Answered plainly.
The questions that come up on first calls, with the answers we give there. Nothing here is a teaser for a sales conversation.
How does a fractional engagement work?
A senior AI executive on retainer, one to three days a week: strategy, governance, vendor calls, delivery oversight, board reporting. Quarterly to start, month-to-month after. A one-page memo each month says what you paid for and what moved. Capacity is capped at four fractional clients.
What does it cost versus a full-time hire?
$10,000–$25,000 a month depending on days per week. The full-time alternative is $400–600K loaded, plus a six-month search, for a role most mid-market firms can’t fill with full-time work anyway.
Who actually does the work?
Khurram leads strategy, architecture, and governance personally. Builds are delivered by a small bench of vetted specialists with experience on your type of problem, selected per engagement, working under our founder’s 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 doesn’t leave it. NDAs come before anything else. Much of what gets built is your competitive edge, and it stays yours. Past clients and employers will vouch for the bar.
What happens after the diagnostic?
You execute the roadmap yourself, or we build the first system together with the diagnostic fee credited, or the honest answer is “fix the data layer first” and the roadmap says so. If it doesn’t identify value worth at least ten times its fee, the fee is waived.
Who’s 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, boards, and for insurers, state regulators under the NAIC model bulletin, now adopted across most states. The answer they all want is the same: what the model does, who validated it independently, and what happens when it’s wrong. Getting that answer on paper is a fixed-fee engagement here.
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 working?
The briefing is 90 minutes. Diagnostics run 2–4 weeks. Build sprints put a working system on your documents inside 30 days, or we stop and the remainder is never billed.
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’s no team yet, we build the foundations and hire your first person to own them.
Should we build or buy?
Decided per case on evidence: workloads, data rights, lock-in tolerance, cost.
Who is behind Operating Alpha?
Khurram Tehseen. Twenty years in regulated financial services, most recently 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 →