AI adoption for private capital

Every investment firm has an AI initiative. Almost none of them have changed how a deal gets done.

Dhaval Kapadia spent twenty years inside institutional capital, at Citi, at Apollo, and running his own advisory firm. He now builds the AI platforms rewriting that work, and helps investment firms get them past their own defenses.

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Dhaval Kapadia speaking on stage
On stage. TiE SoCal Angels.
20

Years inside institutional capital. Citi. Apollo. His own firm.

$300M+

In institutional and retail capital he reported on, portfolio by portfolio.

95%

Of enterprise AI pilots produce no measurable P&L impact.

1

AI platform built and shipped. Not advised on.

Citi  ·  Apollo Global Management  ·  REAM Partners  ·  Blue Skies AI Studio  ·  TiE LA Angels

— The reality

The tools are deployed. The licenses are paid. And on Tuesday morning, the associate still builds the memo the way she built it in 2019.

Roughly 95% of enterprise AI pilots produce no measurable impact on the P&L. The cause is not model quality and it is not a lack of budget. MIT's researchers called it a learning gap: the tools were deployed, and the organization never changed.

In private capital, that gap has a very specific shape. And it has a name.

— The diagnosis

The Trust Perimeter

Every investment firm draws an invisible line around its most valuable information. The LP data. The deal files. The diligence. The models. The judgment of the partner who has seen this cycle before.

Inside that line, information is an asset. Outside it, information is a liability. The line exists for excellent reasons, and every good firm defends it.

It is also the single reason AI does not land in this industry.

Artificial intelligence is only useful inside the perimeter. That is where the work is. And nobody in the building is authorized to move the line, so the tools sit outside it, summarizing public filings and drafting emails, while the actual work of the firm goes on exactly as it did before.

The firms that win the next decade will not dissolve the perimeter. They will redraw it deliberately, with governance, so that intelligence can operate inside it.

That is the work.

“I spent seven years writing the investor reports that AI now writes in ninety seconds. I know exactly what it gets wrong.”

— The model

The CAPITAL Model

Seven dimensions that determine whether AI will land inside an investment firm. Not one of them is about which model you choose.

ComponentThe question it answers
CConfidentiality PostureWhat is actually permitted to touch a model, contractually and legally? Not what the policy says. What the LPA says.
AArchitecture of WorkWhich workflows are genuinely AI-addressable, in what order, and which are theatre?
PPermissionsWho is allowed to act on an AI-assisted output, and at what threshold? If nobody knows, nobody acts.
IInstrumentationCan anyone in the firm tell whether it worked? If not, it will be defunded within eleven months.
TTalent and BehaviorWill the deal team change what it does on a Tuesday? This is the one that kills most programs.
AAssuranceModel risk, audit trail, and the governance posture that procurement and the LPs will demand.
LLeverageBuild, buy, or partner. Purchased and partnered solutions reach deployment roughly twice as often as internal builds.

See the full framework →

— Working together

Three ways in.

01 / Executive Briefing

Ninety minutes with your leadership team. The failure data, the diagnosis, and your firm's own readiness scored live, in the room, by the people who run it. Most engagements begin here.

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02 / The CAPITAL Index

A scored diagnostic that benchmarks your firm against every other firm we have scored. Seven dimensions. A heat map by function: diligence, IC, monitoring, LP reporting, underwriting. You will know exactly where you stand, and against whom.

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03 / The 90-Day Deployment Program

Twelve weeks. Two streams. The Desk track rebuilds the workflows you already run. The Frontier track builds the capability you do not have and could not build inside the existing structure. Your team presents to leadership at the end, to secure resources. The output is a portfolio of funded work, not a training certificate.

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— On stage

Purpose-built for your room.

No stock presentations. Every engagement begins with research into your firm, your competitors, and the question your leadership is actually arguing about.

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— Enterprise AI Insider

The weekly show for the people who have to make this decision.

Every week, Dhaval sits down with the operators, allocators, and builders actually deploying AI inside financial institutions. Not vendors. Not futurists. The people who have to answer for it.

Watch Listen Apply to be a guest →
— Research

The AI Readiness of Private Capital

We are scoring the industry. 40 firms so far. The first benchmark of its kind, published quarterly.

Get the report →

TiE Global Summit  ·  TiE Investor Summit  ·  TiECon West  ·  Chapman University  ·  Plug and Play

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