Documentation Index
Fetch the complete documentation index at: https://docs.datagenie.ai/llms.txt
Use this file to discover all available pages before exploring further.
The problem
Revenue and volume can both look healthy while the underlying margin or price-per-unit quietly collapses. A human analyst reviewing top-line numbers at month-end sees nothing wrong. The issue surfaces weeks later, after contracts, incentives, or customer behavior have already shifted the business.What DataGenie autonomously detects
Hidden margin collapse
Revenue and volume within forecast, but contribution margin falls sharply — detected automatically across customer × product × region combinations.
Concentrated impact
A handful of customers or SKUs often drive most of the swing. DataGenie ranks them as Contributors without a manual analysis.
Material cost spikes
Cost-per-unit drift hidden inside stable totals — surfaced as a Root KPI.
Cross-source stories
Orders + invoices + returns + rebates auto-connected via Nirvana, even when the sources have different granularities.
How the pieces work together
Top Stories surfaces the change
“Week ending 2026-04-18, in the Northeast region — Contribution Margin fell despite revenue within forecast and volume above plan.”
KPI Attribution explains the why
Root KPI: Material Cost Per Unit +32%. Contributors: a small number of customers and product families.
Wisdom validates
“Is this margin pattern isolated to those customers, or spreading?” Wisdom runs a deterministic pipeline and returns the answer.
Relevant features
Top Stories
The feed where margin anomalies surface.
KPI Attribution
Understand which customers and SKUs drive the swing.
Wisdom Skills
Package a “Margin Risk Identifier” skill for repeatable investigation.