Industries · Last updated Jul 2026
AI for family offices that runs like a bigger team.
A family office runs institutional complexity on a lean headcount: entities, managers, custodians, K-1s, and a principal who wants one clean answer. We build AI that does the assembly work so your small team produces at institutional grade.
AI workflows for ai for family offices
Operational value
Our library ships free runnable versions of an allocator morning note, a manager due diligence pack, and a wealth client reporting pack. The paid work is wiring those into your custodians, admin, and document stack.
- One clean report across every entity
- Manager DD in days, not weeks
- The principal's questions answered same-day
The lean office problem
The typical family office pattern: a CIO, a controller, maybe an analyst, serving a structure with more entities than employees. Quarter-end means a week of copying numbers between custodian portals and Excel. Manager letters pile up unread. The principal asks a simple question and the honest answer is that assembling it takes two days.
AI collapses the assembly time. Statements get parsed on arrival, positions reconcile into one view, manager letters get read and summarized the day they land, and the morning note drafts itself from live holdings plus overnight news. The team's hours move from assembling information to acting on it.
Start free, then wire it in
Three builds in our public library map directly to family office work: the allocator morning note, the allocator manager DD pack, and the wealth client report pack. Each runs free on your own Claude account, on your own machine, today.
The paid engagement is the plumbing: custodian feeds, entity structure, your fund admin's formats, and the privacy controls a family requires. Fixed scope, agreed upfront, and your team owns the code at handover.
What AI consulting for a family office looks like in practice
Family offices get pitched two things that don't fit them. One is enterprise software priced for a bank, with an implementation timeline longer than the problem has existed. The other is a consulting engagement that produces a technology strategy for an organisation of four people. Neither moves the quarter-end work off the controller's desk.
So the engagement starts by timing the real thing. We sit with whoever assembles the quarterly pack and watch where the hours go: logging into each custodian portal, retyping positions, chasing the one manager who reports late, reconciling the entity that holds the operating business, rebuilding the principal's summary from scratch. Every candidate workflow gets hours per quarter attached and a build cost next to it, and the first build is whichever pays back fastest. Usually that is consolidated reporting or document intake, and occasionally the honest answer is that a spreadsheet template solves it and no AI is warranted.
Privacy is the constraint that shapes the build, not a section at the end of it. For most families we build the pipeline to run locally, so statements and holdings never leave machines you control, no vendor sees the positions, and nothing trains on the family's data. That rules out some cloud conveniences, and it is usually the right trade for a single-family office whose main risk is disclosure rather than downtime.
The verification layer is what makes a drafted report usable. Numbers pulled from a statement link back to the page they came from. Anything computed gets re-derived by an independent pass, and a figure that doesn't reconcile blocks with a flag rather than reaching the principal quietly. Your controller reviews flags instead of re-checking everything, which is the actual time saving.
Six weeks to a running system, then handover: the repository, the prompts, and a working session with your team. What stays with your people is every judgment call, whether to redeem from the manager, whether the concentration is acceptable, whether the K-1 timing changes the plan. The system compresses assembly, and you can test that claim for free from the library before any contract exists.
Questions about ai for family offices
What can AI do for a family office?
The assembly layer: pulling custodian statements into one consolidated view, reading manager letters and flagging changes, drafting the principal's morning note, and processing K-1s and capital calls. A two-person office starts producing like a ten-person one.
How does AI help with manager due diligence?
It reads everything: the deck, the DDQ, the audited financials, the reference notes, and drafts a structured memo flagging inconsistencies and gaps. Your team verifies flags and makes the call. Weeks of reading becomes days of review.
Is family data safe in these systems?
Privacy is the design constraint. We build fully local pipelines where documents never leave your machines, no vendor sees holdings, and nothing trains on your data. For a family office that beats any cloud dashboard subscription.
We're a two-person office. Is this overkill?
The opposite. Small offices gain the most because every automated hour is a big share of capacity. Start with the workflow that eats the most time, usually consolidated reporting or document intake, and expand from there.
What does AI consulting for family offices actually involve?
A workflow audit first, timed against the real quarter-end rather than a generic maturity model, which ranks candidates by hours per quarter divided by build cost. Then a six-week build of the top candidate, usually consolidated reporting or document intake. Then handover: the code, the prompts, and a session with your controller. No retainer required to keep it running, because you own it.
Do you work as a family office AI consultant or as a build partner?
Build partner, and the distinction is worth checking with anyone you talk to. A family office AI consultant who leaves you a strategy document has moved no work off your controller's desk. We scope narrowly, ship one system, and measure it against the hours it was supposed to remove. If the audit says the payback isn't there, we say so before there's a contract.
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