A Conversation With Fernando San Martin and Gokul Ramanathan

In this episode of the Only Human Podcast, host Yohance Harrison is joined by the Hazel team from Altruist Financial to explore the evolution of Hazel AI, its integration with Altruist, and the future of AI-driven wealth management. The discussion covers the birth and growth of Hazel, the importance of security and privacy in AI tools for advisors, and how technology can help financial professionals stay human while scaling their impact. The episode also features the signature "Marry, Divorce, Date" segment, offering candid insights into the fintech landscape for advisors. If you’re a financial advisor seeking to optimize your tech stack and leverage AI for efficient, personalized client service, this episode is a must-listen.

Links Mentioned:

hazel.altruist.com

Altruist Privacy Policy

Linkedin-Fernando

Linkedin-Gokul

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Transcript

0:02 Yohance Harrison: Welcome back to the Only Human podcast sponsored by Money Script, the Money Script podcast. So happy to be with each and every one of you today. As you can see, I'm a little festive today and I have a gift for you all. It's almost like I'm Santa. I'm coming bearing gifts. So if you're an advisor and you are snuggled up by the fire, enjoying some downtime and listening or watching some podcasts here on YouTube, I have a treat for you today. We I have in the studio. Well, technically I'm kind of in their studio, but I have the Hazel team from Altruist Financial. We're going to talk about how Hazel has been implemented. Has been implemented and how advisors are using it to help do better with AI. And I will admit I am a Hazel user. You've probably seen me on a couple of their podcasts and broadcasts that they've had and I've loved the experience that I've had with it. You've also heard me speak about Hazel and a few other podcast as well. So I wanted to get the team here so that we can have this conversation about how you can continue to stay human in this process. So let's just start. Fernando, Google, thank you for coming to join me today. Can you just tell us a little bit about the birth of Hazel? I think it actually started off as a different seasoning. Thyme, I believe is. How is that? How is it thyme? Time, time, time on my hands. Everyone's seen that, that meme where someone has a bunch of time in their hands. Anyways, shout out to Mary J. Blige. So tell us where, where did Hazel come from?

Fernando: Yeah, yeah, I'm happy to take on that one. This is Fernando. I'm one of the product managers at the Hazel team. And the way Hazel started, as you said, was by maybe a slightly different flavor. Its original name was Time. Time like the herb, not Time like Time is money. And it started in May, June of 2024. At that time, someone by the name of Daniel Lanz. He was my co founder and someone I had worked with for a number of years. He's an extraordinary developer. We decided that we wanted to jump aboard a new venture together. We started tinkering with a few ideas and very early on we landed on We Want to. We were passionate about personal finances. We, we both came from a common background at Capital One, the big bank, and also startups such as Truvada, where we were building treasury management software. And both of us have been very passionate about personal Finances, financial independence movements such as fire. And we told ourselves why don't we build something in this space that we're so passionate about. Very early on we realized selling direct to consumer solutions is extraordinarily hard. And we told ourselves what is the next level within this realm that we can have an impact on. And we landed on the Persona of financial advisors. We did some early explorations, we saw the software that most of you on this podcast are using and it became very obvious that there was a clear opportunity to disrupt the environment. So with that goal in mind, we started started working in, as I said, late May, beginning of June of 2024. We're very lucky to get admitted that early on into the prestigious Y Combinator startup accelerator program in San Francisco Bay Area. And we got our hands to working at the beginning. We started with a note taker. That was sort of the wedge that we identified that was really bringing up, freeing up many hours on an advisor's life, right? Most of you are having many clients conversations online and in person and note taking by hand or having someone in the room is very painful, very, very time consuming. And the follow up actions, right, such as sending a follow up email, making sure that you connect the task to maybe your system of record, your CRM, all of that could be largely automated by AI. But we also told ourselves that's only the wedge into this. There is so much more that we can do. We at one point had solutions to create forms to build clients to send documents such as advisory agreements to clients. Over the course of about 10 months, we developed this solution with an increasingly large level of adoption and impact. We had really good feedback and we also started talking with Altruist at about that time, the 10 month mark or so. Very early on we met with Kohl. I think he was actually the first person we met on the Altris team. We also had a chance to meet with Jason, our CEO. And it became very obvious that the synergy was great and that it made sense to combine the work that Time had been doing for almost a year at that point with the distribution and ambition and vision that Altruist brought to the table. So in June of this year, 2025, we decided to combine forces. We rebranded time to Hazel AI, both the domain and everything. And since then we've accomplished incredible milestones from rebranding the entire product, to doubling down on the features that were really making a difference on the advisors day to day, to launching at the biggest stage in future Proof in September that maybe many of you saw to now having over a thousand advisors using the platform and enjoying it in their day to day. So that's a bit of the story. Hope that's useful.

Yohance Harrison: Very. So Gokul, when you were already at Altruist in the technology space here at.

Fernando: Altruist.

Yohance Harrison: Was time or time which turned into Hazel. Was that something that the technology team was looking for or was it something you stumbled upon? Tell me, what was the kind of the birth of the relationship in bringing that in house to Altruist?

