[Emerging Tech] How AI Copilots Are Transforming Wealth Management With Jagdeesh Prakasam
- Quik! News Team
- 1 hour ago
- 27 min read
Jagdeesh Prakasam is the Founder and CEO of Qdeck, an AI-powered fintech platform that helps financial advisors automate workflows, analyze data, and deliver personalized client insights. He leads the company’s vision and operations, building technology that modernizes how wealth managers serve clients and make investment decisions. Jagdeesh has a background in quantitative finance and previously served as CEO and Co-Chief Investment Officer at a hedge fund before launching Qdeck. Through Qdeck, he focuses on combining AI with financial expertise to improve client communication, efficiency, and outcomes in wealth management.
Here’s a glimpse of what you’ll learn:
[2:05] Jagdeesh Prakasam discusses Qdeck’s AI copilot for wealth advisors
[4:37] Balancing software and professional services in AI solutions
[7:50] Scaling deployments with agent studio and patented AI architecture
[11:48] Jagdeesh talks about real client results and productivity gains from AI adoption
[15:09] Using AI agents to handle client inquiries and reduce email volume
[17:29] Real-time, context-aware chatbot improving client engagement
[22:14] Guardrails, human checkpoints, and audit trails for AI agents
[27:29] How proactive AI compliance prevents errors before they happen
[32:45] Personal leadership influences and lessons from father and advisors
In this episode…
Financial advisors are overwhelmed by fragmented tools, manual workflows, and rising client expectations for fast, personalized communication. Many struggle to keep up with client inquiries, leading to poor engagement and even lost business. With client retention increasingly tied to responsiveness and experience, how can advisors scale communication and deliver better outcomes without adding more complexity?
Jagdeesh Prakasam, an expert in AI-driven financial technology and workflow automation, explains how advisors can shift from traditional software models to outcome-focused solutions. He emphasizes layering intelligent systems on top of existing tools rather than replacing them, enabling faster adoption and less disruption. Jagdeesh highlights the use of AI agents to handle routine client inquiries, reduce email volume, and provide real-time, personalized responses. By implementing clear guardrails, audit trails, and human checkpoints, advisors can safely automate workflows while improving efficiency, accuracy, and client satisfaction.
In this episode of The Customer Wins, Richard Walker interviews Jagdeesh Prakasam, Founder and CEO of Qdeck, about using AI to transform wealth management workflows and client experience. Jagdeesh discusses outcome-based pricing models, reducing client churn through better communication, and building trust with AI guardrails and transparency.
Resources Mentioned in this episode
Quotable Moments:
“We built an AI co-pilot for wealth advisors. Essentially, what we do is we create an outcome as a service.”
“We go to the client and say, tell me about your advisor journey, and we will recreate that more efficiently.”
“We don’t need you to change a thing. Let me go build that intelligence layer for you.”
“We provide the ultimate audit trail in the business, showing exactly what data led to each outcome.”
“Life is not going to be a straight line. You’re going to face challenges and learn from them.”
Action Steps:
Layer AI on top of existing systems: Instead of replacing current tools, integrate an intelligence layer to unify data and workflows, reducing disruption and accelerating adoption while delivering immediate value.
Automate routine client communication with AI agents: Deploy AI to handle common inquiries and provide real-time responses, improving responsiveness and client satisfaction while freeing advisors for higher-value work.
Implement clear guardrails and human checkpoints: Define strict boundaries for AI agents and include human review at critical stages, ensuring accuracy and compliance while building trust in AI-driven decisions.
Focus on outcome-based solutions rather than tools: Design workflows around desired results instead of forcing teams into rigid software, aligning technology with real business needs while improving efficiency and adoption.
Use client interaction data to drive growth opportunities: Monitor client questions and behavior to uncover interests and needs, enabling proactive recommendations while increasing retention and organic growth.
