Anmol Goel on Building a $1B Family Office in Public and Putting AI to Work Behind It

Anmol Goel, CEO and Managing Partner of GACS Family Office, joins The Agentic Allocator for a practical conversation about AI adoption inside a family office. GACS invests over $1 billion across venture, private equity and private credit from London and India, and Anmol runs it in public, speaking at conferences and building a personal profile in a historically discrete community.

Anmol walks through how GACS is using AI within the investment office: a tech due diligence tool trained on the firm’s own past investment memos that has taken analysis from two months down to 2-3 weeks, an internal database that cross compares deals and surfaces unique portfolio connections, and a personal knowledge base built from roughly 10,000 contacts, past conversations and notes that he queries whenever a founder needs an introduction.

He is equally direct about the challenges and what has gone wrong. Team members have put sensitive documents into public tools. Work has gone out without being checked. He is clear that they are still working through where the AI privacy line sits, and that the answer will be different for every family. For an industry where most AI conversations only cover the wins, it is an important reality check. 

What You'll Learn:

• How he got his family comfortable with a public profile in a historically private industry
• How GACS built a tech due diligence tool on its own past investment memos, and why analysis went from two months to 2-3 weeks
• What happened when a new pitch deck went into the system and it surfaced a link to an existing portfolio company nobody had spotted
• How a personal knowledge base of roughly 10,000 contacts answers questions like which fintech regulators do I know
• The two adoption challenges he has lived through
• Why he thinks an extra 30 to 60 seconds on a prompt removes most of the hallucination problem
• Why he worries the next generation will lose the knowledge of knowhow, and what first principles have to do with AI
• What AI adoption looks like across the 30 to 35 family offices he co invests with, and why the split is generational rather than by size
• His starting point for families: repetitive tasks, a cost test, and ignoring vendors who use big numbers to create urgency

About Anmol Goel:

Anmol Goel is CEO and Managing Partner of GACS Family Office, a family office operating across the UK and India with over $1 billion in assets under management, investing across venture, private equity and private credit. He founded his first company at 17 and exited his second at 20 before moving into investing. He holds a degree in mathematics and economics and began his career at JP Morgan and Marsh McLennan. He has backed more than 80 companies and funds, co-invests alongside a syndicate of over 30 family offices, and has beta tested AI models ahead of public release.

Episode Highlights:

[01:42] Building in Public
Family offices have historically operated quietly. Anmol’s view is that a public profile was the fastest route to a network, because if you know something worth sharing, people will take the call. His grandparents’ investment knowledge was land, real estate and gold, so what he was doing looked alien to his family at first. What settled it was a stack of proof. 

[05:35] AI Inside the Family Office

Most significantly, GACS built its own tech due diligence tool, trained on past investment memos and structured around what the firm looks for in a founder, a market and technology. It is not perfect and human intervention is still required, but analysis that used to take two months now takes two or three weeks.

[06:43] When the System Spots What the Team Missed

As the database grows, GACS can cross compare deals and identify smaller M&A opportunities across the portfolio. Anmol describes putting a pitch deck for a company the firm was about to back into the system, which immediately flagged how it linked to an existing portfolio company. The team had not made that connection themselves.

[07:14] Ten Thousand Contacts and One Searchable Base

With close to 10,000 contacts on his phone, Anmol is compiling everything into a single base: contacts, past videos, conversations, and notes. When a fintech founder comes to him, he can ask which fintech regulators, policymakers, operators, founders and investors he already knows, and get back a list with context on how each one could help. For a firm that invests hands on, that is the difference between remembering a useful contact and not.

[09:20] Where It Has Gone Wrong: Privacy and Unchecked Output

Two challenges stand out. The first is compliance and privacy. It can be hard to know with confidence what is being stored, and members of the team have put highly sensitive documents into public systems. The second is cutting corners. Output passed on without proper checking has been wrong highlighting the need for a human-in-the-loop. 

[10:32] Prompt Engineering and the Two Week to Two Hour Shift

A new hire in a team meeting that morning had been hesitant about using AI at all. Anmol’s response was that work which used to take two weeks now takes two hours, and the skill that closes the gap is prompting. Being precise about what you want, and spending an extra 30 to 60 seconds specifying it, removes a large share of the hallucination risk.

[11:22] First Principles and the Knowledge of Knowhow

Anmol has a background in mathematics, taught to derive an equation rather than just use it. His concern is that the models will keep improving while the underlying knowledge of how something works quietly disappears from the next generation. He considers himself lucky to have been on the cusp, having learned it just before it became optional.

