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Build versus buy: how family offices should evaluate technology infrastructure in the AI era
For most single family offices, the build versus buy question is no longer a close call. Complex portfolios, more jurisdictions, and rising AI expectations have raised the bar for what any internal team can realistically maintain. What matters most today: how custodial data feeds are maintained, how data integrity is protected, and how that data becomes usable analytics.
Why building in-house is harder to justify
A decade ago, some large offices built proprietary infrastructure because the market offered little else. That calculation has shifted. Custodian formats change, standards evolve, and security and AI expectations rise every year. Building in-house means maintaining all of that indefinitely, competing with the family's core work for budget and attention. Choosing the right platform means sharing that cost and expertise across many offices instead of carrying it alone.
Custodial data feeds: connectivity is not the hard part
Most conversations about data sourcing focus on coverage: how many custodians, banks, and fund administrators a platform connects to. Coverage is the easy half. The harder half is keeping those feeds accurate once they exist. Custodians change file formats and reporting conventions without much notice, and any of that can silently break a feed. This is not a one-time project; it runs every day, indefinitely. Alternative investments add a second layer: capital account statements and NAV letters follow formats set by each administrator, with no industry standard. The real question is not how many institutions a platform connects to, but how quickly it catches and fixes a broken feed before it reaches a report.
Data integrity: catching problems before they become someone else's
Once data arrives from dozens or hundreds of sources, the next problem is making sure it is correct. A balance that does not match a custodian's own statement, a stale price, a corporate action applied twice: these happen routinely and are invisible until something catches them. Strong infrastructure catches most of these automatically, flags what it cannot resolve, and routes exceptions to a person rather than letting them flow silently into a report. What checks run before anyone sees the data, and how long does a problem typically take to catch?
Producing analytics: turning clean data into something usable
Assuming the data is accurate, turning it into usable analytics is its own challenge, harder for a family office than for almost any other kind of investor. Holdings span public equities, private funds, real estate, and cash, across entities, trusts, and currencies. A single accurate picture of exposure requires consolidating across entities, translating currencies consistently, and looking through fund structures to underlying holdings. Performance has to be calculated differently by asset type, time-weighted returns for liquid holdings, IRR and multiples for private ones, then blended into one meaningful number. Analytics built on shaky data will look precise and be quietly wrong.
A brief note on accounting
Some platforms now generate journal entries from investment activity that export into an office's existing accounting system. That is a meaningful shift for offices running investment and accounting as separate processes, but it is a narrower question than the three above.
AI: a governance question before it is a capability question
The most valuable use of AI in a family office is not the most technically impressive one. It is asking a plain-language question, such as what the office's real estate exposure is and how it has changed, and getting an accurate answer sourced from the office's own data in seconds. None of that matters without governance underneath it. Any AI layer should run inside the office's own secure environment, respect existing permissions, draw on the same verified data used elsewhere, and never send data externally without consent. It should say when it does not know an answer, and every query should be auditable.
Questions worth bringing to the conversation
- What happens when a custodian changes its file format, and how fast is it caught?
- What checks run on incoming data before it reaches a report?
- How is performance blended across liquid and private holdings, across currencies and entities?
- Where does data go during an AI query, and does it ever leave the office's environment?
The decision comes down to focus
Most family offices do not have the capacity to build and maintain this infrastructure competitively, and the market has matured enough that few need to try. The real question is not whether an office could build its own technology. It is whether that time is better spent on data feeds and AI governance, or on the investment and family work only the office can do.
