Speaker 1This is a big question. It's in the news daily or weekly. You're starting to watch the big public firms at least hold constant new analysts and associate classes, maybe trim them some. The addressable market question of replacing human capital inside of these firms is a tricky one, and people get on either sides of this debate. On the future of the investment professional itself, I'm not sure I have a stance on it. Knowing that it took me days and weeks to build models and decks, being able to do that now in hours, you still got to digest it and iterate it. It's not perfect. There's going to be some major margin pickup in the junior ranks that we've been using in these industries to process data. We've got a lot of clients who have AI agents sitting in an investment committee to see what it can do and to see what recommendations it makes. Is the investment committee going to be an AI agent? I don't think so, but. Are they going to use it to help?
Speaker 2For sure. I'm Ted Seides, and this is Capital Allocators. My guest on today's show is Ben Harrison, President of Industries at Intap, a leading provider of software solutions to professional and financial services firms. Ben first joined me three years ago to discuss DealCloud, Intap's platform serving the private capital community. Since then, Intap has nearly tripled in size, and the rapid development of AI has created an entirely new opportunity for the business. Our conversation explores what Ben calls Firm AI, moving beyond using AI to conduct research, build models, or create presentations to deploying agents that draw on a firm's institutional memory and execute its workflows. We discuss how AI is changing sourcing and origination, fundraising, deal lifecycle management, and staffing of investment firms. We also cover the critical importance of governance and security, lessons from the combination of DealCloud and Intap, and Ben's perspective on the next leg of growth for the business. Before we get going, you're on a plane headed to an annual meeting. And this time of year, you're definitely on a plane headed to an annual meeting. With all the travel in front of you, it's a very busy time, so I'll keep this particularly short. Before you doze off in the thin air of the cabin, that's a great time to let the soothing sounds of capital allocators fill your ears. And when you find yourself at a cocktail party at one of those meetings, in that uncomfortable moment where you're not sure who to talk to or what to say, that's a fantastic time to tell them about the capital allocators. Capital Allocators Podcast. It's an icebreaker that's the gift that keeps on giving. Since you're at an event, if you've come to one of ours, that's a great time to tell someone you think highly of about our Capital Allocators Summits. Because if you know, you know. Thanks so much for spreading the word. Please enjoy my conversation with Ben Harrison. Ben, great to see you. Thanks for having me. Excited to be here. Why don't we start with, reiterating the core value proposition of Intap.
Speaker 1The company's Palo Alto-based started with a data integration appliance product for law firms 25 years ago. Over the years, the business was built with a series of software and capabilities that helped law firms run and operate their business. Manage new client intake, new matter intake, manage the conflicts, procedure, eight and a half years ago, we merged DealCloud into Intap and that has formed our growth platform. It's a tool to help you prospect, source and originate new business. We've got a full CRM capability inside of that platform. Thousands of clients later, we built some expertise across the risk area, the profitability area, and the growth area of the firm.
Speaker 2Compared to when you last came on the show three years ago, you already had a pretty significant presence in the private equity community with the legacy DealCloud business. What's changed in the last couple of years?
Speaker 1A lot of the company's growth has been taking care of our existing clients and growing with them on top of our core platforms. We have thousands of firms using that platform today. The biggest difference is the size and the scale of the company. We've been growing consistently over the past year, over the past few years we've been growing profitably. It's about $600 million business today as compared to about four or five years ago. The IPO was almost a $200 million company. There's been huge moves over the past few years from cloud to SaaS, SaaS to vertical SaaS, vertical SaaS to AI to vertical AI. The company has been steady. The markets are changing pretty rapidly. What our clients do during the day, the type of solutions that they're looking for, the ways that they're looking to run their firm, and the ways that they're looking to support the professionals who work inside of those organizations, it's rapidly developing. The past two years have been the most rapid pace of change with the introduction of these frontier models. We're almost repositioning our entire stack and all of our products to
Speaker 2be AI native solutions. As you look at that change as a technology provider from the SaaS space, to AI, what are you doing today with AI that you're delivering to your clients?