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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 their focus on customer experience leads to growth. Some of my past guests have included Dr Jon Randall of XFA Coaching, Chirag Gandhi of Mili and Thomas Clawson of Slant, and today is a special episode in my series on new and emerging solutions. And today's guest is Jag Prakasam, founder and CEO of Qdeck AI. 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'm excited for today's conversation. Jag Prakasam is the founder and CEO of Qdeck AI, an enterprise grade, AI powered platform transforming how financial advisors operate in the front office.
AI serves as an intelligent copilot, combining patented finance native AI with real time data, portfolio intelligence and compliance ready outputs to help advisors move faster, reduce risk, and deliver better client outcomes. Jag, welcome to The Customer Wins.
Jagdeesh Prakasam: 01:44
Hi, Rich. Great to be on your show.
Richard Walker: 01:47
I'm excited to talk to you. So for those who haven't heard my podcast before, I love to talk to business leaders about what they're doing to help their customers win, how they built and deliver a great customer experience and the challenges to growing their own company. So, Jag, I want to understand your business a lot better. How does your company help people?
Jagdeesh Prakasam: 02:05
We build an AI co-pilot for wealth advisors. Essentially, what we do is we create an outcome as a service for wealth advisors with the power of AI.
Richard Walker: 02:17
Outcome as a service. Does that mean pricing? Or does that mean like there are specific outcomes that the advisors are asking for you from you?
Jagdeesh Prakasam: 02:24
Exactly right. So unlike a traditional SaaS world, you know, software as a service world where a vendor or a product creator comes up with a vision, creates a product and forces the customer to fit into that product and run their business. What we do is we go to the client and say, tell me or talk to me about the journey, your advisor journey, and how you orchestrated it today. And we will recreate that in a more efficient, productive way for you. And that's why I call it an outcome as a service.
Richard Walker: 02:57
So does that mean you're re-architecting their entire internal systems. Are you getting rid of their CRMs? Are you making them work better? What does that look like? Most of the time.
Jagdeesh Prakasam: 03:06
That's a good question. And many times that's always the fear, especially in the wealth world, because in financial services itself, you know, systems, a change of system always opens it up for risk, you know, especially when dollars and cents are involved are going to miss a transaction or what have you, right. So in this particular case, that's not how we're approaching it. Some of them have a blank slate. You know, they're long overdue for a tech upgrade.
So they might adopt a completely new sort of architecture or framework. But in most cases what happens is they have an existing tech stack. They like a few things and they are open to changing a few things, or they say, hey, this is my tech stack. Create me an intelligence layer over it that I can just interact with one dashboard across all of my eight different subscriptions. The average number of subscriptions a wealth advisor has is 8 to 9.
And it's a little overwhelming sometimes because all this data is siloed behind these different, you know, point solutions. So that's where we come in and say, we don't need you to change a thing. Let me go build that layer for you on top of it.
Richard Walker: 04:22
Wow. Okay, look, I gotta tell you, my impression is that this is consulting and professional services versus just straight up software. How much of it is just software that gets installed and figures it out versus you guys doing custom bespoke work for every, every client?
Jagdeesh Prakasam: 04:37
So it does feel that way. And as you can see today, you know, cloud is creating a professional services division. You can see OpenAI went down that path of creating a professional service because after a certain point, especially with AI, anytime you go, you know, even us, you know, when we go on cloud or ChatGPT and prompt it or ask a question. We are so free flowing. We wanted to understand what we want in the way we ask for it.
We are not using Excel like, you know, the drop down menu and going into some point and doing the calculation there, right? We are essentially doing that. So that's the expectation really. So there is no choice but to have that professional services piece with almost all AI companies today. And the way we have tried to, you know, there's always a risk with that, right?
Because you always think, hey, is it going to be expensive? Because now you have this, how do you scale yourself? You know, there is a balance there. So we have a core technology, which is a hybrid rag process, which we have patents for. We have a couple of patents on it.