Gokul: Absolutely. So just for context for your viewers and listeners, I've been at Altruist now for close to seven years, pretty much since the inception. Worked on multiple products and investing and now working on Hazel, AI and other AI initiatives at Altruist. I mean, within 20 minutes of talking to Fernando and Daniel, it became very clear to me and our engineers that this is a partnership that we want to make happen in some form or fashion and we're very glad we managed to basically make them a part of the broader Altruistry. Right. Like it's not just the technology stack, but it's their ethos, the way they work, their principles, their ethics, all of it. Just like Fernando said, the synergy was just very obvious and very clear right from the get go. The interesting thing is around the time that we were engaging in these discussions and conversations, we had already built a note taker into the Custodial platform. So it was actually we had around four or five different advisors using the note taker within the Custodial app. But then let's just blame it on Jason for the visionary that he is, where he decided this is a product that cannot just benefit those who custody with Altruist but can benefit literally any wealth professional. That's when I think we made the decision of let's see what it would take to build a standalone product that can benefit those who custody with Altruist in very unique ways. But it can also deliver almost like order of magnitude improvements to any wealth professional irrespective of where they custody. Because operational and growth pains are felt across the industry no matter what technology stack you use. Often using the right technology stack really helps and you feel less of those pains and burdens. But we saw a much bigger opportunity here and around the same time that we were talking to Time and it just felt like this was a match that was waiting to happen and so glad that we managed to collectively make it happen. I think Fernando is being really humbled here. He's a two time founder and the first company that he founded has raised over $100 million. And his co founder, Daniel Lance, incredible engineer, shout out to him as well. And there's Eric, who's, you know, leading sales, who's now joined the product team here at Hazel. So very excited to work, you know, with this team and to keep adding to this team and, you know, changing the future of wealth management with AI.

Yohance Harrison: Yes, and we thank you for helping us change the future of wealth management with AI And I, I want to share. First, I want to share a story about my experience with AI and Altruist because, because I had a very, what I like to call a fever dream with Jason five years ago. Not five, no, I'm dating myself now. Three years ago. Well, time is flying in different ways. Feels like five years ago because so many things have happened since then. And then I wanted get into just the, some of the, the, the fears around AI being a part of the wealth management business. By the way, I'm not scared at all. But a lot of our listeners, a lot of our viewers are, so I definitely wanted to address that. But three years ago, when I met Jason in 2022, we had dinner. I actually didn't even know he was the CEO of the organization. I came late to the Advisor Academy and he was the only one left in the room. He hadn't eaten yet because he had been smoking speaking. I hadn't eaten either because I was went to go see somebody else speak at a adjacent function that was happening at same hotel. And so we sit down and I just assumed he was another advisor that also came late. And we're exchanging stories of, you know, how you got into the business. And at some point he was asking all the questions. And then I finally asked the question, how about you? How did you get introduced to Altruist? Which was a silly question to ask the founder. But then he shared with me that he was the founder and I had a little bit of an egg on my face there. I was like, oh, oops, I didn't know you were you. But he was very humble in his response and he respected the fact that I had no idea who he was. And he was able to tell the story. At some point of our conversation, which lasted at least a couple hours, we started talking about technology and he was sharing about how Altruist was going to be a very technology first company and solving a lot of the pain points that we have with custodians in the industry. And he asked me if we started talking about AI because again, this was 2022, so it was still Very early in the buzz word phase of things. But I was aware of it. Of course he was. He said, if you could have a digital assistant do anything for you, what would you have it do? And I said to him, jason, let's say you and I are having a meeting. And the meeting's being recorded, of course, by my digital assistant. And in that meeting I say, jason, once we get out of here, I'm going to make sure we open up an ira. We're going to open up a Roth ira. We're going to transfer over your brokerage account from name to custodian, and we're going to set your beneficiaries as X, Y, and Z. Because all that information has been captured. Why do I have to now go fill out all the applications if everything is there? We have all the information. Can I just get a hey, confirmation. You want to open these accounts? And the accounts open? And I laughed as I said it, because again, it was a bit of a fever dream. Like, yeah, what world is that possible? I ran into Jason yesterday, and he said to me, we are in that world like it is coming faster than you. Than I was willing to believe that it would. And there's a part of that that can be a little scary, can be a little daunting, of, okay, can I trust this system to do what I expect it to do? But there was also a time where we were a little scared about auto rebalancing. There was a time when we were scared about systematic contributions or all the other tools that we have in the investment management space that have been completely automated over the years. Back then, we didn't call it AI. We called it an algorithm, or we just called it a process, a process that would complete itself on behalf of the client to get the result that we're seeking. And I think this is really just the same thing. There's just a bit of the fear of the unknown that comes with it. So for those advisors that are a little fearful about implementing AI into their practices, can we just speak just briefly about some of the security measures that are in place when we're using a product? Of course, you can only speak for Hazel, but a lot of these companies, especially the mainstream ones that are being adopted by the larger RIAs, are passing the test of security. So can you tell us a little about Hazel Security?

Gokul: Before I let Fernando talk about security, can I address one of the things that you said about how you were having this conversation with Jason about AI in 2022? I was hired in early 2019. And my job description had AI in it.

Yohance Harrison: Wow, that is. Save that business card. That's fun. Okay.

Gokul: Yeah. So like I, for context, I'm a trained aerospace engineer and I was originally using a lot of machine learning and advanced sophisticated like statistical techniques in aerospace engineering. And then I moved to being.

Yohance Harrison: Wait, wait, wait, wait, wait, wait, wait, wait, wait, wait. Okay, I'm sorry, I have to stop you. You are aerospace engineer.

Fernando: That's right.

Yohance Harrison: Oh, I have to insert joke here. Gokul, this isn't rocket science. Go on.

