Nothing leaves the room
Super Chain: Private On-Prem AI for a Family Office
An LLM with retrieval over financial research, macro data and portfolio holdings, with the model chosen per office, running on the office’s own infrastructure. Every answer is cited.
The problem
A family office holds the ledger. Fund statements, trust deeds, counterparty terms and tax filings are exactly the documents that cannot be posted to somebody else’s API. That is why most offices of this kind had no AI at all — not because the use case was weak, but because every available product required handing the crown jewels to a third party.
What we built
Super Chain: an LLM with retrieval over financial research, macro data and portfolio holdings, with the model chosen per office, running on the office’s own infrastructure. Retrieval grounds each answer in the office’s own sources, and every answer is composed with those sources cited so a principal can check the working.
Before
- Documents that cannot leave the office
- Every AI product needed a third-party API
- So the office used no AI at all
How it works
Deploy on the office’s infrastructure. The model, retrieval and data run on infrastructure the office controls.
Choose the model per office. The model is chosen per office to fit its policy and workload. Retrieval over the office’s own sources supplies the domain knowledge.
Retrieve across sources. Retrieval spans financial research, macro data and portfolio holdings.
Cite every answer. Answers are composed with their sources cited, so a principal can check the working.
After
Nothing leaves the room
Stack
LLMFinTechOn-PremiseRAGWhy it holds up
Nothing leaves the room. The privacy constraint is not a feature bolted on at the end — it decided the model, the deployment and the retrieval architecture from the first design session. That is the difference between an AI system a family office can adopt and one their counsel will never sign off on.
Related service: Secure AI agent development
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Get started
Talk to the engineer who will build it.
You will speak with me directly. Bring the use case, the data and the constraints, and I will give you a straight view on feasibility, effort and the first thing to ship.