Speaker 1They have been using our technology and our products to run their organizations for decades. The way that they use those products now have completely changed. The level of automation that we've been able to introduce with Agentic AI is incredible. When you see software executing and moving through organizations without manual intervention, it's amazing. We've all enjoyed the back and forth of GPT and Claude and the question and answer format. When you take the power of those models, you start to deploy them through Agentic workflows in the organization. The level of speed and efficiency that you can drive and supporting the broader company is material. We've been at that concept pre-AI as well. If you look at the original goals of the products, it was to help you run your company and to help you do it better. No matter the platform or the solution, it was to help you harness and manage data, to use that to make better decisions and enable your team. That's what we've been doing with our risk and profitability and growth platforms for a long time. We were introducing automation into those products from the beginning. We have workflow engines that would run automatically if something happened. We were also auto-updating data. I'll never forget the first time, Thompson One Banker add-in for the analysts and the Kappa IQ sync, the PitchBook connector when it came out. We were using API calls to automate data. That was a huge lift in Value Driver because it took some of the manual work out of using software. Most recently, we've been automating proprietary data of the firm. Your systems, whether it's Outlook or email or your internal databases, other software products, Workday, SAP, anything you use to manage the business, it's gonna be full of data. If we can sync that data and auto-update that data, move it back and forth without users of the software having to touch it, you get a big pickup. Most recent one was that RHEL Intel capability where you automated the relationship intelligence of your firm. Ted knows Ben, Ben knows Ted. This is how much we talk. This is how much we email back and forth. Our partners at the organization can see that relationship. They can mine that, use that to the benefit of their coverage of the client. What happened in the last 18 to 24 months with the agentic automation is the biggest step we've ever had in the ability to take the software and run it autonomously for the organization. Today, the super complex workflows, the deal lifecycle management, fundraising and LP management, each of the different areas of the business that have a procedure behind it. We can drive speed and efficiency at a level that we haven't seen before. We're pumped up because we've spent a long time building the client base, building the distribution through thousands of firms. We think the software with agentic AI is more valuable than ever before. -
Speaker 2When you go to update an existing client or you're pitching a new client with the agentic software that you're using, what's an example of some of that workflow that gives someone a total wow when they see it? -
Speaker 1There's an important distinction about Intap, DealCloud, our platform and what it does. If you want to create a pitch deck today, if you want to analyze earnings, if you want to assess a transcript, if you want to come up with an idea for a company, if you want to build an LBO model, the research-oriented tasks, a lot of that today is being led by front end. - Yeah. - It's going to be the front-end models. Going to Cloud, take this transcript, take this earnings release, help me come up with a two-page deck, do my analyst research, we think that's incredible where our agentic ai lives inside of these organizations is on the execution of the firm's procedure by that let's say we have a long-term lp investor in our fund or we've spent five years getting to know the management team of this company that we want to invest in usually the history in the memory of the firm sits in a database some type of structured data documents inside of the organization oftentimes that's in our systems if i'm going to go approach a client pitch them a new fund try and convince them to take our capital or partner with us and do a deal if you can have ai draw on the entire history and knowledge of the firm everything you've ever done surrounding that company and that management team you have a specific way that private equity firm x takes your plan your strategy your operating model your pitch against that criteria you're matching those things together and ai output of that is influencing the way that you pursue the situation that you source originate that you manage the relationship that's what we're calling firm ai the ability to draw on the institutional memory of the firm and the ability to use the past the history documents the outputs everything that surrounds that company so that you can be better in that next conversation or in that next pitch you got the frontier models and there's a ton of firms out there that are automating the work automating an analyst model it's amazing because many of us were analysts i certainly was i did the wee hours of the morning the idea that you don't have to stay up all night is awesome we're taking that one level further into the firm's procedure to help the firm run and manage the business specifically how
Speaker 2different does that look from a long-standing existing client where you've been housing all this information and someone you're onboarding for the first time we feel fortunate to have
