Ask
The user poses a practical finance question in ordinary language.
From report requests to governed answers in seconds.
For a large global enterprise, Radix designed and delivered a finance assistant that allows leaders and business managers to work with budgeting, workforce, purchasing, forecast, and variance information through a conversational interface—without moving calculation or data authority into the language model.
The problem
The organization had rich financial data and established reporting controls, but answering a new question could still require navigating specialist tools or requesting another report.
Adding a chat box would not solve that problem if it introduced unsupported calculations, silent assumptions, or access outside the user's existing permissions.
The approach
Separate language from authority.
The language model interprets the question, identifies ambiguity, and selects from approved finance capabilities. Deterministic services perform the numeric work. Existing identity and row-level permissions remain attached to the request through the data boundary.
The system
Clarify
If scope would change the answer, the assistant asks rather than assuming.
Plan
The assistant selects a short sequence of typed finance capabilities.
Enforce
Identity and row-level permissions limit the available data.
Calculate
Deterministic services perform the analysis.
Use
The response combines an explanation with the right table, chart, or export.
Business value
A reusable pattern for sensitive enterprise AI.
The system replaces a slow report-request loop with governed answers in seconds.
Have a similar problem?
Put language to work without giving up authority.
Tell us where the workflow slows down, which controls matter, and what a useful answer needs to enable.
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