The Fund
Private Investment
Late-stage private technology, healthcare businesses that genuinely help someone, and multifamily real estate that pays every month. Our own capital sits in every position beside yours.
What we invest in→Private Investment · Aligned Capital
Today’s investment.Tomorrow’s legacy.
We open doors that are usually closed — late-stage private technology, healthcare businesses that actually help someone, real estate that pays every month. The kind of access normally reserved for institutions. We open it for the people who invest with us, and our own capital sits in every position beside theirs.
The Firm
Three operators.One position.
ADJL is small on purpose. There is no committee between you and the people doing the work, no layer of analysts summarising a summary. We find the deal, we underwrite it ourselves, and we put our own money in before we ever ask for yours. That last part is the whole thing — when we are wrong, we are wrong with you, in the same position, at the same time.
0Investment Verticals
0Markets Modeled
0Partner Alignment
∞Long-Term Horizon
How We Are Built
One firm.Three disciplines.
Most firms our size do one of these and buy the other two. We do all three ourselves, and each one makes the other two better: the research decides what we buy, the software does the research faster than we could by hand, and the fund is where the conclusions get tested with our own money alongside yours.
Market Research
In-House Analysis
We write the note before we write the cheque. Every position starts as a research file — what the business does, what has to be true for it to work, and what would make us wrong — and the same file is what we hand investors.
See a sample note→Technology
Software We Build
The systems that turn that research into decisions: an underwriting engine for real estate deals, and a rules-based system for liquid US equities. Both built in-house, both used on our own money first.
How the systems work→What We Invest In
Four doorsworth opening.
01
Pre-IPO · Growth Equity
Pre-IPOTechnology
Enterprise · AI Infrastructure
Some of the most important companies of the next decade are still private — and most people cannot touch them until the listing, by which point the interesting part has already happened. We work our way into late-stage companies before they go public: enterprise software, AI infrastructure, the platforms quietly becoming essential. This is access that normally sits behind an institutional door. We open it, carefully, for the people who invest with us.
02
Healthcare Clinics
ABA &Longevity Clinics
Preventive · Healthspan Medicine
Two kinds of clinics, one thesis: healthcare people genuinely need, run as sound businesses. ABA clinics help kids with autism learn, grow and thrive, on steady insurance-backed revenue. Longevity clinics — the fast-growing world of preventive and healthspan medicine — ride a powerful demographic wave as people invest more in staying healthy longer. Both are places where doing good and investing well point in the same direction.
03
Multifamily · Student & Workforce Housing
RealEstate
Multifamily · Student & Workforce
We buy apartment buildings that pay us every month — in college towns and cities booming with defense and tech jobs, where demand for housing is not going anywhere. Our edge is renting by the room instead of the unit, which meaningfully increases what a property earns. And we are picky: every deal has to work under conservative, worst-case-ish assumptions before we will touch it.
04
Proprietary Technology · Built In-House
TDPSTrading System
Systematic Equities · Live Market Data
Our own rules-based system for liquid US equities. It watches live market data and turns it into a decision: buy this dip inside this uptrend, risk exactly this much, take most of the gain here, let the rest run. Entries, stops and exits are all defined before the trade rather than argued about during it. We built it, we run it, and we publish what it does badly alongside what it does well.
How the system works→What We Focus On
Where we are looking —and why.
We do not chase every shiny thing. We concentrate on a handful of areas where we think the next decade gets decided, and we go deep. Here is how we are thinking about the world right now.
The data layer of AI
Every company racing to use AI runs into the same wall: their data is a mess. The platforms that help enterprises organise that data and actually put AI to work on it are becoming as essential as electricity — quietly indispensable, deeply embedded, and very hard to rip out.
Why it matters
Once a company builds its AI on your platform, they do not leave. That kind of stickiness, at enterprise scale, is where durable value lives.
The compute underneath it all
All of AI — every model, every chatbot, every agent — runs on GPUs sitting in data centres somewhere. Someone has to own and rent out that raw horsepower. It is the least glamorous part of the AI boom and, historically, one of the smartest places to stand: sell the picks and shovels.
