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The "manual era" of capital allocation is in its final chapter. The firms still relying on manual data extraction and analysis aren’t failing overnight, but they are falling behind one week at a time. While most of the industry continues to "white-knuckle" through 200-page documents and legacy databases, and manual Excel extraction, a new breed of Agentic Allocators is quietly rewriting the rules. They aren’t just using AI to summarize emails; they are leveraging AI-augmented workflows that intelligently automate parts of their investment and operational processes that were previously impossible to automate.
Hosted by Victoria Sienczewski, CEO and Founder of AuumAI, The Agentic Allocator is the "behind-closed-doors" look at how the world's most sophisticated Limited Partners (LPs), allocators and General Partners (GPs) are actually deploying AI, and the hard-won lessons from those building the systems.
This isn't a series about high-level theory or technical gibberish. Each conversation features industry leaders, forward-thinking LPs, GPs and experts who are rewriting the rules of capital allocation through agentic AI. Expect real-world case studies, tactical frameworks you can actually use, and moments that challenge outdated norms. You'll come away with a clearer understanding of the critical questions every allocator must ask - about data privacy, team adoption, integration, and governance - before investing in any AI solution. If you're tired of the "black box" and ready to evolve your investment office for what comes next, you're in the right place.
Humans are not perfect. They're made of crooked wood. If you can get into a world where the AI is near perfection and can earn us, it will bring so much more transparency and clarity in who's performing and where and how.
Victoria:Welcome to The Agentic Allocator. We are joined today by Maureen Eugene, chief commercial officer at Moonfare. Moonfare is a digital platform widely recognized for democratizing private markets by providing access to funds like Insight Partners, Silver Lake, and Founders Fund, and many more.
Marine:I I'd rather have my investor relations team preparing in-depth portfolio review and and preparing for a nice conversation with an investor that's gonna be insightful rather than having them search for leads or do lead screening. So it allows you to focus your talents on what really matters.
Victoria:Today, we explore how Moon fare is integrating AI internally to augment its investment team's processes, sharpen fund due diligence, and redefine the standard for client service in the private markets.
Marine:I think there's so much excitement, and there's so many area you can deploy an AI. The sheer volume and capacity, and you can deploy this lift in pretty much every function in the company. But you have limited resources like every business, so you have to pick and choose. You have to allocate. You have to decide where is the biggest impact and you have to stay focused on your customer.
Victoria:I hope you enjoy the conversation. Maureen, thank you so much for joining me today. I'm thrilled about the conversation.
Marine:Lovely to be here.
Victoria:You transitioned from the world of private aviation to private markets. And curious, in that transition, how have you seen the desire for a digital first service from a family office perspective emerge? Yeah, very good question.
Marine:Well, first and foremost, know, Moonfare is a digital platform, so we were digitally native. But obviously what was innovation then is now baseline expectation, so what we really did is reduce the amount of paperwork and really simplify the subscription and onboarding flow for family office so that they didn't have to run around, you know, doing paper signature and wet signature and sometimes even involving notary and Apple and all that. So we killed all of this and then made it much more simple with a digital onboarding flow. What was then innovation then became complete baseline expectations, so that's not innovation anymore, everybody else is doing this and it's very much what family offices now expect, something simple, intuitive and easy to handle and to navigate. Where they're now next is finding a lot more interactive live data.
Marine:So you know, today they can log on the platform and they will see their quarterly reporting, they will see, they will have access to the data room, they will have access to all the kind of documents that have been stored in one place, that's great, that simplifies the experience, but that doesn't really give you much interactivity. It doesn't allow you yet to benchmark, compare, bring all your portfolio data in one place, do any forecasting or predictive modeling, and that's really I feel what the family office are now asking. So baseline is bring me a digital service that functions where I can see all my information in one place, but what I really want now is an ability to see my entire portfolio with a lot more live data, news, news feed information about the performance of the font. So less static information and much more interactive live data.
Victoria:And it seems like a ripe opportunity for AI integration.