[12:48] The Adoption Split Across Family Offices

Across the 30 to 35 family offices GACS co invests with, the divide is generational rather than by size. Families rooted in agriculture, manufacturing or real estate, with principals in their fifties and the next generation not yet in seat, are still some ways behind. Founders who exited in their early thirties and now run a few hundred million are often far ahead, to the point where Anmol asks them how they built it.

[14:15] Where to Start, and What to Ignore

Start with the most repetitive tasks and see whether AI can take them. Run a cost analysis and check that one plus one makes two, because families understand numbers. Be skeptical of vendors who use big terminology and big numbers on an audience they know has a knowledge gap. Start small, understand what is actually making it work, and do not buy on FOMO.

[15:23] People Analysis Over Market Analysis

Anmol argues qualitative analysis matters more now. His own work has shifted from technical, financial and market analysis towards people analysis: how hungry the founder is, how driven, what the why is. That is the part he does not believe AI will pick up, so he lets the models handle the rest and spends his time travelling to meet people.

[16:22] Why He Meets Everyone Before Investing

Of roughly 80 funds and startups backed over the past two to three years, Anmol cannot think of one he invested in without meeting them first, even where that meant waiting a month or two. He accepts that this costs him deals. The trade is that the ones he does write are the ones he is most confident about.

Episode Resources:

Anmol Goel on LinkedIn

GACS Family Office Website

Victoria Sienczewski on LinkedIn

AuumAI Website

Disclaimer: This podcast is for informational purposes only. The views expressed are those of the speakers as of the recording date and may change over time.

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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.

Victoria Sienczewski: 00:06

Welcome to The Agentic Allocator. Today we're joined by Anmol Goyal, CEO of GAC's Family Office, an over $1,000,000,000 family office based in London and India, primarily investing in venture, private equity, and private credit.

Anmol Goel: 00:20

AI models are getting better and better, and they'll continue to. But I think the knowledge of know how is still super important. That's again one of the worries, which I feel like a lot of the younger generation is kind of not having.

Victoria Sienczewski: 00:32

Anmol built Gax, and at 25, he's part of a new generation of family office leaders who operate in public, speaking at conferences and building a personal profile in a community that has historically focused on discretion.

Anmol Goel: 00:46

Attention became currency. So I realized if I really know something and I can help educate someone or support someone, they'll be more than willing to create a video with me or I can talk about that. And then the ripple effect of social media really, really help grows.

Victoria Sienczewski: 01:00

Today, we're getting into how AI is changing capital allocation for family offices and their portfolio companies. And what happens to a traditionally private ecosystem when a new generation of principals decide to build in public instead?

Anmol Goel: 01:13

Qualitative analysis, I feel like now is more important than ever. My analysis all of a sudden has gone from this super heavy tech and financial and marketing analysis to people analysis. How hungry is this person? How driven is this person? What is the why of this person?

Anmol Goel: 01:26

That's what AI can't pick up, I don't think it will be able to.

Victoria Sienczewski: 01:29

I hope you enjoy the conversation. Anmol, thank you so much for taking the time to meet with me today.

Anmol Goel: 01:36

Thank you very much for having me, Victoria. Such a pleasure to be here with you today.

Victoria Sienczewski: 01:40

Before we dive into our topic of discussion today, which is AI, I'd love to learn a little bit more about you. And specifically, the GACS family office is quite unique. You're building what I would say in the open quite publicly which is in many cases I would say quite different than historically how family offices have operated in the sense of being a little bit more under the radar. And so I wanted to ask you, how did you get your family on board to post on Instagram and on LinkedIn and and speak publicly about what you do?

Anmol Goel: 02:09

When I started building my own sort of stuff, the family was very clear that, hey. You go do it yourself. We're not gonna give you funding for it. Right? Which I think is the right way anytime you're getting someone new into the business.

Anmol Goel: 02:21

I think oftentimes where families go wrong is they'll say, yeah. The family money is behind you. And that ability to take risk or that ability to to creatively think or differentiate themselves kind of dissipates. So my thing was like, okay, well, I gotta figure it out now and do whatever it takes. Right?

Anmol Goel: 02:39

And as a very young founder, I I built my first company when I was 17. You have no knowledge, you have no experience, you have no network per se. Right? I mean, you might know a few people. And in the world which, you know, this was 2017 that we were coming into, attention became currency.

Anmol Goel: 02:54

So I realized if I really know something and I can help educate someone or support someone, they'll be more than willing to create a video with me or I can talk about that. And then the ripple effect of that, you know, social media really, really helped gross. So I built my first company. It wasn't the most successful. I made like 50 odd grand when I was 17.

