey, when you're working on client accounts and you're having meetings together, just record this inside of FinTurk that we get the inside scoop and we learn how you're making judgments and assessments on those portfolios or client accounts, etc. not that you'd expose that back to the client, but then FinTurk can learn how you guys judge problems. Like you get off a call with a customer and you're really nice, but you're actually really kind of upset about it As an advisor, you're allowed to have emotions. Maybe that plays into how you deal with the right clients or finding the right clients. Yeah, man, I gotta wrap this up. Unfortunately.
And because we always go over, you and I could talk for hours; we already have. So before I get to my last question, Mitchell, what is the best way for people to find and connect with you?
Mitchell Bratina: 33:29
Yeah. So our website is FinTurk.com. You can go there, check out the features on the platform. You know, schedule a meeting with us. If you want to shoot me an email, my email is mitchell@FinTurk.com.
So I'm always happy to hear from people. Shoot me an email. And then we're also on LinkedIn, so you can check us out there. You know, we post the goings-on and, you know, some takes on things, which if people like reading and scrolling through LinkedIn, you know, we'll show up in your feed.
Richard Walker: 34:00
Nice, nice. All right. Now I get to ask one of my favorite questions of all my guests: who has had the biggest impact on your leadership style and how you approach your role today?
Mitchell Bratina: 34:11
Yeah. So I'm going to I'm going to say two people. One is Jim Hagedorn, who is the founder and managing partner of Chicago Partners. That was, you know, the advisory firm where I worked. And really my first real boss, I guess, you know, and being able to see how he built the business.
You know, I joined, I think, when Chicago Partners was 2020 people in the office and $ 2 to $2.5 billion in AUM. And then, you know, I their clients of FinTurk; I still interface with them and see them grow to now, you know, they're probably going to be at 10 billion here pretty soon. And, you know, 50 or 60 people in the office watching the business grow, how Jim manages that and the approach to, to, to leading, you know, a growing group of people has been extremely helpful. Interesting.
You know, I'm still learning a ton still. Actually, I'll do two more - if you don't mind, three, three people in total. So the other would be Jack Hagedorn, who is my COO. He's a few years older than me. He has done HR.
His background is in business. You know, I didn't have any business background before FinTurk, so I've learned a ton from him. And then the third one would be Sam Kendry. He's the founder of Wealth Feed. Not sure if you're familiar.
They do lead gen, but for advisors. He came out of Chicago Partners a few years before I did, too. So he's kind of been like right ahead of me in, in the in the path. And I've been able to learn a ton from him as he's been going through a lot of the same, you know, business struggles and fixes to those problems that I'm experiencing now.
Richard Walker: 36:08
Oh, that's outstanding. It's so great to see people that you can follow and learn with. That's awesome, man. All right. I want to give a big thank you to Mitchell Bratina, founder and CEO of FinTurk, for being on this episode of The Customer Wins.
Go check out their website at FinTurk.com. And don't forget to check out quickforms.com, where we make processing forms easier. Hey, I hope you enjoyed this discussion. We'll click the like button, share this with someone, and subscribe to our channels for future episodes of The Customer Wins. Mitchell, thank you so much for joining me today.
Mitchell Bratina: 36:40
Yeah. Thank you, Rich. I look forward to chatting again.
Outro: 36:44
Thanks for listening to The Customer Wins podcast. We'll see you again next time. And be sure to click subscribe to get future episodes.
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