Gokul: Yeah, so, yeah, that's where it began like more than a decade ago. But then I moved into finance, especially being a quant in JP Morgan in New York. But then I figured that I didn't like, really, I wasn't set to or cut out to work in like a larger organization. I was like very interested in being very scrappy and you know, rolling my sleeves up and really making big impact. And I moved to San Francisco and I was like looking for opportunities. And then altruists reached out. So they had the idea of building an AI first product. Right. Like for financial advisors, an AI First Custodian and incorporating that right. Into the, you know, the fundamentals or the heart of, of, you know, the architecture of a custodian, if you will. So Jason has been thinking about it for way longer, you know, than I think anyone has probably been thinking about this in the industry. Right. And.

Yohance Harrison: Oh, I believe it. Absolutely. Yeah.

Gokul: Yeah.

Yohance Harrison: We're to come up in conversation in our first interaction that he's bringing AI and I, when he said it, I was like, this guy. Guy is crazy. But yes. I couldn't believe I, I was shocked to hear those words out of the, the. The sea suite of a custodian of. We want to find ways to adopt more AI And I viewed it as, as this is how we help more people. This is how I make less mistakes. You know, I, I trust my AI system on my sprinklers at home because if it were left up to me, I would either over water or underwater all the time. No, let the AI handle it. It sends me the message, hey, it's really windy today. So instead of starting at 7, we're going to start at 4. Cool. Know what I would do is like I'd have it on in the wind and water be blowing all over into my neighbor's yard. But I trust the AI is going to get it right. And I'm. Now, do I also have to put some input? I have to. Yeah, I have to do some. I Have to tell it based on my soil. It doesn't know my soil until I tell it my soil. It doesn't know the type of grass I have until I tell it the type of grass I have. It doesn't know whether it doesn't. It also can't see my yard. So it doesn't know whether this is a flower bed or this is a grass bed. So, yes, I have to give it some data so that it knows how to interact with me. But then after that, it can use what it knows about the environment that is paying attention to. To do a better job than me. It doesn't take me out of it because guess who still gets to enjoy having green grass? Me. So I hope that advisors can start to think about AI in the same way. And this is the way Jason, and this is the conversation we were having three years ago of he was saying, this is not to. The goal was never to replace. The goal was always to enhance. The goal was always to give advisors the ability to help more people. I mean, let's talk about what used to be our competition. Call it Robinhood. In our space, Robinhood was the do it yourself. Well, guess what? Robinhood now has a platform, a custodial platform for advisors, because Robinhood's. Their mission is to democratize access to markets. And they realize that not everybody wants to be a do it yourselfer. So he said, well, hey, there's all these advisors here that want to help people do it. Let's give them a platform as well. And I believe that Jason thinks about this in the same way. So I'm excited, really excited. And that's why I've done so much work with the Hazel team, because I want more advisors to have access to this so that we can do more good as a whole, for society as a whole.

Gokul: My favorite saying is AI is not here to make humans unnecessary. It's here to make humans unstoppable.

Yohance Harrison: Drop mic. What was the. What's our moment in this? I don't know. I lost the timer. 18. 18 minutes. There it was. 18 minute mark. You got that? Continue.

Gokul: Yeah, no, I.

Yohance Harrison: This is.

Gokul: This is a subject I'm really passionate about. I could speak about this for hours, but. Yeah, I mean, I totally agree. I think that's the benefit of someone like Jason who's not just a. Who's just not just a visionary, but who's also a technologist and most importantly, also an ria. He's done these things before. He has felt these pains. And I think if you're A technologist on top of that. It becomes very obvious to you early on, why isn't that a better way to do these things?

Yohance Harrison: Right?

Gokul: And that's when I think you, it's rare to be one of these things really well, but it's even rare to, you know, combine all of these things and be one person, you know, who can, who can, who can make such a big impact. But yeah, I mean, along with the power and the potential of AI also comes, I think, like you said, questions and concerns around like, is this secure? You know, what does this mean for, you know, my data, my privacy, my clients data. And I think Fernando has like done some incredible work along with the team on that front, which I will let him speak about.

Yohance Harrison: And by the way, we'll put a link to the security disclosures that Fernando will speak to. There'll be a link in the show notes for those of you that are cuddled up by the fire. You can go ahead and click on those now. If you're driving, please wait until you're not driving. But we'll have those links so you can go do that research for the folks in there that want to learn more. But Fernando. Yes. Speak to us a bit about the security protocols that Hazel has in place to protect our clients, to protect data and ultimately just protect the advisors as well. Because this is a CYA business.

Fernando: Absolutely. We recognize the important, the importance of strong security practices when it comes to your client's information. And I would say I would make two distinctions here. One is that are you concerned about the accuracy of, of the AI and the AI is doing good work and to appease that concern, which is very valid and I'm sure many of you have. What I would say is that first of all use the technology and see how it works and I think you'll see how the output is generated is very often brilliant at a PhD level in many of the topics that you're dealing with. I use our most brilliant engineers within Altruist use AI to help them code or to help them write tests. And it's not that they cannot do that, it's that they could be focusing their time on more value at task. And the way AI does it gets them 90% of the way there. And the stamina problem, the focus problem, you don't suffer when you're using AI. If we're thinking of if you have a nest thermostat at home or if you've seen self driving cars because you're in a city such as San Francisco, those technologies are very effective and they're powered by AI just like Hazel is. And very often they're more secure, for example in terms of self driving cars when it comes to accidents per mile driven. So in many aspects AI has already surpassed the human level. Yesterday we witnessed the release of ChatGPT 5.2. They benchmark across a series of tests and again on many topics from cellular biology to complex math to document instruction across hundreds of pages. They perform at peak beyond a human level or beyond an expert level. So that's the technology we're using. And I think once you use it, it becomes very clear that it's very superior in many ways. It's not perfect, but it's superior in many ways.

