# Super Chain: Private On-Prem AI for a Family Office | Super Cat > Super Chain: an LLM with retrieval over research, macro data and holdings, model chosen per office, on a family office’s own infrastructure. Every answer cited. Source: https://www.super-cat.tech/portfolio/super-chain-family-office Last modified: 2026-10-22 [← All case studies](https://www.super-cat.tech/portfolio)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. After: Nothing leaves the room.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 - 01 Deploy on the office’s infrastructure. The model, retrieval and data run on infrastructure the office controls. - 02 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. - 03 Retrieve across sources. Retrieval spans financial research, macro data and portfolio holdings. - 04 Cite every answer. Answers are composed with their sources cited, so a principal can check the working. After Nothing leaves the room Stack LLM FinTech On-Premise RAG ## Why 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](https://www.super-cat.tech/secure-ai-agent-development) ## More case studies Big 4 client · fully on-premise ### Enterprise RAG Chatbot for a Big 4 Accounting Firm Multimodal retrieval over a Big 4 firm’s full compliance library, tuned for citation instead of summary — every answer arrives with its source paragraph attached. - Juniors reading thousands of pages per question - Seniors acting as search engines Read the case → 200k calls/month · 67% booking rate vs 77% human ### 24/7 AI Agent Call Center: 200k Calls a Month Across 60 US HVAC Brands Voice agents orchestrating 200,000 calls a month across 60 US HVAC brands for a 5,000-person enterprise, booking 67% of calls against 77% for human agents — within 10 points of a trained team, around the clock. Built as a product, an AI front desk that answers, books and routes, not a pilot. - Night and weekend calls unanswered - Staffing every shift hard to justify Read the case → US$1M collected in the first 3 months ### AI Payment Collection and Reminders The companion product to the AI front desk: it chases unpaid invoices with polite, timed reminders and a payment link, and stops the moment the customer pays or replies. It collected over US$1 million for the client in its first three months. - Chasing payment is awkward and late - Billable time lost to collections Read the case → 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. [Book a call](https://calendly.com/super-chain/catyung)Hong Kong & London time zones