And the reason we created that is we wanted to create a trust layer. So our claim to fame, as you know, I'm going to make a small marketing pitch here, which said that we provide the ultimate audit trail in the business, right? So we say, you know, anything that we look at, any piece of data that we look at, once we use it to come up with an outcome for you. We give you an audit trail and also tell you what exactly did we read in that particular piece of data that may have made us make this claim. So this is something you can archive.
You can verify what you have, whether it be public data or your own private data, right? So that's the core architecture. And then above that, we have an agent studio that we build agents for different sorts of advisor journeys to help with those journeys. But that's how we are scaling. So, the way we do it is that it makes the scaling process a lot more manageable, rather than a purely professional services team that is doing custom work for every advisor we scale.
Of course, if the client is large enough. Sure, we went to the point where we do have to do custom work. But for most cases, the agent studio's got.
Richard Walker: 07:10
That's cool. Look, you're bringing up really fascinating things in my head. I want to talk about pricing. I want to talk about the value. I want to talk about the workflow.
But just to make sure I get this, I mean, you have this foundational piece of how you're managing data. Do I recall the Q stands for quant that you have a quantitative background, right. So you understand data really, really well. So you have that foundational layer. But then you also develop this agent studio.
So you can build agents really fast effectively to do the work that you want to do. So if that is coming together, that means your professional services engagements may not be very long. I'm presuming.
Jagdeesh Prakasam: 07:50
That's right. So we are in the range of 6 to 8 weeks at most 12 weeks. In certain elaborate cases, if the number of users are larger and more integrations are required. But no, it's not that much more. And beyond that, it's a support fee and a licensing fee.
That's it.
Richard Walker: 08:11
Okay. And are these handling entire workflows like movement of data and making decisions and operational, etc.?
Jagdeesh Prakasam: 08:19
Yeah. So see, there are two ways to if you're an advisor today, right? There are two, two different pitches sitting in front of you. One is something like ours who comes to you and says, hey, I can do a short term professional services engagement, and then I'll get you to where you are and support you and charge you a license fee. But the other one is there are just pure consulting firms who come up to you and say, hey, let me go do it, and I will continually build it for you.
The incentives are very different for both these things. In our case, we have a product. We are trying to make sure that we can meet you where you are. You can think about it like we see ourselves as, you know, like what Uber did to cab hailing, you know, like in the past, in the old days, what we would do, we would go to a hotel or some sort of a, you know, airport or some location, some hub where we can find cabs and, you know, flag one down, right. But they did a simple thing.
They met their clients where they are. That's all there was. They found a point where they could say, hey, this is my location. Hey, you know what? I'll come meet you right there.
Right? That's how we see ourselves. So that is how we are saying, hey, we have a product here, but we can meet you where you are and customize it, but you don't need to be engaged with us on a professional services basis for the rest of your existence. Right? Yeah.
And you go to a consulting arm and things like that. The biggest challenge sometimes is your face. Let's say they put together this, you know, why are you up and the way you want it to be done? But then they have to be continuously engaged. And most firms are not technology firms.
They're wealth management firms that use technology to deliver great outcomes for their clients. That's it. They're not looking to innovate or create patents or anything like that. They're not trying to sell a wealthtech platform. Right.
So there's a difference.
Richard Walker: 10:23
Shouldn't be they shouldn't be building their own software is what you're getting at, right? They're not trying to innovate. They're just trying to do the business they have to do. I love that you said it this way, that you're trying to meet your client where they are, and that means where their tech stack is with their current state is, you know, how their processes work, etc.. And I love that because that's just one of the ways in which AI is making new things possible, right?
Because you're really unlocking the speed, the compression of time and the Creativity through AI to actually accomplish these things really fast. So let's talk about this now from an outcome standpoint, I'm assuming there's a professional services fee, but so they're paying for the outcome of that professional services fee.