Marine:Yes. Absolutely. I mean, you could do that, guess, with that, but it would require so much mind work. You know, the almond of the sheer volume of data that our investment team is having to deal with, AI is definitely providing shortcut and a faster route to be able to efficiently process that huge amount of data and really sanitize it and distill it in a much more effective way.
Victoria:And we'd love to focus in on the investment team, so Moonfare has an investment team of around 15 professionals, and they monitor over two fifty alternative funds every year. And so with the sheer volume of GP information as you mentioned, how are they thinking about integrating AI into their process? Well,
Marine:obviously the first obvious application was efficiency and to say okay, take legal documentation, we have 200 pages long contract PPM, you can now just ask the AI to extract the most important relevant terms that we're looking after, you know, what's the minimum ticket entry, what's the duration of the phone, is there any geographic restriction, where we would have had to read page by page, we now kind of get access to that information much faster. And then of course as you know in the investment world we used to be heavily dependent on very complex big excel spreadsheets, and really that AI application there has allowed us to really shortcut again the work. So if you enter like SIM data and prequeen of a company, you can actually pull out all the historic accounting, and you can also automate the the the data normalize and and and maybe just automate things like the IC memo and so there's definitely an efficient play that's already live and and being leveraged by our investment team. The question really is how do you move from an efficient application to a value creation application, application, which is really the next stage or the next wave of of AI implementation.
Victoria:Fascinating. And curious, when did AI become a commercial priority for Moonfare?
Marine:That's a really great question. I think everyone was searching for optimization, efficiency, tools have moved so fast, so fast. The ability of those model is just keeps on really improving by the months really, so we started really deploying basic AI tool to become more effective and ease the workload of the like of the investment team or the engineering team about nine months to twelve months ago, and we now see in the conversation with the client, with the underlying investors that there's some sort of expectation that the AI deployment will accelerate their service, will allow them to see things they currently don't see. So it's becoming, it's moved from a backhand optimization efficient tool to now actually being an expectation from the client base to see AI leverage in their user experience to see a lot more interactive and live data.
Victoria:Fascinating, and would love to dive into the client side. So you have accelerated Moonfare's growth as the chief commercial officer over the past three years. I'm curious, how are you thinking about implementing AI from a commercial perspective and specifically for the institutional family offices that you serve?
Marine:So there are some, again, some really effective low hanging fruit where you can leverage AI. So traditionally, one of the biggest hurdle in a commercial team where you generate a fair amount of inquiries and leads coming into your platform, registering users from multiple, like we're in 23 markets, so you know, every year we will sign up 10,000 to 15,000 new registries on the platform. And so there's a natural element of triage that needs to happen. First of all, because we only really want to talk to suitable investors who have the right minimum qualification and criteria to be able to invest in the underlying fund. And also just to be more effective and not spend time on leads that may just be general inquiries or it may be students doing a research piece or it may be a supplier wanting to sell us a service.
Marine:So traditionally in sales, to do that triage, we relied on pretty archaic lead scoring and we would really hire, you know, five to 10 inside sales junior executive to score and lead qualifying, make sure that your investor relation team really just focus on the most mature opportunity that requires their attention. You can now really do this with an AI, so that's fascinating because where you would have traditional, and in my previous career in the like of NetJets, Flexjet, similar. We would hire ten, fifteen multilingual junior sales executive. Now you really need just two or three of them that are very smart young graduate that can handle really those AI, those chatbot and modeling and they can deploy triage and lead scoring at a much more advanced level. So now you get a lot more and rich data, so they can help you really focus on the leads that are the most mature and the most important.
Marine:There's also a fair element of, you know, in the past when when I started my career, if you wanted to find an interesting lead, you would really, you were down to doing what we called in those days desk research. You would be reading the paper, the financial news, you'd be finding, you know, in pitch book who was about to sell their business and you would be trying, you know, one by one by one with a lot of hustle and hard work finding the right leads. This now, in terms of the lead enrichment and the ability to contact certain ICPs, certain individual customer profile, you can now leverage so many AI tools. So again in that area, it has moved so fast. There are now multiple tools out there that allows you to append a tool into your CRM and they go nurture lead score, profile, segment your CRM and you gain a lot of time.
