FundProcess
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AI helps you build. You stay in control.
FundProcess AI accelerates workflows, calculations, interfaces and reporting, while critical financial logic stays controlled, transparent and fully traceable.
Three roles
AI has three roles. None of them runs the calculation.
It helps you build
Generates data acquisitions, calculations, workflows, interfaces and reports inside Studio. The platform then validates and executes every output.
Implementation stops being the bottleneck between a requirement and a working application.
It answers questions on your data
Ask in plain language — “list all sub-funds with currency and AUM” — and get a structured answer, with the agent’s activity visible.
Operations teams stop queuing for a report to be built to ask one question.
It acts as a business agent
Performs well-defined functions: classifying cash movements, extracting fields from documents, drafting AML notes.
The repetitive review work that used to sit in someone’s inbox.
Where AI is deliberately used — understanding documents and interpreting natural language — and nowhere else.
The principle
One environment. Generative to design it, deterministic to calculate.
AI
Where configuration is built, not calculated
Drafting, structuring, assembling, suggesting — your team reviews the draft before anything runs on it.
Controlled software
Where financial reliability matters
NAV, fees, performance, compliance thresholds — the software applies the same methodology every time, and shows how it got there.
The guarantees
What we will not do with AI, or your data
The commitment
What it means for you
Your data never trains a model
No business-specific RAG, no parallel knowledge bases, no fine-tuning on client data.
Confidentiality and data sovereignty are structural, not contractual promises.
Financial results are always deterministic
Calculations, business rules and regulatory logic stay deterministic, transparent and auditable — verified before any result is used.
A NAV, a fee or a limit breach can be explained to a regulator, line by line.
Nothing reaches production unchecked
Every AI-generated artifact is versioned, traceable, regression-tested and validated against the live data model before deployment.
The audit trail covers what AI wrote, not just what people did.
You choose the model, and where it runs
Model-agnostic architecture — pick the LLM, or deploy entirely inside your own infrastructure.
No dependency on one vendor’s AI, and no data leaving your perimeter if policy forbids it.
See FundProcess applied to your operations
One use case or the whole operating model.
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