Jagdeesh Prakasam: 11:06
Yes there is. There is a professional services fee, but it's short lived. So, you know, you can kind of do, you know, two months or three months, that's it. It's not. And especially if you're getting into a contract that goes on, it's not priced in the traditional sense of a professional service because we are customizing those agents on our tech to be delivered for a longer term, you know, support licensing contract.
So.
Richard Walker: 11:33
Right. Are you finding that customers are seeing that you're doing things they couldn't do, or you're doing it ten times faster than what they would have done? I mean, what kind of results are you actually hearing customers talk about?
Jagdeesh Prakasam: 11:48
No, absolutely. So, you know, I can give you two cases that come to mind on a live client basis. So one of the things is, and I'm sure you read these stats rich and, and, you know, a lot of the, a lot of the clients that have left their advisors, the churn rate, you know, if there is a poll out there, you can look it up and, you know, they did it actually nicely. They did it across your asset, your net worth or whatever is with the advisor, right? So it was 100 K to a million.
And then there were 1 million to 5 million. And then there were 5 million to 25 million. So there were three cases. They said, let's go ask them. It was an exit survey or people were changed.
It was a wider survey that said, why did you change your advisor? Right. And many times. The majority of the time it was client service. client communication, 60% of them said it was due to client communication or lack.
Richard Walker: 12:59
Thereof.
Jagdeesh Prakasam: 13:00
Or lack thereof. So they were not, you know, they were not getting enough communication from their advisor. You have to remember, we are living in a, you know, a digital native world. You know, a lot of the people who are inheriting the baby boomer wealth as well are digital natives. So for them, communication is all over the map.
I mean, the amount of notifications all of us get in a day is, you know, I have to turn them off, you know.
Richard Walker: 13:28
I know.
Jagdeesh Prakasam: 13:29
But they're used to it. Right. And, and if they don't hear some level of immediacy in those communications, especially when it comes to their dollars and cents, you know, I think it doesn't matter what it's telling us. It doesn't matter if it is a $100,000 account or a $25 million account, 60% of them across like each vertical. It was like plus or -3% on each category.
But you know that they're leaving because my advisor didn't communicate well enough. So one of the advisors was really early in picking up on this trend, right? Because they were watching this in their book where they said, you know, we send out these bland newsletters or cookie cutter newsletters. I shouldn't say bland, maybe they're very interesting. But, you know, once a quarter or what have you and hope that the topics that we are covering are interesting to our clients, and maybe 10% of the book will come back to us and inquire further.
That shows validation that they're sending you content that's worth reading. You know, this is and many advisors do it differently. They have semi-annual dinner talks and this and that. You know, it depends how you do it. And they were not. They were not getting the way they found.
The satisfaction level wasn't high constantly. They had inbound emails coming from their clients about different topics. All right. And then they said,
Richard Walker: 15:06
And not consistent across the board. Everybody had a different topic.
Jagdeesh Prakasam: 15:09
Everybody had different topics, diverse sets, you know, and you can imagine, you know, depending on, you know, you're a business owner, here you are, you're a professional here. And you can imagine and, you know, family situations are different. But what they found is they found this. It takes a lot of time from a client services perspective to actually dig into the issue, give them a thoughtful response, an actionable response. And 80% of the time they don't act on it.
They just want to know about it. 20% of them are guilty of this.
Richard Walker: 15:46
I've been guilty of this, I get it. Oh, hey, advisor, tell me this. Okay, I'm not going to do anything.
Jagdeesh Prakasam: 15:52
Exactly right. So it's a common thing. You know, you're on the golf course your buddy told you about, you know, a new way of a new investment vehicle or some category. And you said, you know what? I'm going to ask why it is because this is the only space in the professional services that people engage in that is not built by the R.
So, you know, if you're an attorney, you think about it because they're billing you by a six minute increment, right? But this is one of those things. Advisors get hit all the time.
Richard Walker: 16:24
Yeah.
Jagdeesh Prakasam: 16:25
Right. And, and, and it is, and they miss a lot. They were missing a lot of incoming emails. And then they said, you know, this has to be a better way to do this whole thing. And I really want to serve my clients.