Marine:The challenge is that they can be quite expensive and not all of them are adapted to the type of customer that we deal with. You have to be very careful when you deal with high net worth in family offices. They don't want to be contacted by a bot, they don't want to deal with an automated, low level transactional conversation. So it's really good in the back end to optimize your lead score and your triage to enrich your data, but you still need qualified human to have the actual finite touch and interaction to prepare for a very high quality conversation because these type of customers don't want to talk to a bot, that's for sure.
Victoria:And tell me how you're preparing your team from a commercial perspective to adopt these tools. What are the cultural elements you have to work through? What are some of the kind of AI training elements that you're integrating into into the team?
Marine:Yeah, we're very lucky at Moonfare that we we work with a very bright, young team motivated, they all come as you know, they all come from tremendous background, they've all like got a pretty good academic baggage, so everyone's excited. Everyone has understood that this is the era we live in, and so there's a lot of initiative. We have champions for every area, we have an AI working group, and every area has chipped in and appointed their own champion to try and figure out what tools we can leverage. But we're very clear that this isn't a substitute for human bodies and for what it really is just a tool to improve efficiency so that the team can then, which is a very smart team, can then focus on what really adds value. So I.
Marine:E, I'd rather have my investor relations team preparing in-depth portfolio review and preparing for a nice conversation with an investor that's going to be insightful rather than having them search for leads or do lead screening. So it allows you to focus your talents on what really matters.
Victoria:Yeah, absolutely. And you touched on an interesting part in terms of the human in the loop integration that will continue to be important within AI systems as we deploy them across investment organizations, Making sure that folks on the team know that there has to be a human in the loop, that they're reviewing the output, and then enabling them to focus on the higher value, higher stakes. So essential.
Marine:The AI is not always right. You cannot rely on what you get. It's a formidable shortcut to go faster, but you need that human interaction, you need the training of the AI. We've also done some really exciting things like for example, producing a new brand book with a ton of voice that we think is adapted to the audience that we are targeting and training our internal AI agent to make sure that we correct communication coming from, you know, one of the things to control is you have so many touch points from the mid office, the operation team, the product on the platform, the investor relations team, the marketing team, and so you need to make sure all those functions are on brand. And it's always a challenge in any business I've been here where you have multiple stakeholder engaging with your customer, how do you keep everybody on brand?
Marine:How do you make sure everybody knows how to speak, what language to use, the right terminology? We can train an AI to do that. That's fantastic. To help everyone that has a touch point with the customer use the right terminology, the right approach, and and and automatically leverage the AI to train the staff when they are engaging in communication.
Victoria:It's a fascinating point to make sure that we're actually focused on domain specificity for these AI systems. That's what we're very focused on is making sure that our customized, for example, to the underlying domain, to the LP and to the allocator context, to the nuances. And so curious when you think about moving forward with AI integration internally, curious if you're able to speak to some of the challenges of that journey and how you've overcome them.
Marine:I think there's so much excitement and there's so many area you can deploy an AI, a lift from AI in engineering, in compliance. I mean, you think about it, just compliance would have required in the past a human person to listen to every single phone call, which was not possible. So you would actually listen to a sample of numbers of phone calls. Now we can have an AI agent listening to a 100% of every call is now covered by compliance. So you're now seeing like the sheer volume and capacity and you can deploy this lift in pretty much every function in the company.
Marine:But you have limited resources like every business, so you have to pick and choose, you have to allocate, you have to decide where is the biggest impact and you have to stay focused on your customer. What does the customer want? You can't just take a shortcut and assume that this is what they necessarily want. So you've got to leverage it where it matters without disrupting the customer flow and the engagement. So for us, it's clearly in engineering, in the investment team, in compliance.
Marine:On the commercial front, as I said, we remain really careful not to really go too far. It's really important for our customer that they still have a relationship with our high quality investor team.