Anmol Goel: 03:15

And and, you know, there's still ceilings to things. Right? So I I couldn't scale it because, you know, hedge funds aren't seriously listening to a 17 year old. Then I built my second company at 19, which I eventually exited at 20. Then I got some more experience down under my belt working at JP.

Anmol Goel: 03:31

Then I went and studied at Harvard, and, you know, I got the access to OpenAI, worked as a beta tester for OpenAI. So this sort of started to happen where the family was seeing me do all of these things, pick up experience, and they were like, continue at it. See where you can get to. Right? Because family's understanding and background was very, very traditional.

Anmol Goel: 03:51

My grandparents, who come from a bit more of a army, bit more of a traditional background, their knowledge that they passed in my family was invest in land, invest in real estate, invest in gold, and and that's about that. Right? So for someone like them looking into what I was doing was almost alien. So for them more than restriction, it was part curiosity and part of like, let's see where this goes. So eventually, when I ended up starting my venture platform and, you know, I said, look, I'll consult companies, I'll invest in companies, I'll syndicate stuff.

Anmol Goel: 04:23

They were kinda like, okay. Maybe you'll make a little bit of money. And by the time I turned 24, you know, I grew it to a $54,000,000 platform and eventually, you know, launched my own fund and became the youngest ever fund manager in history of Europe. And, you know, Forbes came calling and New York Times and, you know, all these other sort of big guys. They were like, You know, there there...

Anmol Goel: 04:45

There's some merit to it, and this works. And at that point, I realized how to leverage media and how I can build a network, you know, through these communications. And at that point, it became much more easier to sit with them and say, hey. Here's my plan of actions. Here's what we wanna do.

Anmol Goel: 05:00

So if you still look at, you know, the structure of our family office and what we do, we talk very much about our successes and failures, which I think is super important in today's day in world. I think the aspect of transparency is being lost, And I think that's led to a lot of people getting to know me and that trust being built. And as a young operator in the industry, you know, that's the quickest way to just grow up where people can say, here's a stack of proof. Right? Here's the validation.

Anmol Goel: 05:28

Yeah. So that that was sort of the the reasoning and the decision making stuff behind it.

Victoria Sienczewski: 05:31

Fantastic, Anmol. Thank you for walking me through that background. And would love to dive into AI. So you mentioned obviously sharing successes and failures. Very important, and there are many, right, when we're adopting AI.

Victoria Sienczewski: 05:44

And so wanted to jump right in and ask, how are you adopting AI internally within the family office?

Anmol Goel: 05:49

I talk about from a investment perspective as a as a as a family office investing. It's been super helpful to the analysts and associates in the team where they've been able to get on a call and we have a notetaker, you know, and it would... The notetaker will then summarize the notes, they will forward me, you know, using AI compile. We've also built our own sort of tech due diligence tool internally, which our CTO reviews. So we basically did a few calls and and and uploaded our past investment memo and sort of said, okay, these are the things we look for when we are investing in a company.

Anmol Goel: 06:19

This is the founder profile. This is the market profile. This is the tech, you know, we need to sort of look at. And again, it's it's it's not perfect. Human intervention is is still needed, but it's been able to cut down, you know, what would typically take us two months to analyze in maybe two to three weeks, and that's been super useful.

Anmol Goel: 06:36

And the bigger knowledge base, the bigger database that we're getting, we can now cross compare deals, and even better, we can now start to sort of do a lot of smaller m and a stuff. I I can name one company, which is Sprouts AI, which is one of our portfolio companies doing really, well in data and AI, and there's another company we're about to invest through, one of the funds we are both LPs and GPs in. And automatically, as soon as we put the pitch deck for the second company into our AI system, it says, this is how it can link to the existing portfolio. And we were like, oh, we didn't even think of that. So those kind of, you know, databases are already being built and the brainchild of that AI is already being built, which is super cool.

Anmol Goel: 07:16

And then there's something that I'm doing personally myself, which I'm sure you're also facing a similar problem from time to time, is that there are so many contacts on my phone. Right? There's about, I think, nine and a half, almost 10,000 contacts on my phone, and, you know, you go to so many events, you meet people, you exchange contacts, and six months later, you're like, who was that that guy in Miami with the with the blue shirt, you know? He he did something, I swear. So I'm I'm now sort of compiling everything, on Claude's base, which is like LinkedIns, contacts, everything, and basically giving it every single data point plus adding like my past videos and conversations and my OneNotes and everything.

Anmol Goel: 07:57

So anytime, let's say a founder comes to me and, you know, when we invest, we like to be very, very strategic, very, very hands on when it comes to the private market. And they say, let's say, for example, they're a fintech company. Right? I can go into that base and say, fintech regulators do I know? Which policymakers do I know?