I want to improve retention, client satisfaction, but this might also bring in organic growth from my existing book that I already hold the trust with. Right? And this is where we deployed an interesting one, because we deployed an agent client services agent between the actual team and the client, their email traffic automatically dropped by over 50% or more on these kinds of one off requests or even asking questions about investments, what have you.
Richard Walker: 17:19
Hold on. So you said email traffic dropped. Does that mean clients stopped asking or are you saying they were getting back faster? And so the team had fewer to worry about.
Jagdeesh Prakasam: 17:29
They were interacting. So this was a three way communication in the chat engine between the client, the I mean, the client, the client services group or the advisor is on it as well. And this chatbot and this agent, AI agent that we deployed in there, right? Okay. The AI agent was context aware of that client, you know, and they had approved I want to say about 20 different now it's gone up to 200, but 20 different initially on the start, 20 different major news sources that can answer that particular query like licensed news sources.
So we allow for that. We say, hey, you're an advisor, you're in a fiduciary business. You want licensed news sources only and you can pick and choose, you know, depending on your, your client book, you know, how they are spaced and where, which part of the country they are, whatever matters to them, you know, and you can pick and choose. These are the only things I want feeding into my public answers. Whatever I source from the public world.
And here is an access to a private repository of research that we collect or, or create, right? So the beauty of it was they would ask questions to our bought and they it's a white label bot. We power it, but they would ask questions and get answers in real time. So about 50, 60% of the time they got their answers right away. The client services group didn't even have to jump in.
And then every once in a while, if, if it went, if they kept going, we would say, hey, would you like to schedule a call? Which was great. Now it worked like old school cookies, you know, like if you if I went and searched for a mountain bike, you know how it is. The mountain bike would show up in every other browser or any other website.
Richard Walker: 19:24
Yeah, if you're on YouTube and the mountain bikes, they're like.
Jagdeesh Prakasam: 19:27
Yeah, ads are out there, right? So like that. But in this sense, they were able to see they were able to meet their client where they are. They were able to see exactly what they're searching for. Right?
What are they looking for? Because today, if you don't give them away, they're going to be going to ChatGPT directly. This search is happening outside of the purview of the advisor.
Richard Walker: 19:47
Yeah.
Jagdeesh Prakasam: 19:48
And then when that happens, they have no idea the context as to why this client is coming in and asking me about this. But now they were able to see their whole chat history. They can actually see it in real time and say, okay, I get it. And many other times they ended up getting organic growth because they would say, hey, would you like to invest more in gold? Would you like to put in more money?
I see you had a liquidity event. You're looking at, you know, putting some money into different investments. Can I suggest you a few options? It looks like you've been researching, you know, whatever gold or oil or whatever is your flavor, right? So this is where I tell people every client of mine is a co-founder of Kodak.
And it's a simple reason because they tell me what they want many times, sometimes, you know, as a product creator, you can't see all the scenarios because they are doing their business on a day to day basis. They know exactly what the pain point is. And if we can.
Richard Walker: 20:53
Actually you've taken this from a different perspective. You didn't say, let me build a better dashboard. Let me build a better analytics system. Let me build a better chatbot. You said, let me build a studio to create agents, and then we'll build out this bespoke system our customers actually need and want, which actually this is really smart because I have a friend, he just, he just quit his job because he realized more people need consulting on AI enabled solutions than our consultants out there, and he can make ten times the money doing that kind of work versus the job that he had.
So he started doing that. And it's just going crazy because everybody sees what's possible with AI, but they don't know how to do it themselves. And like you said, these are financial advisors who don't want to be technologists. So you're helping do that for them, right? Yeah.
Jagdeesh Prakasam: 21:43
No, that is exactly what you know, what we found would be the best way to interact? Yeah. What we have, you know, we are in the best time in the world we could ever be in, in terms of how we can.