Speaker 1the 20 plus years under our belt because what happened in that time frame was our clients' taught us how their organizations run we work with 10 of the top 10 private equity firms 10 of the top 10 private credit firms 9 of the top 10 secondaries firms and we have a deep appreciation for the level of complexity of fundraising the investment and deal life cycle management process the process of running those portfolio companies once you're post acquisition trying to drive value the exit as well that level of fluency has made its way into our software procedure these businesses over the years have gotten big they've gotten complex to run we were putting the procedure in with the software up and running scale as businesses it is that procedure that a context aware agentic ai agent can run through learn process and automate where you can get an incredible outcome for the existing clients we have done that in spades you spend years working together you spend years refining the deployments making them better and better and higher value for each firm for the new client maybe that's just a new firm and they haven't built it yet the new firms have the opportunity to skip the line there's never been a better time to make the technology investment because it's never been more valuable it's never been easier instead of maintaining software api or data integrations in the previous era of automation we're doing it in the ai era and that is so much easier than it was a couple years ago it's fun for the new clients this is a whole
Speaker 2new day what are the differences that you see in between a firm that fully embraces everything that's possible in your work with them and another one that isn't at that leading edge the
Speaker 1most common variable between the firms that push the envelope invest the most do it the fastest and become the earliest adopters there's a clear correlation between big enterprises that have the r d dollars that have the internal technical capacity to do it when we look at our client base look at the transition into agentic ai capability the largest organizations on the planet that are the most competitive that tend to grow the fastest and have the greatest resource those are the ones we're seeing go first on our systems today they are your top 10 private equity firms they are your top 10 global investment banks top 10 and 20 law firms around the world there's also nuances that influence that you have some firms that are technologically inclined even if they're a small firm they're running through the openings too it's not just a difference between big and small it's on that technology life cycle curve where you've got the early adopters and we'll cross the chasm and we'll get to full usage or near full usage quickly this cycle goes a lot faster than the last couple if you
Speaker 2were trying to look horizontally below the top firms maybe it's in the large swath of the middle market trying to figure out which ones are more technologically savvy which ones might not be what types of questions would you suggest that someone posed to try to tease out the differences across firms we have hundreds of
Speaker 1enterprise clients we have thousands of middle market clients organizations with 20 to 200 people the technology investors the tnt investors a lot of times the aerospace and defense and some of the industrials investors typically there's a heavy underlying technology component to running and managing the portfolio companies in those investment strategies they're proactive in the way that they run and manage a portfolio company to be in the latest and greatest spot from a tech perspective and they're proactive to do it for their firm as well some of the more traditional industries that don't require the same level of technology expertise to run those businesses those are the areas where they're probably a little bit later adopters and
Speaker 2everything that you see from all these clients investment processes from the data what are some of the trends that you can see in how private equity firms are sourcing deals through the work and the data that you collect on the source and
Speaker 1origination side it has become incredibly important to me as a private equity firm as a private equity firm to be able to incredibly fast and a heck of a lot easier to map the market, research the companies, develop the hit list, and develop strategies against those particular assets. The best firms that are doing aggressive source and origination with a data-oriented foundation are starting with global publicly available data. They're adding on the proprietary third-party market fees, everything they can get their hands on. Usually there's some type of proprietary calling effort or some way for the firm to measure their proprietary relationships and all their proprietary data that exists nowhere else. You bring those three big pieces together on a systematic basis across thousands of assets, and that forms the foundation from which the firm wants to develop a pipeline of opportunities that they're going to try and put money to work against. That's exactly what DealCloud helps with on the front end of the process. Now, instead of researching that and searching that or just doing NLP question and answer with AI, you can build playbooks and agentic co-workers that can ingest all of that and pursue a strategy across all of those assets. I'm on the industrial team. I want the top 10 assets with the highest growth rates, with the most likelihood to trade in the next couple of years that we believe are positioned against these five economics. You can quickly go from thousands to tens. What's the pitch going to be to the company and the management team? We have agents and co-workers helping develop the ideas based on each level and layer of that data. It's the secondary and tertiary layer of that data that form some of the most thoughtful and thorough source and origination techniques.
Speaker 2When you have the potential to bring all this together to dramatically increase the efficiency and the efficacy of what you're looking at, on the other side, where are some of the private equity firms furthest behind in their workflows?