Why it matters
Demand for AI compute keeps outrunning supply. The companies that can deliver it efficiently, at a better price than the giants, have a real edge.
Markets for information
A genuinely new asset class is being born: platforms where people trade on what will actually happen — elections, prices, world events — turning crowd wisdom into a live, money-backed signal. When the parent company of the New York Stock Exchange starts investing billions here, it is worth paying attention.
Why it matters
Brand-new categories are where the asymmetric returns hide — if you understand them early and size the risk honestly. We are studying this one closely.
This page describes the sectors and themes we research and find compelling — it is educational, and it is not an offer to invest, a solicitation, or a recommendation of any security. ADJL Capital’s specific holdings are shared only with qualified investors through private materials.
How You Invest
Two kinds of peopleinvest with us.
Some want to hand it off and get on with their lives. Others want to be in the weeds. We built ADJL so neither one has to compromise.
You have better things to do.
You have worked hard for your money and you would rather not spend your weekends underwriting apartment buildings. Fair enough. Put your capital alongside ours and we will do what we do — find the deals, run the numbers, sweat the details — and keep you posted. You check in when you want to. That is it.
- We source, vet and manage every deal
- Straightforward updates, no jargon
- Our money is in right beside yours
You want to see it for yourself.
You like understanding what you own and why. Good — so do we. Invest with us and you also get the keys to the same research tool we use: scan any property, dig through rent history, run the returns, pressure-test a market at midnight if that is your thing. No black box. You see exactly what we see.
- Full access to the research tool
- Run your own numbers on any deal
- Real transparency, not a summary
Sample Research · Illustrative Only
The kind of researchwe actually do.
Here is a real example of how we study an opportunity before we would ever put a dollar in. This is a sample write-up on Lambda — an AI infrastructure company we find compelling but are not currently invested in. It is here to show you how we think, not to pitch a position.
Lambda
AI Cloud Infrastructure · Research Note
~$5.9B
Last Valuation
~61%
Cloud Gross Margin
1M+
GPUs Deployed
2012
Founded
What They Do
Lambda rents out GPU computing power for artificial intelligence — the raw horsepower companies use to train and run AI models — positioning itself as “the AI Developer Cloud.” Founded in 2012, Lambda started by selling physical GPU servers and workstations before pivoting to cloud as demand for AI compute exploded after ChatGPT. That cloud business now drives the majority of its revenue. The pitch is focus and price: rather than being a general-purpose cloud like AWS or Azure, Lambda does one thing — AI compute — and does it cheaper, offering Nvidia H100 instances at roughly $2.49/hour versus materially higher prices at rivals.
Valuation Trajectory · 2024 → 2026
*Reportedly negotiating a new round around $4–5B and targeting an IPO as early as H2 2026. Figures are from public reporting and are unaudited.
Why It’s Interesting
If most AI bets are on the software, Lambda is a bet on the physical infrastructure beneath it — the classic “picks and shovels” position. Every AI model, at every company, runs on GPUs somewhere, and Lambda has built a credible, cost-advantaged, developer-friendly business supplying exactly that. Two facts anchor the interest: Nvidia is both a validator and a customer — Lambda holds Nvidia’s “Exemplar Cloud” performance status, and Nvidia has reportedly signed on to lease back roughly 18,000 GPUs — and the company has hired Morgan Stanley, J.P. Morgan and Citi as it heads toward a potential IPO, following rival CoreWeave’s path to the public markets.
The Case For
- Pure “picks-and-shovels” exposure to AI compute demand
- Nvidia is both validator and a major customer — rare signal
- Cost-advantaged: H100s at ~$2.49/hr vs. much higher at peers
- IPO advisers hired; CoreWeave’s listing set the precedent
The Case Against
- Deeply capital-intensive — GPU buildouts need constant funding
- Nvidia dependence cuts both ways — supplier, customer and risk
- Hyperscalers and CoreWeave compete directly on price and scale
- IPO is reported and prepared, but unconfirmed — timing can slip
How We’d Think About It
This is the kind of infrastructure bet we find genuinely compelling — but “compelling” and “invested” are two different things. If we were to take a position, we would hold it conservatively, with clear eyes on the capital intensity of the GPU-cloud business and Lambda’s heavy reliance on Nvidia. The setup is strong: a cost-advantaged operator, an Nvidia relationship that is hard to overstate, and a live path toward the public markets. For now, we are watching the terms of any pre-IPO round and the trajectory toward a listing.