Richard Walker: 21:56
That's amazing. So let me ask you a harder question because, look, I've built agents. I understand agents really well. How are you putting boundaries, controls and making sure the AI agents don't do things they shouldn't do? How do you constrain them?
Jagdeesh Prakasam: 22:14
So we have extremely tight guardrails in every agent. So when we reimagine a flow, let's say I'll give you an advisor journey is a proposal generation, right? Typically this is a crazy stat, you know, and you should help me out here if I'm getting my numbers right. But apparently 50% of proposals from leads fall apart because it gets stuck in some complex advisor journey. Which is crazy.
Richard Walker: 22:48
Was it the paperwork? Was it the forms? Because I can fix that. Yeah.
Jagdeesh Prakasam: 22:52
You know, maybe they should talk to you. You know, this is a partner on this. I'd love to post your forms into that advisor journey. Right. Because we integrate with other partners.
It is, it is.
Richard Walker: 23:03
Let's go. Yeah.
Jagdeesh Prakasam: 23:05
And the reality is, because there are a lot of like a lot of misses, right? When you're, you know, looking at an advisor and if it becomes like you feel like you're having a colonoscopy, trust me, you're out. You're like, you know what? Way too much paperwork or, or back and forth or, or what have you. You want it to be so simple initially, you know, first to get them onboarded, right?
And this is crazy. So we have created these agents. We looked at their flow, which is completely complex because many times it required humans to give them their statements or what have you extracted that data, put it into, you know, Excel or what have you. They would make errors in it. So there are data errors and then it would not compute.
So someone had to verify it. Before you know it. It's like three weeks in you got a lead. You had that, the advisor had that conversation, but the proposal hasn't gone out for three weeks because it's stuck somewhere right before someone picks up on it. So we created autonomous agents.
So we are very careful about creating autonomous agents. First of all, we look at your advisor's journey for a specific use case, and then we say, hey, here is how we would do it, but here is where the autonomous agents would be. And here is where the human gaits are. So we put in the human checks at critical points that we think is, you know, fair to the fiduciary who's taking the risk, right. And also critical in getting things accurate.
You know, getting it correct. So we really ring fence each of the agents. We tell you exactly the scope of it. That's all it can do. It cannot go beyond that.
And then at the back end, we give you a dashboard to track all your agents. And you say, you know, this particular agent is doing great. It has a 100% success rate, but this one only 30%. I don't know what's going on. Now.
You can dig into it and say, okay, you know, this is the reason this fails a lot because for whatever reason, when I'm making it up, let's say a Schwab statement comes in, the PDF is not, you know, picking up because whenever this particular instrument is there in it or whatever it is, the reason it fails, it can tell you that, right? But otherwise it reads through, it extracts the data, you know, administers the risk questionnaire, creates a proposal for the advisor and says, hey, this is what I would do. What do you think? Do you want me to change it? And then the advisor can interact with that before it goes back out.
Right. Yeah. So that's a classic example. But we are very focused on saying not trying to give too much to any agent, you know, not not making the scope so wide that there is a potential for, you know, going out of scope. But also we give you the audit trail.
See, this is where we focused a lot because, you know, the trust layer is very important in wealth.
Richard Walker: 26:15
Yeah. It is, it is. You know, John, since last summer, I've been working on building autonomous software development with AI. And one of the things I immediately saw was I, first of all, I started with a premise. Software is a known thing, like software has been written.
There's tons and tons of examples of it. There's best practices, right? So AI can write software. So therefore, I think AI is an elite programmer, top of the top best programmers out there. What I discovered was that it's also a toddler.
It has shiny object syndrome. It goes off and does things you didn't ask for it to do. It does the wrong thing entirely. And so what I've figured out is how do you control that kind of management scope is a really good way to look at that as well. So but one of the things I did, and I'm curious if you've done something similar, is I put, I call it the hall monitor.