Speaker 1I don't think they're behind in the workflows. If we go through the top 10 or 20 of them, the main workflows are going to start with fundraising. How do I originate my LP base? How do I form a pipeline of everybody who's going to invest in the fund? What's my track record? How am I benchmarked internally against other managers? Do they have my materials? Are we in a diligence procedure with the pitch books, the prospectus, and the DDQs? Are they committed? How are we going to onboard the new LP? What's the procedure for the LPA and the subscription docs? Fundraising. workflow. 20 steps to it. Then you get into the investing cycle. You're going to source originate, you're going to underwrite, you're going to do the modeling, you're going to get through diligence in the data room and the market studies. Then you're going to get to documentation across deal docs, stock purchase agreements. There's going to be a procedure for closing the deal and calling the capital and wiring the funds. Everybody has those. Today, those exist in at-worse email Excel, at-best, we believe, inside of Intact and DealCloud. Some firms have done homegrown systems and capability. Normal operating procedure for a company and a traditional industry, I'm going to manufacture something. I'm going to sell something. I'm going to use thousands of salespeople and high-velocity sales motions to sell thousands of widgets to a buyer, screws. The procedure of running the private equity firm is pretty hard to understand and it's pretty complex. There's a very small number of alternative asset technology providers out there who spent the last two or three decades studying that. We believe that we're one of them. Whether a firm today is running Excel or email or they've got a DealCloud deployment across every fundraising strategy, we can still come in and deploy those inside of the organization. They know the specific procedure for this firm. They can execute it quickly. They can execute it efficiently. They can execute it with a small token spend instead of asking AI to go figure it out. It doesn't have to go into DealCloud. It doesn't have to go into Intact. It can go into other technology solutions as well and run that procedure. If you haven't done all the work yet, it's not like you get a free pass, but putting that infrastructure in the day is easier than it was years ago.
Speaker 2On the relationship side, whether that's the LP relationship side or the deal pipeline side, what are some of the holes that you see get filled when someone starts to work with you that hadn't previously?
Speaker 1The first is capturing the data and information of the existing LP in a way that you can service them well. Ingesting the data around the relationship with the firm, everything that's been shared with them, how you raise money there's incredible pickup on new fund formation, source and origination of capital for the next fund, and the strategy for who to go to, leveraging AI to give you that plan. There's intuition and you've got the relationships, you're going to know who to go to first. But if you're hustling, trying to fill out a fund, we're seeing the AI recommendation on where to go with the highest probability of an allocation, the highest probability to close on the timeline. That helps a lot. We've got integrations with market leading firms in around the LP and institutional LP side. Prequin's an important partnership for us there and has been a leader in that space, working with this fundraising team. When you get into the procedure of the fundraise, this is where some of the biggest pickups happen. Automating the DDQ and the diligence process. We're particular experts in the LP onboarding experience.
Speaker 2How about on the deal side?
Speaker 1Same thing. It centers around what I would call the deal lifecycle management. One of the primary capabilities of DealCloud over the years has been bringing together the global deal pipeline across the firm. First at the fund level and the strategy level. Oftentimes, you're running multiple funds and strategy simultaneously, you're going to want to roll that up to a global fund structure too. You've got multiple investment teams, you've got multiple investment teams, you've got multiple investment teams in each fund. Those teams are going out, source originating, bringing the deals back into the firm, and then they're entering the underwriting procedure of that deal and getting that deal to indications or to a proposal to acquire or invest in the company. Getting that deal through an investment committee. Each one of those steps of deal lifecycle management, that's been a huge core use case for us over the years. The firms are famous for that Monday morning meeting where they go through the pipeline. Part of the industry from the beginning, but automating that procedure, you're prompting agents to say, I'm looking at this company. We've got a deal and an opportunity. I just got a book from the bankers here. This is an active deal. We got NDA signed. None of that now is point and click. Create my deal, create my company. All of that is AI assisted, procedurally managed, and you can have agents and co-workers back there automating that deal workflow for you.
Speaker 2As more and more firms deploy these tools, I'd love to understand what you think the future of an investment firm looks like from both workflow and staffing.
Speaker 1You're starting to watch, the big public firms at least hold constant. New analysts and associate classes, maybe trim them some. The addressable market question of replacing human capital inside of these firms is a tricky one. People get on either sides of this debate. One of the areas that I think is universally shared is we would like to run the firm. We would like to run the firm more efficiently. It would be nice to get our G&A down. The support staff and the support function doesn't need to scale with the business. If you look at where we play, the systems and the technology to run the business, we think we can bring serious cost reduction, speed and efficiency to the operation of the business. On the future of the investment professional itself, I think we're going to have to look at the future of the investment professional itself. I'm not sure I have a stance on it. Knowing that it took me days and weeks to build models and decks, being able to do that now in hours, minutes, you still got to digest it and iterate it. It's not perfect. There's going to be some major margin pickup in the junior ranks that we've been using in these industries to process data and information. I don't think so. But are they going to use it to help?
Speaker 2For sure. As you're on the leading edge of providing these software solutions to continuously improve these businesses, what software are you working on that still needs to be created and deployed inside these firms?