Yohance Harrison: And let me, let me pause you for a second there, Fernando. So I again, I'm a Hazel user for those that this is your first time listening and I've been in financial services for 25 years and the specialty of my practice is working with new doctors, specifically ER doctors that are coming out of residency and going into, going into the field or as an attending physician. The majority of these doctors come saddled with hundreds of thousands of debt, dollars of debt. And in the past, thanks to the federal government and a lot of the weird stuff that's happening there, I could just feed their, their student loan into a financial planning tool and then feed that into an Excel spreadsheet and do some calculations. You've probably heard of terms like avalanche, pay down, snowball, pay down, things of that nature. Well now the federal government would not allow a direct feed. So instead I have to download the statement and then take that statement and prior to AI, and this has been going on for about a year, or Hazel for that matter, upload, take that statement, take the data put into an Excel spreadsheet and then manually do the calculations and say here's when you pay your fifteen hundred dollars next week or next month, this much goes on loan one, this much goes on loan two, the rest are zero, that sort of thing. That would be an hour long process of trying to figure that out and let me get one formula wrong as I'm building out the Excel, Excel spreadsheet and everything beyond that's now messed up. I took that information, not even the Excel. I took the statement, put it into Hazel and said here's what I need and here's what I want. And Hazel said thinking for a minute and then started running some calculations. I walked away for a second, came back and it said is this what you needed? And I looked and it was 90% of the way there. And it made, it made one mistake, but the mistake was how I prompted it. And I said no, actually I want you to focus on the. Because I told it the highest interest rate first. So it did exactly what I told him to do. And it was applying the payment to the one that had the highest interest rate. And I said, no, I wanted to focus on the highest interest cost per month, recalculate this each month, rank them and then apply the money, the payment to the one that has the highest interest cost. And sure enough, it redid the calculation and it was right. And I said, perfect. Had it put it into a. Something that I could now display to the clients that, okay, I want to put this in something just for the next two years of payments. It's easy for them to understand. It wrote that I gave it to the client. It might have taken 10 minutes.

Fernando: Which.

Yohance Harrison: Used to take an hour. Again, it wasn't perfect at first, but part of its imperfection was me. It did exactly what I told him to do. I was like, oh wait, let me describe this differently now from there, now I know my prompt, like, okay, now I know how to prompt this properly to get the output that I'm looking for.

Fernando: Yeah. You touched on the second aspect of this technology, which is that you, the user are always in control when it comes to AI. The way you interact with Hazel is very often through a chat interface in which, as you said, you verify the answers, you make sure to prompt it again or to re ask the question or to ask for clarification if something is not entirely clear. When it comes to things like follow up emails for example, or agenda prep, you are always in control of what the output is. So we're never committing any actions without your prior approval. So that's another element to keep in mind when it comes to AI. The second aspect, the second pillar of AI and users data security is actually we are, as far as we know, the industry first in offering this feature and it's called zero data retention. With AI providers that HAZEL is powered by, Zero data retention ensures that these data providers, these LLM providers, AI providers, do not train whatsoever on the inputs or outputs that they're generating. We have that in contractual terms they're not allowed to train any of their models in our information and secondly, they're not even able to persist this information besides the minimal time required for us to access that data, for example, when we send a request to an LLM provider, when you're asking that question, for example, about hey, can I Fetch this interest rate, sure we will make a call to an LLM provider, but that, that information is ephemeral. It'll be deleted immediately upon the request being completed. Meaning that say an engineer within one of these vendors decides to peek at the logs and say like oh, I want to see what, what people are using Hazel for. Well, unfortunately they won't be able to because those logs are not kept anywhere. For that we have to go through a risk assessment and guarantee that their use case is safe. But it also means that your data is extremely secure with us that no one else gets to see it or let alone train their models on. And it's something that even if you're on the paid tiers of other vendors such as, you know, say chatgpt or cloud or these, these type of solutions, you will not, you will get nowhere close to that type of guarantee that you're getting with Hazel.

Yohance Harrison: Oh, those have Gemini. You have to tell Gemini like 30 times that you don't want them to train on your data. Even if you do their signed up. If you have so on the Google workspace, if you sign up for that and then you go to their Gemini, there's a process you go through where you can allow Gemini to see your Google Docs and your Google Drive. And when I say you have to tell it 30 times, not the train, I am not exact. It might be 50. It will constantly, it's begging you, please, can we, can we learn from. No, no, no, no, no, no, no, no, no, no, no. To the point where I was like, I don't, I don't feel safe anymore because I feel like you're going to trick me and say oh, we were learning from it. Do you want us to stop so that. No, that is that zero data retention is very important. When you are opening up again your client sensitive data, your data and not even just your data, it's also your way of doing things. I mean there are some advisors that do some pretty incredible things for clients. It becomes their secret sauce, their trade secret, if you will. And you may not want that to get out for free. And not that it's not okay if people are able to duplicate what you're able to do. But if that's your true differentiating factor, you don't want that to be out there in the world. So that is very important. I have a question on that though. If there's zero data retention and this is just my own young technology brain just trying to understand, then how does my Hazel learn to be more like Me, how is that happening without the data retention piece of it?

Fernando: Yeah, so we should distinguish it into what's an AI vendor on which we have pseudo data retention. And those vendors cannot train their models. They, they cannot look at the logs. For what reason?