We are not currently invested in Lambda.
This is a condensed sample. Our full research notes go deeper — and are shared privately with qualified investors.
What Happens to a Note Like This
A note is not the end of the work. It is the input to a process that keeps running long after the file is written, and that process is ours — built in-house, used on our own capital before anyone else’s.
-
01
Everything is written down
The case for, the case against, and the specific facts that would change our mind. Writing it down is what makes it checkable later — including against ourselves.
-
02
It goes into our own systems
Figures, terms and assumptions land in the same internal models we use to underwrite every deal, so a new opportunity is measured against every one we have already looked at rather than judged on its own.
-
03
It gets re-checked as facts move
Valuations, rounds and competitive positions change. A note is revisited when they do, and the revision is kept beside the original — so we can see whether our reasoning held up, not just whether the position did.
-
04
Investors see the same file we do
There is no internal version and external version. The note our investors read is the note we made the decision from, including the parts that argue against it.
Get Started
Stop guessing.Start knowing.
Whether you want us to handle everything or you want to run the numbers yourself at 2am — there is a place for you here.
Get in Touch→How It Works
From listing toverdict in three moves.
-
01
Paste
Paste a Zillow or Redfin link, or type in the details yourself. That is the only part you have to do.
-
02
Scan
It goes and pulls the real numbers — current pricing, what things rent for, and what has sold nearby — plus the history behind them.
-
03
Decide
You get the full breakdown and a clear verdict — buy, think about it, or pass — in the time it takes to read this sentence.
The Partners
Three partners.One position.
The same three people who source the deal underwrite it, sign for it, and answer the phone afterwards. Every dollar we manage sits next to a dollar of our own.
Daniel Laskowski
Managing PartnerDaniel leads the firm’s investment strategy and deal underwriting. He also designed and built ADJL’s proprietary market intelligence platform — the tool the whole team now runs deals through.
Daniel sets the firm’s investment strategy and underwrites the deals that come out of it. In practice that means he writes the research note on a position before there is a position, and holds the file open afterwards — including the parts of it that argued the other way.
He also built the software the firm runs on: the underwriting engine that turns a listing into a full model in seconds, and the rules-based equities system the team trades from. Both were built because the off-the-shelf versions did not underwrite the way ADJL does.
[Placeholder — background, education, career before ADJL, and what drew you to building the firm this way. Two or three sentences in your own words.]
Andrew Jongeneel
Partner · Real EstateAndrew heads real estate acquisition and diligence, sourcing multifamily opportunities across college towns and defense-sector markets — and making sure every deal earns its place.
Andrew runs acquisition and diligence on the real estate side, concentrating on multifamily in college towns and markets carried by defense and technology employment — places where demand for housing does not depend on any single employer staying.
He is the partner most likely to kill a deal. Every property has to work under conservative assumptions before it goes anywhere near the fund, and the per-room leasing strategy that lifts what a building earns only counts if the numbers hold without it.
[Placeholder — Andrew’s background, how long he has been in real estate, notable deals or markets, and what he looks for first in a property.]
James Harvey
Partner · Advisor & InvestorJames advises on capital strategy and investor relations, bringing steady judgment and a long-term perspective to the firm’s biggest decisions.
James advises on capital strategy and carries the investor relationships. He is the one asking what a decision looks like three years out, and whether we would still be comfortable explaining it then.
His role is deliberately a check on the other two: when the research and the software both point the same direction, someone has to ask what they are agreeing about and whether the agreement is evidence or an echo.
[Placeholder — James’s background, professional experience, and the perspective he brings to the partnership.]
Connect
Let’s openthe door.
Curious about investing with us, or want access to the tool? Just reach out — you will talk to one of us, not a call centre. We treat every conversation with the same care we would want if the money were ours. It usually is, too.
daniel@adjlcapital.com→ Explore the Platform