Speaker 1The number one questions that are unanswered are around governance and security. You work at these organizations, you are constantly under information barriers inside of the company. You are constantly signed up to confidentiality obligations as a firm, as somebody who's on that deal team. You're under review from conflicts from every angle before you even get to work on it. There are a series of firm level, client level, ethical level responsibilities. There's a series of regulatory and market level responsibilities that all of these firms have, all of the people who work on all of these transactions have. Those systems are incredibly complex and they change with the regulatory landscape basically quarterly, sometimes even faster. Our clients hold the world's secrets and their clients' secrets. They work on them as they move a company through its life cycle. A lot of that data exists in our systems. All of our technology and systems has to understand that procedure of confidentiality obligations to the market, to the clients. Those policies and procedures, those information barriers, those ethical walls, those things have to be executed perfectly. You make a mistake, the consequences are grave. You're going to find that the reputational risk is even bigger. The number one thing our clients ask us is, can you make sure that you are doing this in a way that you are following every confidentiality procedure and the governance procedures that run our firms? AI isn't particularly good at that. Throw something into a frontier model or have a frontier model say, go look at all this data. What if I have an obligation to this particular client? That data can't be looked at. When we say firm AI, we also mean simultaneously that all of the policies and procedures, all of the access controls and information barriers is going to be followed. You got to do it the right way. We love our position there. It comes with the history and we're using our systems to govern a bunch of other AI companies. There's some well-known ones now, Harvey, Lagora, some of the ones that are working inside these law firms using our walls product and our information barriers product and our exclusionary permissions about what lawyer can see what as a way to govern other new AI companies. That's a huge question. You can't get more than 10 minutes into a conversation with a client. prospect without it coming up.
Speaker 2I'd love to ask you about a totally different angle, which is private equity world today has this big question about a liquidity bottleneck at the back end. Eight years ago, you're running a business and decided to merge it into another one as opposed to staying independent. We just love to get the benefit of your experience on what advice you might give a company in a similar situation about what was good about this that's now a public company. What might you have done differently?
Speaker 1Intep had a unique history. It was bootstrapped, grew organically over the years. Same thing with DealCloud. We took our time, got to know our markets, tried to build a market-leading product in each of the verticals. Our decision to bring companies together eight and a half years ago, the cross-sell and the up-sell of the products that we were doing, we were doing it in a way that we were doing it in a way that we were doing it the complementary nature of the products and the complementary nature of the markets. We were serving the investment banks, the private equity firms. Intep had the legal tech company. We had the growth platform, the sourcing and origination is here on the front end that you would use to service the clients. Intep had a lot of the risk, management, and profitability functions. Those capabilities together were all you needed to run your firm. That's where we locked onto the firm AI brand and concept. Because that's a true representation of our platform.
Speaker 2When you have that elegant of a potential industrial combination that you did, what doesn't meet your expectations when you go forward?
Speaker 1We're blessed and have a great business, wonderful team, and awesome clients. We service this part of the economy that forms the function of supporting all the other companies through their life cycle. I'm going to invest in it. I'm going to be the banker that represents it. I'm going to be the lawyer that helps you pay for the deal. I'm going to be the accountant that does the QOV. I'm going to be the consultant that helps with the market study. Those are our customers. They are using our technology to run the businesses that are supporting global GDP. Once you become a scaled public technology company, the thing that you're always striving for is better year-over-year growth, acceleration. You've got the analytics, the analysts, and investors always watching and evaluating you. It is our goal as a company to try and grow as fast as we can and do it as efficiently as possible too. If anything's not going to meet your expectation, it's that you didn't get there fast enough. We're all going to get there, but it's the question of how fast. When we do our yearly planning and budgeting, we certainly try to lean into the most aggressive position that we can.
Speaker 2As you've gone in your role, from running the private equity vertical to as head of industries across all these other touchpoints, what have you learned from working in the other industries that have impacted how you've thought about the original business?
Speaker 1They're all different. There are some similarities that are pretty interesting. All of these industries tend to deploy teams, a deal team, a litigation team, an assurance or a tax team. They all tend to work with senior leaders who have spent years and years mastering their craft and a series of mid-level and junior people that are studying in a apprenticeship model to become that senior partner. I've gained a deep appreciation for the way that everybody in these markets is doing. And it's similar. They may be coming at it from a difference of opinion or with a different solution. If you look at the architecture of our firm AI, you look at how Celeste sets up to work for these firms. There's a ton of similarity, how they hire and recruit, how they train people, how they put together teams, how they serve clients, how they drive to revenue and profitability in those practice areas. We've been studying that for a long time. And that similarity, because it gives us a lot of intuition and software. That's where we get good with the agentic workflows. Contextual awareness where you put the AI against those nuanced procedures at the firm level, you can serve the customer.
