Skip to main content

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.

This Getting Started guide provides the fastest path to transforming your raw datasets into meaningful business stories using the GO onboarding engine.
DataGenie is autonomous by design. The moment a dataset finishes onboarding, the platform begins monitoring hundreds of thousands of metric combinations and surfaces connected stories with root causes — no chart-building required. See Autonomous Insights for the mental model.

​
Quickstart flow

The goal is to move from a raw dataset to your first real insight in minutes.

Initialize GO

Start the GO engine and upload a sample dataset to allow DataGenie to understand your schema and key fields.

Add Context

(Optional) Provide dashboard screenshots, metric definitions, and filters so GO can align the output to how your business tracks performance.

Generate Blueprint

Generate the onboarding blueprint — a consistent, reusable configuration — and complete the onboarding process.

Review Top Stories

Open Top Stories to immediately see the most impactful changes surfaced by the autonomous engine.

Validate with Wisdom

Ask a follow-up question in Wisdom to confirm if a change is localized or represents a broader trend. Wisdom runs deterministic analytical pipelines — no hallucinated answers. See Responsible AI.

Deeper Investigation

If the story requires more detail, continue to Explorer for dimensional analysis or Wisdom for historical context.

​
Onboard with GO

GO is the core onboarding engine designed to configure your dataset for insights with minimal friction.

​
Input requirements

Sample Dataset

Required. A representative sample of your data to help the engine map the structure.

Dashboard Context

Optional. Screenshots or definitions that help GO map KPIs to your team’s specific business language.

​
The output

Once GO processes your inputs, it produces an Onboarding Blueprint. This ensures your configuration is reusable and that DataGenie can accurately learn the trend, seasonality, and inter-relationships of your metrics.

​
Your first insight: Top Stories

Top Stories is your primary destination for consuming automated insights.
  • Impact Prioritization: Review the most critical changes first based on their impact on the business.
  • Contextual Summary: Every story includes a layman-style description explaining what changed (KPI movement) and where it happened (segment or dimension).
  • Visual Severity: Indicators like the “battery charge” icon show the intensity of the deviation — Minor, Major, or Critical.

​
Ask your first question: Wisdom

Wisdom provides the fastest way to explore data without manually building charts or writing complex queries.

​
Question patterns to try

Trend Analysis

“Show me the trend of [KPI] over the last 3 months”.

Dimensional Breakdowns

“Break down [KPI] by [Country/Channel/Device]”.

Historical Comparisons

“Compare [KPI] for current period vs previous period”.

Segment Filtering

“Filter to [Segment] and re-check the [KPI]”.

​
Alerts and monitoring

Alerts ensure you stay updated on critical shifts without needing to log in daily.
  1. Select Dataset: Choose the metric landscape you want to monitor.
  2. Set Cadence: Configure the monitoring window, such as Daily, Weekly, or Monthly.
  3. Receive & Validate: When an alert is triggered, use the linked story to jump directly into Wisdom for validation.

​
Where to go next

Core Concepts

Master terms like KPIs, Dimensions, and Contributors.

Product Features

Deeper guidance for every specific feature.

Release Notes

Track recent updates and platform improvements.