$1.2B
in impact from the data and AI functions built
Be the person who gets AI running at your firm.
With a private capital Chief Data & AI Officer on demand. In 90 days.
The partners are asking about AI. The LPs are asking, in the DDQ. And the firm still runs on manual work: compliance certificates re-keyed into Excel, portfolio company packs rebuilt before every review, capital account statements copied from dozens of managers, a close that takes weeks. Most firms under $10B have nobody who owns the data. I fill that seat for one quarter, and I do the work myself.
■ The problem we solve
A deal team on ChatGPT is not a fund with AI.
Being good with ChatGPT is a personal skill. Running AI inside a fund is a different job. The tool has to be approved by counsel, the data has to stay where counsel says it stays, someone has to own what comes out, and the answer has to survive a question from an LP, an auditor or a regulator.
Most pilots stall in that gap, and the model is rarely the reason. Usually nobody wrote down what the old way cost or agreed what a good output looks like, and nobody owned it after the demo, so it can’t be signed into production.
Personal AIFund AI
The toolWhatever you signed up forApproved by counsel, no-training terms, in writing
The dataPasted inStays where it lives, tiered, logged
Good outputYou can tellDefined in writing, tested against a golden set before go-live
Who owns itYouA named person, after the demo, with a budget line
Who asksNobodyAn LP, an auditor, a regulator, and they want the file
Most pilots are built for the personal column. The work is in the fund column.
■ Where it shows up
You know the symptoms.
They show up in the firm’s day-to-day work.
LPs ask about AI in the DDQ, and there is no good answer.The IR team drafts something careful. Nobody can point to a policy, an owner or a number.
IC memos take weeks to assemble.Deal teams re-key the data room into the template. The partner reads v6 the night before.
The month-end close takes weeks.The administrator’s NAV file, the ledger and the portfolio model never agree the first time.
Portfolio monitoring runs on spreadsheets.Portfolio company packs and compliance certificates land as PDFs. The problem that matters is found at quarter-end.
“What is our exposure to this name?” takes two days.Across funds, vehicles and co-invests, one question from an LP becomes a fire drill.
Dozens of managers, dozens of formats.Capital account statements and NAV arrive as PDFs, and last quarter’s numbers aren’t next to this quarter’s.
Each of these maps to a step on the ladder. The free self-check takes five minutes and needs no call.
Find your step, free →■ How we solve it
How firms get started.
Start with a five-minute self-check. Then the 90-Day AI Program. After that, the build the roadmap calls for, if you want us to do it.
Step 1 · Five minutes
AI Alpha Ladder
35 questions · five minutesYou get your step on the ladder, the factors holding you there, and a 90-day plan for the next step. No call attached.
Take the free AI Alpha Ladder →
Step 2 · 90 daysThe 90-Day AI Program
Led personally · one quarterYour Chief Data & AI Officer for one quarter. Roadmap at day 30, first workflow live at day 60, results measured at day 90.
You can stop at day 30 and keep everything.
See the 90-Day AI Program →
Step 3 · After day 90The fix, if you want us to do it
Fixed scope · delivery partnersWhatever the roadmap says comes next: a stalled pilot audited, an eval harness, one record underneath the funds, exam-ready controls, or the seat kept on after day 90. Each is listed on the Services page.
See what comes after day 90 →
■ How engagements work
Build work is delivered with a bench of senior engineers across data engineering, AI engineering and model governance, under Khurram’s review: senior judgment on every engagement, without the $500K hire.
Track record / prior executive roles
$754M
in reserve accuracy improvements at a global insurer
99.9%
digitization accuracy across 50M+ pages of regulated records
34
data & AI systems shipped to production over six years
■ Why “Operating Alpha”
The name is the thesis.
Alpha comes from operations too: the days a close takes, and whether the problem in a portfolio company is found in-month or at quarter-end. AI is now the biggest of those levers, for the funds that get it into production. Most have not yet, and that is the work we do.
Financial services experience
Richardson
BMO
Manulife
John Hancock
Preston Capital
Encore Life Settlements
Altriarch
Richardson
BMO
Manulife
John Hancock
Preston Capital
Encore Life Settlements
Altriarch
■ Who you’re hiring
Twenty years building this inside funds, lenders and insurers.
I founded Operating Alpha and I lead every engagement myself. I have started five data and AI departments from scratch, most recently as Chief Data Officer at Altriarch, a private credit manager, and zero-to-one builds are the specialty. The three most recent seats:
- Chief Data Officer, Altriarch Asset Management
- Managing Director, Data & AI, Preston Capital
- Director of Advanced Analytics, Manulife Financial
The functions those teams built delivered $1.2B in impact, with 34 systems shipped to production. Build work runs with a bench of senior engineers; the judgment on what to build, and what not to, is mine.