Victoria:And this is obviously an industry evolution and journey, and Moonfare is far advanced, others are still experimenting and earlier on in that journey. When you think about going five or ten years into the future, what do you think an AI enabled investment office will look like?
Marine:That's a fantastic question. What's really exciting next is how far the AI can go. Can the AI get so granular, and we know they can, to track the performance of a specific manager across all vintage, across certain industry segment. Can the AI actually pick cases that are outside of the benchmark that are can the AI on us if you say for example, I'm looking for biopharma, mid cap fund based in the Midwest Of America, can the AI actually surface a form that you didn't know about? Because even though you're formidable and you have 15 investment professionals and you've done a very diligent work for fifteen, twenty years accumulating data, you still rely on tribal knowledge.
Marine:And that tribal knowledge is never perfect. Humans are not perfect. They're made of crooked wood. They will occasionally miss things. If you can get into a world where the AI is near perfection and can earn us all of that.
Marine:It will bring so much more transparency and clarity and who's performing and where and how. I also think a lot around the valuation and the tracking of the live funds in their performance. Today we rely on pretty static data that often have a lag. As you know, we rely on quarterly report that are often based on the previous quarter results and a sheet was a certain lag. It'd be amazing to think that in the future you can have a tracking of every underlying assets, accounting and business flow that actually provides a lot more like a tracker that gives you live information on really how the portfolio is going.
Victoria:It's a fascinating point you raise in terms of sourcing of investment managers and the potential to discover new managers that you haven't known of. Currently lots of LPs and allocators are focused on use cases on the operational side, for example, or from an investment process perspective. But I do agree with you that in the future there's going to be an opportunity to actually connect LPs and GPs in a really unique way based on an intense understanding of a specific investment organization and the GP and their mandate and their track record and their portfolio. So it's very exciting and we'll see how it goes. Maureen, wanted to close the conversation by asking you, if you were to give advice to a peer, another chief commercial officer or a client CIO, how would you advise them on how they should approach AI internally if they haven't yet taken the leap?
Marine:I think it's really I mean, if they haven't taken the leap really they're far behind. This is an urgency. This is happening. Like you cannot not having the AI conversation within your business. And when I think about this, don't think just of a fintech like Moonfare and a digital platform, I think it's really happening in every even traditional business.
Marine:And and everyone has to be looking at it. You've got to be curious, you've got to document. I mean I've registered on Google, know, this Google search or alert anything like LLM prompt because it's not enough to know how to use the AI, you also have to know how to prompt them so that you can avoid the BA's and and so even I am like registered on all those Google alerts on learning how to prompt Claude and how to prompt everyone has to do that bit also. It's a personal journey. You gotta get interested, you gotta be curious, you gotta look around, talk to everyone.
Marine:It's slightly overwhelming, and also those tools are not cheap. Some of the tools that I mentioned that you append into your CRM to do all the lead enrichment and the lead scoring can cost up to 10 k a month. Those are not small budget. That can really quickly rack up in like half 1,000,000, 1,000,000 a year on AI tool. So you also have to be very, very precise, determined and what you're looking at, like be decisive.
Marine:What is it that you're looking for And make sure you don't just rush for the first two that everybody is talking about because there's also a lot of marketing and you really need to figure out where you're gonna get the biggest return for your bot.
Victoria:Absolutely. Focusing on the specific use case, and as you mentioned, the expected benefit for the business whether efficiency or performance outcomes in the future. Marina, was a pleasure speaking with you. Thank you again for joining me Likewise. For the
Marine:Thank you, Victoria.
Victoria:That's a wrap for this episode of The Agentic Allocator. If today's conversation gave you a clearer vision of where the industry is headed or helped you pinpoint exactly where your own process is stuck, go ahead and follow or subscribe wherever you get your podcasts. And if you're curious what Agentic AI might actually look like inside your investment office and how to get there without compromising on security or control, visit auumai.com for demos and resources on AI native LP and Allocator workflows. Until next time.