Agentic AI for finance, explained

"Agentic AI" sounds technical, but the idea is simple. This page explains it in plain words — no background in AI required — and shows how the four parts of Numen fit together.

Traditional software vs. an agent

With traditional software, you click buttons and the tool responds to each click. With an agent, you describe the outcome you want in plain language, and the agent works out the steps itself, then does them. You move from operating a tool to delegating a task.

The loop: ask → plan → act → review

1. 1Ask — you type a request in plain language, e.g. "Show me gross margin by product for Q2."
2. 2Plan — the agent figures out which data and steps it needs, and shows you its reasoning.
3. 3Act — it runs those steps against your data: pulls figures, builds a chart or table, drafts the analysis.
4. 4Review — you check the result, adjust, and approve. The version you confirm becomes the final one.

You stay in control

The agent proposes; you dispose. It never posts entries, changes a plan, or finalizes a report without your review. In finance this matters — so Numen is audit-ready by design: reported figures are traceable to the source transactions and computed from your data, not generated by the model. Forecasts are modeled estimates — you can inspect which model produced them, review the assumptions, and adjust them.

How Numen's four pieces fit together

In practice: you ask a question in AI chat; the relevant agent does the work; it drops a widget onto the canvas; you refine and save. That is the whole loop.

Next steps