Small team. Large mandate.
AI agents that multiply your team's output
without multiplying your team.

Fiducia AI is not a SaaS platform. We deploy the agents directly into your existing infrastructure rather than operating as a shared service that all clients use. For most multifamily offices and EAMs, that means inside your dedicated Microsoft Azure tenant or AWS account, with secure connections to your on-premise systems where needed.

This architectural choice changes how several of the standard SaaS vendor risks apply to your operation, and it is what makes the answers to confidentiality, data, privilege, and continuity work the way they do. Your data and your workflows never leave your environment.

Confidentiality is governed by your existing access controls and tenant boundaries, not by ours. The agents run inside your dedicated Azure tenant or AWS account, with secure connections to on-premise systems where needed. No data leaves your tenant. No information is shared between clients. Each engagement is fully separated.

No. The enterprise AI services we use inside your tenant, such as Azure Foundry or Amazon Bedrock, are governed by contractual no-training and data-handling commitments from your cloud provider. Your data is not used to train third-party models, and is not visible to other clients or to Fiducia AI.

No. An AI agent inside your own environment functions like any other authorized internal tool, comparable to secure email between you and your client. It receives content, applies its rules, and returns the output to the same authorized user. Nothing leaves your confidentiality perimeter. Privilege concerns generally arise when privileged material is shared with external consumer AI services, which is the opposite of how Fiducia AI is deployed.

No. The agents are designed and configured by Fiducia AI to fit your existing workflows. Your team interacts with them in natural language, the same way they would brief a human assistant. Your relationship managers, analysts, and trustees stay in their craft. The conceptual layer of the work, what to ask, what matters, who the client is, remains entirely yours.

Mistakes are treated as input, not incidents. Most fall into two categories, and both are fixable: if the agent misunderstood an instruction, we refine the prompt or rule; if the agent lacked context, we add it to its knowledge base. A structured feedback loop captures these corrections so the agent gains experience over time rather than repeating the same mistakes. Critical decisions stay with humans in the loop, and every action is logged. Agents are tools, not unsupervised autonomous workers.

Operational continuity is built into the architecture. Because agents run inside your own environment, they are governed by your existing business continuity plan and your cloud provider's SLAs, the same framework that protects the rest of your IT operations. There is no separate Fiducia AI platform that needs to stay online for your team to keep working. On our side, we maintain incident response procedures and can quickly restore agent configurations; on your side, your existing BCP already covers the infrastructure agents run on.

No. The goal is to invert the 80/20: today most relationship managers and analysts spend 80% of their time on admin and 20% on the relationship. Agents take the admin layer so your team can spend their time on what AI cannot do, which is the trusted human relationship at the core of this business.

Swiss multifamily offices, external asset managers (EAMs), single family offices with operational complexity, and small holdings managing multiple entities. The common pattern is small expert teams under regulatory and cost pressure, still running on Excel sheets, manual reporting, and fragmented systems.

Four core pillars, plus custom workflows: due diligence on direct investments and portfolio companies; compliance and KYC; market intelligence; prospecting and client acquisition. If your team can describe how they do something, we can build an agent that does it alongside them.

Concrete examples from current engagements: a single family office in Zurich reduced quarterly due diligence from 120 hours per analyst to 12, in one week. The agent also surfaced five forecasting errors that had gone undetected across multiple analysts and years.

A multifamily office in Basel reduced monthly client reporting from one full day to two to three minutes per client, with personalization per family.

We start with a focused pilot on one workflow, typically delivered in weeks. From there we expand based on what we learn together. You see ROI inside the pilot.