Anmol Goel: 08:14

Which c suite top level fintechs guys do I know? Which Fintech founders have I spoken to? Which Fintech investors have I spoken to? And it compiles a list and will say, this is their background. This is what they're doing.

Anmol Goel: 08:24

This is how they can be a value at this particular company, and it just makes my life so much easier. From the perspective of efficiency, like, the bar is now here, which is sort of been one of the things that we've really tried to focus on.

Victoria Sienczewski: 08:38

Really, really interesting. You mentioned the word brain. That's my focus right now, the AI brain for LPs and Allocator organizations. And it's so important to add in all of your different systems of record, all of your contacts, all of your historical, I'd say institutional knowledge into that system in order to leverage it fully and leverage Agentic AI. Yeah.

Victoria Sienczewski: 08:58

Incredible. And so obviously, the journey hasn't necessarily been smooth. Right? There are challenges to AI adoption and wondering if you can maybe share one or two learnings that have come up along the way.

Anmol Goel: 09:10

Yeah. I think, you know, the biggest or the earliest issues, and I think this is still kind of one of those things where you're like, you either kind of accept it or you kinda just have to go, I won't use it at all. Right? And that's the issue of sort of compliance and privacy. And this is something, you know, Meta had massive issues in the in the Internet wave of things.

Anmol Goel: 09:32

It's still very hard to know if AI is storing this... You know, even even the enterprise solutions that you have for Claude and whatever, and they say they don't distribute the information. It's just readily available for you. It's still hard to to to see or to understand it, the depths of that. So that's been...

Anmol Goel: 09:50

There's been a couple of, you know, cases where team has gone, put super sensitive documents on, you know, the Claude systems, and we've gone, what the hell are you doing? Right? And it's resulted in a few disciplinary actions, let's say. So there... There's been some issues there, and then part of it has also been, which I mentioned, AI is not perfect.

Anmol Goel: 10:10

It's still hallucinate. It still has issues. And again, anytime you try and cut corners, you know, you'll you'll put a document and then you'll say, great. I'll just pass it forward without in-depth checking. It has had issues and it's led to us sort of kind of being embarrassed and...

Anmol Goel: 10:27

So those two are the the biggest concerns. So... And and and, you know, this was a conversation actually I was just having in the team meeting this morning where they were like, oh, I don't know, you know, if we should be using AI. I'm trying to do this, da da da. And I was like, guys...

Anmol Goel: 10:41

And I mean, to be fair fair play to her, she's a new hire, so she doesn't know what it was, you know, working seven, eight years ago when there wasn't any AI and you had to sit down and do everything by hand. And I was like, your work has condensed down from two weeks to two hours, you know, and you need to learn how to prompt engineer. She she basically, put something into the system and was like, do this with this. And I was like, you can't just put that. You have to be a little bit more precise with your prompt engineering.

Anmol Goel: 11:08

Right? And even now Stanford is running a course in prompt engineering, is super cool. So, you know, I want this to look like this. I want this to be built like this. And if you can put in, like, an extra thirty to sixty seconds, I think a lot of that hallucination would be restricted.

Anmol Goel: 11:22

I think AI models are getting better and better, and they'll continue to. But I think as a human, you still need that, knowledge of first principles. So in... I'm a mathematician by background and, you know, we were taught rule of first principles, was, you know, let's say you have your quadratic equation. Right?

Anmol Goel: 11:39

You have to kind of know where that quadratic equation comes from. How do you derive that equation? So the knowledge of know how is still super important. So I think that's again one of the worries, which I feel like the... A lot of the younger generation is is is kind of not having, and I feel very lucky that I was on the cusp, you know, that I I just learned it and then it dissipated, so I can still retain it.

Anmol Goel: 12:05

But, yeah, the privacy, I think, still, you know, is a big issue. And what I was saying in the start regarding, like, there... There's two ways. Right? You can either just go, well, everyone's information kinda is already out there, so you might as well, or you kinda just go the European way of, like, I just will not touch technology.

Anmol Goel: 12:21

I think that will push you so far behind everyone else. So I don't know what the right answer is, and I can't say confidently that my family has figured it out. We're still trialing and erroring in the hopes, you know, we can find a solution which is best fit for us. Right? And and there's another thing, right, which is what might be a best fit for me might not be a best fit for you or someone else's family.

Anmol Goel: 12:43

So... Yeah.

Victoria Sienczewski: 12:44

Absolutely. And you mentioned, obviously, Anmol, there's a clear picture of the industry. Right? Some folks are leveraging AI to the fullest extent. Others, would say, are lagging behind or they're adopting at a slower pace.