Yohance Harrison: When you say vendors, you're meaning chat gbt. Exactly.

Fernando: Transcription solutions. Solutions to help us with document parsing. These are world class solutions. They come from companies based in the US with US servers and everything. But we, we still wanted that extra level of security and privacy. So those vendors do not have access to our information. So that I want to make very clear now in the case of Hazel, we still don't use your data to train models on our, on our side either. But we do have to keep track of your information to present you the experience that Hazel empowers. Right. So when you're asking, when you want to revisit a meeting, we obviously have the notes of that meeting so that you can, you can see them. We also don't do not train or use it for any other purpose than providing you with a service. But the way Hazel learns about doing certain things the way you like them is by keeping track of those changes that you've made. For example, if you have a meeting and after meetings you like to. This is one case that came up with another advisor. He likes to see if upon receiving a compliment from a client, the advisor is following up with a request to for a referral. Right. You can embed this within the Hazel notes, summary notes, the way we generate the notes from that point forward, any type of meeting that you have of that type, Hazel will tell you, oh well, in this meeting, indeed there was a compliment by the client. And indeed, let's say for the sake of the example, the advisor did ask for a referral. That's the way Hazel is learning. And we do in this case persistent those prompts to fulfill this request. But we're not training models on our side either.

Gokul: To add to what Fernando said, Hazel also has very strong data retention controls. So what that means is advisors at the end of the day are completely in control of whether a given meeting, audio, video or transcript is retained in Hazel or not. They can completely choose to not retain this information. Even chat, let's say you have a chat session where you interact with Hazel, you upload a document, you ask it a bunch of questions, you like the output, you use it, you're done with that work, you can literally delete the chat instance and we will delete it from our side as well. We really want to Give advisors and our users ultimately in the control to ensure they can run their practice and use Hazel, or any technology for that matter, that interfaces with Hazel the way they see fit.

Yohance Harrison: So that, that means that if the advisor wanted to be, you know, extra cautious, they could, after they have a meeting that's recorded, they could take that transcript, put the transcript into their CRM database, whether it's a website, Wealthbox, a redtail, wherever they're keeping that information. And instead of it being recallable inside of Hazel, it can just be recallable in their own database if they felt more comfortable or more secure with that database. Am I saying that properly?

Gokul: That is fair. Yeah. We see some advisors to that as well, where you can move this data and information to another database system. It could be a CRM or it could be another data source and then it gets removed from the product. Hazel. We also see some advisors remove or delete audio, video, transcripts included once the notes are generated. So only the notes go into the CRM and then nothing effectively that led to the notes are persisted anywhere across, across any technology source, whether it be the CRM or could be Hazel.

Fernando: Got it.

Yohance Harrison: Got it. Man, this is, this is so exciting. I, I, I, I love, of course, as you can tell, talking about AI and its implementation, so I want to shift gears here. So you mentioned earlier that the AI is not here to replace. How did you say it? You say it's not. It did say it again because, Because I don't want to mess it up.

Gokul: AI is not here to make you unnecessary. It's here to make you unstoppable.

Yohance Harrison: Unnecessary. Unstoppable. I love it. So, out of curiosity, just how, as developers and being on the side of creating this technology and pushing it out there into the field for us, for advisors to use it, how do you see that? Advisors, when it comes to their relationships with their end clients, how do they stay human? Since this is the only human podcast, how do advisors stay human and insert the human element into their interactions with their clients when they're using a tool like Hazel?

Gokul: I think there are a couple of very interesting things here. We've talked a lot about what AI can do so far and what it can do really well. But what AI can't do is bring something like empathy, accountability and kindness, which are exclusively human qualities, to the table. How do you hold AI accountable? It's just going to deeply and profusely apologize and chat. That's about it.

Yohance Harrison: I've seen it do that. Yes. Yeah, it's deep and I didn't feel? I didn't feel that it was apologetic at all. It was like you're just saying that. Yeah, exactly.

Gokul: It's borderline servitude. But it probably comes from the training data, right? More so than anything else. How do you AI can mimic kindness but can actually be kind. Right? Like for instance, we had like an academy event in San Diego last week, right. And there was this advisor I was talking to and he said something that really stuck with me where he knows his clients names by heart, right? Like he doesn't have to look up anything. He knows. This is a Mary, this is a James, this is a Phil, this is a Mike. How does he know that? He knows that because he's worked with him for years. He deeply cares about them, he relates to them. AI would know that only because it's in a database and you remove access to the database, that AI doesn't know really what to do anymore. But then that's not really true for human beings. We really build this personal relationship. I think AI can 10x that client experience can help you deliver a better client experience at scale. The more obvious thing is, okay, if you have a note taker in your product, like in your meetings, you're more present and that's great, that's fine. But that ultimately leads you to building a better relationship with them. Right. The other aspect of this whole equation in my head is there is this dichotomy in wealth management, right? Like where you either have efficiency or you can personalize or customize. You can't necessarily do both. I think that is definitely true pre AI where you build templates around how you do things, you set varied processes around how you do things. If someone doesn't work really well within those processes might not be a good fit and for good reason. It's hard to scale with these two things together. But that's not really. I really question that premise now in the world of AI because you can deliver personalization and customization at scale, right? So that really. So you can take your empathy, right? AI is not going to replace your empathy, but it's going to allow your empathy and your skills to scale across your book of business. So more people who can benefit from your advice have an opportunity to be at the receiving end of it. This is interesting stat I came across McKinsey ran the study, the consulting firm ran the study where they predicted that there are going to be hundred thousand fewer advisors, there's going to be shortage of 100,000 advisors.