Like when you're in high school, you weren't allowed to go to the bathroom mid mid class, right? There was a hall monitor out there who'd write you up a traffic cop, if you will, but somebody, some agent who's looking at the violations of the agents and their scope. Do you guys mean, you have the audit trail, but is that part of your thinking as well that you're really monitoring it in real time?
Jagdeesh Prakasam: 27:29
Yeah. So we do monitor it in real time in terms of performance and alerts and things like that. We do see. First of all, we define the scope very strictly for each of the agents. It's very simple.
It shouldn't be doing anything outside of that. To your point. You're right. Like if it does anything outside of its scope, there will be an alert on the monitor that says, hey, you know what? This particular agent, there is something wrong with it.
And this is the reason why we think it's wrong, right? Yeah. This is a classic use case, which you've seen in compliance, right? This is the most compliant softwares until today or maybe until tomorrow. They talk about archiving like they would say, hey, archive your emails.
I'll keep it. I will store it. If there was ever an audit or if there was ever a problem that was identified, we can go back and trace it back and identify who is to blame or where the issue was. Yeah, it was never about preventing an issue from happening.
Richard Walker: 28:43
Right? It's all reactive, not proactive reactive.
Jagdeesh Prakasam: 28:46
After the event, you know, it's like and you would think the whole idea of compliance is to prevent it from happening. Because most compliance departments or or groups are internal to the firm, they're invested in the firm, they hold equity in the firm. You know, you are not an auditor. You're not an external person. You're not the police station sitting outside the firm.
You are internal. So you're trying to prevent it from happening. Right. But most softwares, if you see, has never traditionally prevented it from happening. We see that all the time with cybersecurity threats and this and that.
You know, we've gone up that spectrum very well. But in financial services, it's still not a thought process. It's a mindset. They saw that as a friction in terms of if you that that time to prevent that was too much in their opinion that we would let it happen. And then if there was an issue, we go back and, you know, find someone or get hold of someone.
Richard Walker: 29:57
This is what happens in forums. It is like it's easier to let somebody put a mistake on the form than apply rules to the form to prevent the mistake.
Jagdeesh Prakasam: 30:04
You see.
Richard Walker: 30:05
I get it because some of those rules will create friction in the process. Slow it down and the user will cash out of that or not cash out. They'll just bow out of the product and they won't buy it. And I look at it as well. How do you improve that experience then?
How do you make it just part of the experience? And our best customers are doing that, right? They're, they're actually designing workflows to capture the data in the order of requirements. So they don't have that friction anymore. And then it flows to the form perfectly.
So I get it. Yeah. All right. I want to ask you a different question. Oh no, we're running out of time.
But okay, one more. One more question about this. Are your customers seeing you as a potential way to actually displace and remove and not use legacy SaaS products? Are they going that far?
Jagdeesh Prakasam: 30:55
I think it would happen over a period of time, but at this point in time, it's too nascent. You know, it's and it's fine. You know, I think they're more focused, like we discussed earlier, they're more focused about the outcome for their clients because they are not remunerated. They're not going to get a gold star or be given higher fees because you deployed the, the, the greatest technology on, on the planet, right? They're only remunerated based on the returns, the assets, the services that they offer.
And if they can meet their clients, where they are is the only way they're going to get remunerated. Right. And, and that's not been a focus for that reason. And I totally see it. It's actually fine, but it might get there over a period of time.
Richard Walker: 31:46
I agree with you. It's very, very early. I only know one firm in particular. I'm not going to mention the ones that have completely gutted their systems and rebuilt themselves from the ground up, using AI to get the exact systems they wanted. They had the will, they had the technical expertise, they had the money and the time.
And so they did it. And it's an amazing outcome. I mean, they're getting what they want out of their systems and the control to go change it. All right. Before I run out of time, I'm going to get to my last question before I do that, what is the best way for people to find and connect with you?
Jagdeesh Prakasam: 32:20
You can go to qdeck.com or email us hello@qdeck.com, and a team will get hold of you and set you up with whatever you need.
