Answered plainly.
The questions that come up on first calls, with the answers I give there.
What is the 90-Day AI Program?
One quarter with a Chief Data & AI Officer, led personally by Khurram. Month one maps every team and writes the firm-wide roadmap, a plain-English data plan and the AI policy. Month two stands up one shared record and puts the first workflow live. Month three measures it against today and starts the second. Two days a week, fixed monthly fee. You can stop at day 30 and keep everything delivered.
How is that different from the free AI Alpha Ladder?
The ladder is 35 self-reported questions in five minutes. It tells you your step and gives you a 90-day plan and a template, with no call attached. The program is Khurram in the room with the people who run the firm, reading the systems they complain about, writing the roadmap and putting the first workflow live.
Who do you work with?
Private capital GPs and LPs under about $10B that don’t have a data or AI lead yet: private equity sponsors and their portfolio companies, private credit and specialty finance managers, family offices, endowments, pensions and funds of funds, and insurer-owned managers.
Who actually does the work?
Khurram leads strategy, architecture and governance personally, and every program is his. Build work runs with a bench of senior data and AI engineers, selected per engagement and working under his review. Nobody junior learns on your invoice.
How do you handle confidentiality and our data?
We work in your environment under your security practices; data does not leave it. NDAs come before anything else. Much of what gets built is your competitive edge, and it stays yours.
What happens after day 90?
Most firms keep the seat on a monthly retainer: a workflow per team, the quarterly re-ranking, and the build work the roadmap calls for, such as the Pilot-to-Production Audit, the Replay or the eval harness. Each build is fixed fee and scored against your own numbers. There is no obligation to continue; the runbooks are written so your own team can carry on.
Who is going to ask about our AI, and will we have answers?
More parties than most firms expect: SEC examiners, external auditors, LP operational due diligence (DDQs now carry AI sections), financing counterparties and boards, and for insurer-owned managers, state regulators under the NAIC model bulletin. The answer they all want is the same: what the model does, who validated it independently, and what happens when it is wrong. The program includes the LP answer written for the next DDQ.
How do you keep AI outputs safe?
Human sign-off at judgment points, confidence-based exception routing, golden-set evals before production, drift monitoring after, and validation independent of the builder. This is the actuarial discipline of effective challenge applied to AI. It was Khurram’s profession before it was a supervisory expectation.
How fast do we see something?
The AI Alpha Ladder takes about five minutes. In the program, your own team gets a quick win inside two weeks, the roadmap lands at day 30, and the first workflow is live by day 60.
We already have a data team. What do you add?
Architecture, standards and senior cover. Most engagements make an existing team faster rather than replacing it. Where there is no team yet, we build the foundations and run them with you.
Should we build or buy?
Decided per case on evidence: workloads, data rights, lock-in tolerance, cost. Month one of the program says which, and the honest answer is sometimes neither. There is no platform of ours on the other side of the roadmap.
Who is behind Operating Alpha?
Khurram Tehseen. Twenty years in regulated financial services, Chief Data Officer at Altriarch Asset Management, a private credit manager, and before that Managing Director of Data & AI at a multi-billion-dollar asset manager. FSA, FCIA. Operating Alpha is a service of Data Unicorn LLC. The full background →