Yohance Harrison: Yes. Microsoft did the same thing. Yes, they did Correct.

Gokul: Yeah, exactly.

Yohance Harrison: Which by the way, was going to happen anyway just due to aging. Exactly. We were already on that path because our industry on average is 55 and plus.

Gokul: Exactly.

Yohance Harrison: And not enough new young individuals were coming into the business, coming into the business in a position to be an advisor. They're coming in as paraplanners, are coming in as staff and assistant, but not on the path to have ownership and to be an advisor and have that one on one relationship with the clients. So yes, AI is just accelerating that. But we've been on that path for, for 20 years. We've known about that for 20 years.

Gokul: Exactly. So no, I mean, you basically stole those words out of my mouth, right? Like the two reasons are folks aging and then there aren't as many new people coming into these lead advisor kind of roles or client facing tools, right? Like where they can, you know, serve advisor, serve investors and retail investors. So now with AI, imagine what happens, right? Like it's every advisor has a copilot now, right? And they can, and they can personalize their advice, right? So it's here just to make you better. Right? Something that we're excited about is at Altruist is we consistently keep thinking about how can we deliver using AI and even not using AI in general, a 10x better client experience, right? How do you enable that? And that is not done just through administrative tasks, which are great, which can help advisors save a ton of time. So again, they can do more with less. But also how do you actually help them grow their business better, right? Like if they can sell on average 100 households, how do you help them serve 500 households, right? Like with that same level of personalization, with that same level of care, right? Like how do you make sure, for instance with AI that you remember that for instance, your client's daughter is going to Georgetown in fall and send them that email right on time, that makes them feel valued, that makes them feel like someone is out there thinking about them. And how do you do this at scale? These are some very exciting problems that we really think about, you know, applying hazel to which you will see happening, you know, in the upcoming months. So definitely feel like AI is here to be a co pilot with advisors and not take anything away with an increasing population, an increasing demographic, you know, population where people need more financial advice, financial education, especially given this kind of content that's floating in TikTok out there, right? Like of that together, it's I think a very exciting time to be a financial advisor and especially to be a financial Advisor using AI.

Yohance Harrison: Speaking of AI, the, the building knows that there's not a folk a lot of folks here on a Friday. And so outside of my room, the lights just went off, so got a little dim in here, so I was turning it up a bit. All right, so I, I, I want to kind of wrap things up here a bit. And again, I appreciate both of you, you for your time. This has been a very exciting conversation, but we get to have a little bit of fun. So we're going to do two things. One is we are going to play the game that I play with everyone on that comes on the Only Human podcast. And the game is Marry, Divorce date. So I want you to think about technologies and you can of course be very biased about at least the one you're married to, but I want you to think about advisors and maybe thinking about this more at scale than, than it is down to the particular tool itself. So with advisors, sometimes they're naming specific tools like I'm committed to E Money, I'm not committed, I want a divorce. Or in my relationship with fill in the blank. And I'm starting to date Hazel, so to speak. But if you could think of that, maybe even, like I said, on a grander scale because I know that Jason made a comment on LinkedIn the other day with Michael Kitces regarding the future of CRM tools. Thanks to some of the work that you're doing at Hazel. So, yeah, so let's, let's play. So marry Divorce date. Think technologies for advisors. What do you think advisors should absolutely be married to? What technology or tools should they consider divorcing and then who should they, what should be on their radar to start a dating relationship? Fernando will let you go first.

Fernando: And are we allowed to say names here of companies?

Yohance Harrison: You're allowed to say names? Yes. All they will do is they'll, they'll, they'll reach out, their sales people will reach out to me on LinkedIn and, and say, can we talk about this? Like, sure, yeah, let's have the conversation. That's the whole purpose of this. I'm the ruffling feathers here.

Fernando: Maybe one clarification. You're asking me to say which technology they're married to or they should be married to?

Yohance Harrison: Well, no, you should, you can speak like advisors should be married to or are married to and they should stay married to. What do they need to start planning their divorce and what should they start dating?

Fernando: I think I would approach this exercise from a principal first and I would look at the companies that you're using and whether they have your best interest in mind. The core function, I would say, for a financial advisor is the custodial. And the first question that I would ask myself is the custodial that I'm using, do they have my best interest in their heart? And when I look at companies like Schwab in this case, and how they prey on the business that you're bringing to. To use swap, Right. The clients that you're bringing on and they try to maybe get some of those clients for themselves, I would say that's a relationship that's toxic and that you should switch to a custodial, maybe altruist that's not trying to do the same, whose incentives are to help you and never to compete with you. Right. Dating. I think I would definitely put AI on the arena here. We know it's a novel technology. We know there is room for improvement. But we also have great examples, case studies of how advisors have multiplied their productivity, like Gokul said, bringing that level of personalization across the board. I don't want to put too much of the roadmap here on the table, but we're thinking particularly at topics like report generation across your firm and how effective those would be, especially now that Hazel connects to the custodial side. By the way, many more integrations are coming on 2026.