Speaker 2With the pressure on growth that comes with being a public company, where do you see the next leg of growth for the business?
Speaker 1The value proposition of SaaS software was awesome. Incredible way. We were in the vertical SaaS business where we didn't say we're going to build a horizontal solution for everybody in the world. We said, we're going to focus on some specific firms, specific problems, and we're building the vertical. We've stayed in that spot. The firm AI is coming down through each of those verticals. We believe that that is higher value than it was before. We believe that it commands superior prices from where these products have been in the past. Not just because it's cool, because we think the savings and the ROI for our clients is going to be higher. We believe that it's going to be higher value than it was before. If you're chasing aggressive growth, which we always are, this is a nice market to be in in the AI era because it gives you an opportunity. It's a little bit more of a compelling event today to say, let's have the right systems and procedures. Let's make them efficient and as good as possible. We've all experienced the magic of AI. The outcome is super fun and cool.
Speaker 2Ben, I want to make sure I get a chance to ask you a couple of closing questions. What's the most rewarding thing you do outside of work? I've got a three-year-old,
Speaker 1four-year-old, and a five-year-old. It's pretty fun to go home. They're pretty interested and usually eagerly awaiting at the door to greet you and commence playtime until the battery pack shuts down and they go to sleep. We taught my daughter how to ride a two-wheeler this weekend. That was pretty cool. Learning how to ski and play basketball for the first 20 years of my life. I've had a lot of fun. I've had a lot of fun in my career. It was no kids. You'd stay at the office and grind on your deal. Now there's something to go home to. A very active weekend that includes watching little ones try to play soccer or football.
Speaker 2So that part's fun. What was your first paid job and what'd you learn from it? I had an awesome first job.
Speaker 1I started working at 14. I'm not sure if that broke the child labor law in North Carolina or not. Maybe. I worked for a resort. Called the Chalet Club. I was a water ski instructor in the summer and taught the families who came to the resort. We would get there pretty early in the morning at 5.30 or 6. It was a small resort. So we would clean all the pools, make breakfast, pancakes for the resort guests in the kitchen. And this was a nice place. They didn't know that the water ski guys were in the kitchen doing the pancakes. We would load them up, take them out on the ski beds. It was a great, beautiful mountain lake. We had all these aids and tricks. We were pretty close to 100% success rate in teaching a child or an adult how to get up on two skis. If you had the right family, you're usually handsomely rewarded with a tip if you got everybody water skiing. Sometimes you could make 500 or 1,000 bucks a week in tips. 25 years ago, you were 14 years old. That was a lifetime of earnings and a summer. A lot of fun.
Speaker 2All right, Ben. Last one. What's a life lesson you wish you earned earlier in life?
Speaker 1I love your podcast. You have so many great thought leaders who show up about personal improvement, a lot of great coaches. If you could just become a good listener early on in your career, good at processing feedback. I just think back on the 20s and the 30s. I was surrounded by a bunch of wonderful, smart, brilliant professionals, many of them who had decades of experience to my hero. Did I maximize my time with them? Did I listen enough? Probably not. I'm thankful for the company and the success that we've had, but I've gained a newfound respect for people who have been in it longer, who have seen more. Now in the AI era, it's not about tenure. You can learn from so many angles. I would go back and I would be a much better listener. I would be much better at processing feedback. I do it okay now. I think I'm getting a lot better at it. That's all I get, but I would love to go back to the 20s and the 30s and have done a better job
Speaker 2there. Ben, thanks so much for sharing this incredible update on what's happening with AI and the workflow of the private equity industry. Thanks for listening to this Sponsored Insight. Sponsored episodes are paid opportunities for another 12 to 18 managers a year to appear on the podcast. If you're interested in telling your story to the largest audience of investors in the industry, please email us at team at capital allocators.com to apply for one of the slots.
Speaker 3All opinions expressed by Ted and podcast guests are solely their own opinions and do not reflect the opinion of capital allocators or their firms. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of capital allocators or podcast guests may maintain positions and securities discussed on this podcast. Thank you.
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