Victoria Sienczewski: 12:57

You've created a very interesting syndicate from a family office perspective where you co invest with thirty, thirty five plus family offices. When you look at that landscape of your peers, what is adoption like from your perspective within the industry right now? What's the state of adoption?

Anmol Goel: 13:13

I think there's there's there's levels to it. Right? There's those guys who come from very traditional families, and backgrounds of, agriculture, manufacturing, real estate, and especially the principles are still in the ages of, like,. So next generation is just coming in but hasn't quite entered. They're still lagging quite behind, and the knowledge is still relatively primitive.

Anmol Goel: 13:34

And there's those guys, you know, SF grown founders, maybe exited a company when they were, like, 32, 33. They're now in their mid to late thirties sitting on a maybe a smaller family office, you know, a couple 100,000,000, but are, like, super integrated. You know? And sometimes I have to sit with them and I go, woah. What's how have you done that?

Anmol Goel: 13:53

Right? So there there there's a there's a scale. I would say I... If the center is here, I sit bit more towards the higher side of it, but I I definitely don't think I'm, you know, maximizing what I could. But that's because I don't also wanna become overly dependent on AI that if something happens, you know, everything then sort of shuts down.

Anmol Goel: 14:14

So... Yeah.

Victoria Sienczewski: 14:15

And Anmol, wanted to ask you, if you were to give advice to a family office that's earlier adoption journey for AI Yeah. Where would you tell them to start?

Anmol Goel: 14:24

I think the the easiest thing that I would probably say is look at what are your most repetitive tasks and see if AI can pick up on those. I felt that saved a bunch of time and cost, you know, going in. So I would say have a look at those and see how that AI is working for you before you start to double down. I think a lot of the times when people are sort of building out AI technologies and they're pitching to these family offices, they know that there's a lack of knowledge, so they'll use big terms and big numbers to scare them and lure them in. So I would say don't fall for that.

Anmol Goel: 15:00

Start with something small. Grasp your head around it. Understand how it's working, what is making it work. Do a cost analysis. As families, everyone knows, you know, the numbers.

Anmol Goel: 15:10

Right? As a mathematician, I just looked at numbers. I was like, is, you know, one plus one making two? And if it's not, then don't touch it. Right?

Anmol Goel: 15:19

So don't FOMO get into it. Right? On the investment side, I would say best way is to collaborate with your peers and partners who have started to adopt it. I think analysis has been a good way, but again, don't solely rely on AI analysis because it's still relatively quantitative. Qualitative analysis, I feel like now is more important than ever.

Anmol Goel: 15:41

So the reason, you know, I was in India last week. Now this week, I'm heading to New York, and then couple of weeks, we'll be in Monaco and so on and so forth is I'm meeting just people now. So my analysis all of a sudden has gone from this super heavy tech and financial and, you know, market analysis to people analysis. How hungry is this person? How driven is this person?

Anmol Goel: 16:00

What is the why of this person? That's what AI can't pick up, and I don't think it will be able to. So I still lean on those and let the other stuff be done with AI. So that's what I would say.

Victoria Sienczewski: 16:10

I fully agree. Right? In the new AI world, the focus will be on people Yeah. And how we are able to, let's say, really meet them face to face, learn about their backgrounds, what motivates them, especially from a, let's say, manager selection or fund selection perspective.

Anmol Goel: 16:25

I'm I'm still very old school in my thinking. I'm I'm trying to think... We've probably done about eighty eighty something funds and start ups investments over the last two to three years. I can't really think of anyone who I invested in without going to meet them. Even if it's, you know, I'll invite them to an event or they'll come or I'll wait maybe a month or two, but I think there's there's a sixth sense that I have and people might think it's heebie jeebie, whatever, you know, they they wanna call it.

Anmol Goel: 16:54

But I I trust a lot in my gut feeling, and I I I sometimes... I I... Yes. I might miss deals, and I have missed deals. I mean, you know, which is fine.

Anmol Goel: 17:02

But the deals that I am becoming a part of it, I just don't wanna get those wrong. So... Yeah.

Victoria Sienczewski: 17:08

Anmol, thank you so much for taking the time to meet with me. What a wonderful conversation.

Anmol Goel: 17:11

No. Thank you very much for having me, and I hope people have got some good takeaways from it, and and and this has been super helpful. So, yeah, thanks again for having me here.

Victoria Sienczewski: 17:20

Thank you. 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. Your firm's judgment took years to build. Stop letting it reset every time a team member walks out the door.

Victoria Sienczewski: 17:47

Visit auumai.com to discover the structured digital intelligence foundation your team needs to leverage Agentic AI to its fullest potential. Until next time.