Yohance Harrison: I'm sorry, Fernando, we forgot to mention that Hazel can do that none of the other AI tools can do yet. So we're going to rewind that back because he said it fast, and I want to repeat it because I'm using it and loving it. The one thing that Hazel can do that the others cannot is custodial integration. Hazel is an altruist product. Now, you can have Hazel even if you're not an altruist client, but if you happen to also be an altruist client, Hazel has. How do we say it has the ability to read data from the custodian. So I can query Hazel questions about my client's accounts, and it will go and read that data from the custodian instead of me having to scroll and poke through the webpage to find it, which sometimes I can. But why do I want to take the time to do it and put it in a deliverable format for the client or tell based on my prompt, tell me. One of the most recent ones I did is I had a client asking about, you know, the market starting to get a little volatile. And they asked, should I be concerned about my concentration in technology? And normally that would be me Going down the rabbit hole to go look and see what they have. I usually have to. Typically I got to pull it from the custodian, go plug it into another tool and run that analysis. Be it nitrogen, be it quanta, be it Qantas, I can't remember the name of, but any of those other tools. Morningstar, what have you. But now I just prompted Hazel.

Fernando: Exactly. We very often think internally of Hazel, as you would think of this layer that connects to all your sources of information, your email, your calendar, your CRM, your custodial. And we make sense of that and expose it through a natural language prompt that you can ask questions to. One thing that we are still not excellent at is firm wide report generation. So if you ask a question such as with whom I haven't spoken in the last 90 days, that's maybe behind on RMDs. Answering that question actually involves maybe going through all of your emails across all of your clients, going through all of the meetings that you've had in the last three months, and checking on the custodial side who's behind maybe on rmd.

Yohance Harrison: Right.

Fernando: And combining all this information into a single distilled answer. That's what. That's the 10x work that Hazel is going to be doing very soon for you. You may have success with this question today if your data set is relatively small, but we want to have 100% coverage even if your data set is large.

Yohance Harrison: Wow.

Fernando: So that's the sort of technology that I would start dating. So that as these changes come and you'd also have the ability to nudge or influence the roadmap of this tool. Right. We use canny. We rely on Canny for user feedback, feature request. Incredible engagement there. So I would encourage you to join the conversation. And even if you're only using some aspects of Hazel today, and for it to work across the board for you, you need certain things. Please start using it. Please engage with us in the conversation. And things are changing so quickly that even if I look back at the product three months ago, I barely recognize it in a good way.

Yohance Harrison: That's true. Same here. Same.

Fernando: So. So he's dating and he's moving quickly into. In the pipeline. The last thing I would say is in terms of divorce, I talk about marriage. And so for me, marriage will be someone like Altruist. Dating will be someone like Hazel. Sign up for a demo today and you can start. You can take Hazel on a date tonight. And the third thing is who would I consider divorce? I would 

Yohance Harrison: Oh, oh, bars.

Fernando: Okay, yeah, maybe refrain from, from saying names. But if the information is. If when you request your information which is yours, and you don't get it back, it's not your information. So maybe reevaluate that relationship, man.

Yohance Harrison: Goku, I don't, I don't even know if you want to follow that. That's, that's, that's tough. I mean, I'll give you a shot at it, but that man. Oh, I got goosebumps on that one, Fernando. Geez.

Gokul: Yeah, it's a very tough act of what to follow Fernando there. He absolutely killed it. Ditto on who to marry and who to date. Obviously we're biased. No, can't get any of the answer from us. But to divorce, I mean, will say this right? Like this is a great time to divorce point solutions in your tech stack. So think about like specific pieces of software that you're using for very specific applications and use cases and you will see that with AI, some of those things are going to change radically and very quickly in the upcoming weeks, if I may say so, we have some very interesting things in store for our users and for everyone early next year where you'll see Hazel make its foray into tasks that go beyond administrative work, like think taxes or investing or planning. I'm not going to say anything more than that because the more fragmented your tech stack, the more time you spend moving data across, right.

Yohance Harrison: And the more mistakes get made, the more things get dropped or missed and oh yeah, absolutely, that's. Yes, I've experienced that.

Gokul: Less time spent on revenue generating activities and you know, things that can grow your business and less time spent with your family. Right. Like in the spirit of, you know, holidays. So really rethink these points solutions and we will make it very easy for advisors and any wealth professional for that matter to do so early next year. And also one of the questions that I keep getting when it comes to this kind of technology is like, can you help us fill up data into forms and move forms around? The question that I in turn ask advisors and everyone is what are you filling up a form form for? Right? You let us know what is an activity that that form is going into and we will help you achieve that directly. Right. Like that again comes back to like there's a point solution that's helping you do something very tactical around generating a certain kind of a report or a certain kind of like, you know, a document you want to share with your prospect or your client or uncovering certain Insights. A lot of that is going to become incredibly easier, you know, with Hazel, you know, in the very near future. So excited for that.

Yohance Harrison: I am, too. I am, too. So I said two things. One was the married, divorce, and date, and the second was what's coming. And you answered that already. You're giving us a little insight of what we can look forward to. You didn't go too deep, but I heard you flirt with planning, tax reporting, and other administrative tasks, and I can't wait. I just got an email yesterday saying that there was a new beta for me to test inside of Hazel. I've been here at headquarters, so I haven't had a chance to play with it yet. But you know that I will, and I will continue to live by what I shared with the two of you almost six months ago. My goal is to break it. I want to break it. I want to. I want to show you where is it vulnerable? Where is it not working? And I am very grateful for you and the entire Hazel team that every time I've brought something to you, you've shown me how. How I was the problem. Sometimes it was me, which is good. And that. That's good. I need that feedback. Or you said, hey, this is something that we're working on. Here's a timeline. Here's how we're going to make that better. So I appreciate you and the entire Hazel team. Please tell them that I said thank you and I appreciate you. So, again, this was Only Human podcast, brought to you by the Money Script product podcast. My name is Johans Harrison. This is a podcast for advisors. If you happen to be listening to this and you're not in the industry, that's okay, too, because you just wanted to get a little insight. We have Sienna over there saying hello. She's on the sales team. Again, I'm in headquarters, so they're just dropping by. I do spend a lot of work with the Altruist team. I am one of their speakers at the Altruist Academies. I am an Altruist client as well, and my clients are altruist clients. And I do still have few clients over at Schwab also. But that is also the beauty of being an RIA is we. We don't have to be solo custodian. If there's a reason that they need to be at a different custodian, we get to choose to do that. And I think that's the beautiful thing about our business. So I do encourage you, as an advisor, to take a little bit of time over these holidays where you have the downtime and well, or if you're listening this past the holidays, take some downtime, analyze your tech stack, think about how the world is changing around you. Think about how you can stay human in this process and deliver better, higher quality, faster results to more clients. And we will see you next time on Only Human. Thank you, Gokul. Thank you, Fernando. Y' all take care.