Richard Walker: 32:33
Awesome, awesome. All right. Look, I, I love asking this last question here. Who has had the biggest impact on your leadership style and how you approach your role today?
Jagdeesh Prakasam: 32:45
You know, I'm going to give you two people of course, one is personal and one is professional. One of them is my dad. And, you know, many times you don't appreciate your parents enough when you're growing up, but when you look back in hindsight, you know, unfortunately, I lost my dad a couple of years ago. But when you look back in hindsight, you say the value of the lessons that they imbibed in you. And one of the biggest things is, you know, optimism.
You know, life is not going to be a straight line. It doesn't matter. You know how good your education may be, your, you know, your pedigree or whatever it is, but life is never going to be a straight line. You're going to face some challenges. It's a marathon.
It's all right. You'll hit the road bumps, you're going to have some learnings out of it, and then you're going to bounce back and solve it. And that's what makes it, you know, a rich experience for you. But also that's why people value experience saying, hey, you know what? That person has gone through all challenges and bounced back.
So in the event that this person runs into future challenges, they know how to, you know, bounce back and not panic or come out, you know, completely drop out. Right. And I think his sense of optimism, I was, I was like, I recognize it today. And I sort of, I think have internalized it growing up. So running a startup, as you know, Rich, you've been doing it for a while now and nothing fazes me.
And it's great. I'm comfortable sleeping at night with the uncertainty of what we face every day, you know? And that's all right. On a professional level, it's you know, to be honest, I as I I've had, you know, many people have admired and, and things like that in my career when I was in the quant fund and now, you know, in AI, but I have more. So I would like to focus on someone in the wealth world.
And after I started my startup and things like that, he's actually I requested him to be on my advisory board. You know, his name is, believe it or not, Bruce Lee. Okay. And it's, it's, it's a name you can't forget. Right, right.
And, he's an advisor. He's, and I've met a lot of advisors. They're very focused on, you know, the investment business, very focused, hyper focused on their existing client pool and how they're servicing their business and things like that. But I felt when I met him, and he started understanding my business and the things that he asked of us, he was very visionary in nature. You know, he looked at it, the bigger picture, he said, you know.
How do you bring about all aspects of wealth? And then he's now going towards also bringing in wealth and health together, which when you think about it, are two core pillars. You know, that a human being cares about ultimately, you know, if you only have wealth and no health and it doesn't matter. It is meaningless to you, right? You can, you can tell them I've grown 40% average annualized return for 20 years.
And it doesn't matter if you're not going to survive or if your health is horrible, right? Yeah. And, and he's managed to sort of talk about that vision, but also has been very tech forward. So one of the use cases that I told you earlier in the show here was essentially his request for his clients. And I thought it was phenomenal.
When we deployed it, he had like, you know, first month or second month, he had 40, 50% adoption within his clients and using that. Right. So. And you, you, you, you know, it was sort of an event that opened up my mind to say, you know, there are advisors who, if we spend enough time, you can find those, those visionaries. And I'm looking forward to meeting more of them.
But he's been a phenomenal sounding board for me. And through this sort of process.
Richard Walker: 37:29
Yeah, I love meeting people.
Richard Walker: 37:30
Like that, I really do. I've had many, many customers that have impacted our direction. Our ideas for what we could do challenge us to think harder and bigger about what we were doing. It's remarkable. It's one of the best parts of the journey of being an entrepreneur. So thank you for sharing that today.
All right. I hate to wrap it up, but I have to. So I want to give a big thank you to Jag Prakasam, founder and CEO of Qdeck AI, for being on this episode of The Customer Wins. Go check out Jag's website at qdeck.com. And don't forget to check out Quik! at quickforms.com where we make processing forms easier.
I hope you've 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. Jag, thank you so much for joining me today.
Jagdeesh Prakasam: 38:15
Thanks a lot. Thanks for having me on.
Outro: 38:18
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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