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LPs.

For family offices, endowments, foundations, pensions and funds of funds investing through external managers.

■ What we hear

What we hear from allocators.

The same handful of problems come up whether the program has fifteen managers or eighty.

01

Every manager reports in a different format

Quarterly reports, capital account statements, capital call and distribution notices arrive as PDFs from dozens of managers, and someone keys them in.

02

Last quarter’s NAV isn’t next to this quarter’s

The documents sit in SharePoint and the numbers sit in a spreadsheet. Reading them is easy now; comparing them over time is the hard part.

03

Look-through exposure takes a week

Sector, sponsor and company exposure across every fund means opening every report, every time the committee asks.

04

The AI working group meets, and nothing ships

Nobody owns AI full time, so it runs on the side of someone’s desk and stalls between meetings.

05

Nobody can see how staff use AI

There is a Copilot or Claude licence, but no signed policy and no register of who uses what for what.

06

“Do we need a data lake?”

The lake, warehouse and lakehouse terminology gets in the way of the decision, and nobody on the team can vet the answer.

■ Where the first workflow usually lands

One workflow, live and measured by day 60.

Month one decides which. These are the three that come up most.

Manager reporting in one record

Capital account statements, call and distribution notices and NAV extracted into one record, quarter over quarter, with every number traced to its page.

Look-through exposure

Sector, sponsor and company exposure across the whole program, ready before the committee asks.

An AI lens on your managers

A question set for the AI section of your operational due diligence, so you know which managers are running AI safely and which are guessing.

■ How it starts

The 90-Day AI Program.

Month one maps the program and picks the first workflow. It is live by day 60 and measured against today by day 90, and you get a signed AI policy and a plain-English data plan along the way.

I build these records for private markets firms now, starting with the data model: managers, funds, commitments, cash flows and valuations, built so new sources plug in as you add them.

Be the person who gets AI running at your firm.

Thirty minutes with Khurram. Bring the question that takes your team the longest to answer.

If it’s not a fit, I’ll tell you who is.