Gokul: The pleasure has been ours. Thank you.

Fernando: Thank you for having us.

Gokul: Johannes. I was thinking of covering one thing. I know we're way past time, just.

Yohance Harrison: Oh yeah, go ahead. We can throw it in there. Yeah.

Gokul: So one of the questions that I keep getting, is Hazel going to replace any particular piece of software in my stack and things like that. Ultimately, when we think about building Hazel, we think about Hazel as being a new category in the advisors tech stack. We are not necessarily looking to replace any personal particular piece of your tech stack, but rather we're building the unified intelligence layer in wealth management. Right? Like so imagine Hazel connects to your CRM, to your financial planning software, to your portfolio management software, to your custodial, you know, to your custodian, and can basically help read and access data across all of these data sources and can also help orchestrate actions across all of these data sources. So we really look at a new category of software and product being born here. And like Johannes already said, the beauty of being an independent advisor is the optionality to really do things the way you want to do it, right? So there are certain benefits that will come with custodying with Altruist. Imagine if Hazel is in your calls with your prospects, right? You do your intro, you do your fact finding or your KYC and then you present them with the financial plan and then you want to open accounts right after your financial plan. Like Hazel knows exactly pretty much what it is that you want to do with your prospect and has filled out like 90% of the account opening form. You hit a button, it opens accounts and sends things to your clients and it happens instantly. Right? That's something that we will uniquely be able to do. But we will work very closely with your existing tech stack as well. Right. We will only be fundamentally limited by what the other software providers can expose to us. And we ultimately are building a product for advisors like for wealth professionals in this industry, irrespective of whether you custody with Altruist or not. And we will really integrate with your existing stack and help you grow your business, retain your existing clients, provide them a 10x experience while being profitable and being very efficient while doing so. Right. Like efficient growth. I think that's what we're after.

Yohance Harrison: Efficient growth.

Gokul: Growth.

Yohance Harrison: And I. I'm experiencing it. I. I am. I'm a client. I'm experiencing it. And I have. If you've heard me speak anywhere else you've been on any other podcast. I've given dozens of examples where Hazel has helped me. And actually, I'll give credit to some of the other AI tools. Look, I've been using. I've been using AI for going on two years now. So I was an early adopter and I was waiting on the sidelines for Hazel. Give me beta. Let's go. And since using the tools in mass, I've experienced a much better. I've had a much better experience. Excuse me, with my clients and my ability to deliver advice and my ability to not have to remember everything I used to tell clients all the time, oh, how did you remember my anniversary? I didn't. I just remembered where I wrote it down. That's what I used to say, but now I just could say, oh, no. I also, I did not remember. But I have a tool that helps me to capture the information I need that's important and then reminds me and nudges me when I need to do it. Just like I have the alert that says set out the trash. I haven't figured out how to get AI to put my trash out yet, but I still need an alert sometimes. But I forget it's trash day. And that's like one of the most worst things. The worst things to do it as an adult is forget it's trash day, especially in the summertime. But I need a reminder for that because I'll forget I'm too busy playing with my daughter or walking the dog or working with clients or doing a podcast. So having those tools just helped me to be a better human at the end of the day. So, no, I appreciate that follow up. So again, thank you everyone for joining us for Only Human Podcasts with my guest here, Gokul Fernando from the Hazel team at Altruist. Again, if you would like to start dating, as Fernando mentioned, if you'd like to start dating Hazel, you can start today. There'll be a link in the show notes. You can click that link and you can start dating. And you'll be surprised. The price points aren't what you think. Okay. This is something that's very palatable, that you can again latch on to what you're doing now as a new technology that ties everything together. I was just as you were saying that Goku I was thinking about it, like, it's kind of like the roof of my house. The roof of my house is very important, but I don't want to just live under the roof. I want walls. I want bathrooms and toilets and kitchens and all that stuff, but I also want a roof. And that roof then protects everything that's there. And it touches all corners, all four corners of the house, and is supported by all the beams within the house. And that's how I'm starting to think about these AI tools. It's kind of just, let's put a roof on the house. It kind of ties everything together.

Gokul: The custodian is the house. The AI is the roof on the house.

Yohance Harrison: Yes. There we go. We got it. You heard it first today. All right, everyone take care. Happy holidays. If it's already past the holidays and you're hearing this, then happy next holiday that's coming up. Take the time, review your tech stack and find ways that you can be continue to be a human through this process of technology in the financial services system. Everybody take care.

Fernando: Thank you.

Yohance Harrison: All right. Hey.