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AI Analytics

Turns the Virtual Data Layer into business insight — manages the lifecycle of dashboards and views and binds them back to specific Solutions so each app gets its own purpose-built navigation.

For platform-overview framing see Platform Architecture > AI Analytics.

Capabilities

  • Dashboards — multi-panel reports built on the VDL, classified by intent (Outcomes / Predict / Diagnose / Monitor).
  • Views — reusable analytical surfaces, the building blocks that compose into Solution UIs.
  • Four-Views Framework — Outcomes / Predict / Diagnose / Monitor, auto-seeded for every Solution.
  • Solution Mapping — bind Views to Solutions so each shows up as a left-menu item in its Solution UI.
  • Search & Tags — free-text search plus typed tags (four-views, outcomes, monitor, customer-360, esg-sustainability, ...).
  • Dashboard Builder — multi-step canvas with the AI Query Builder for natural-language-to-VDL query authoring.

Walkthrough

Three tabs cover browsing, authoring, and binding of dashboards and views — plus a multi-step Dashboard Builder drill-down reached from + New Dashboard.

Dashboards

Dashboards tab

  • Per-card: name, one-line description, panel count, last-updated date.
  • Tags by intent (Outcomes / Predict / Diagnose / Monitor) and target Solution slug.
  • + New Dashboard opens the Dashboard Builder.

Views

Views tab

  • Auto-seeded four-views per Solution (Outcomes / Predict / Diagnose / Monitor).
  • Per-card: classification + Solution tags, sub-tab count, last-updated date.
  • + New View for custom surfaces beyond the auto-seeded set.

Solution Mapping

Solution Mapping tab

  • One row per catalogue Solution with current view count and slug.
  • Per-row actions: + Add View to bind another, trash icon to unmap all.
  • Auto-provisioning — the backend Solution row is created the first time a View is mapped to it.

Dashboard Builder

Multi-step canvas reached by clicking + New Dashboard. It walks the author through three stages: pick a panel type, wire up its data with the AI Query Builder, and watch the visualisation render against the VDL.

1. Pick a Panel Type from the Add Panel Catalogue

Add Panel modal

  • Built-in panel types across categories: Stats, Charts, Tables, Timelines, Graphs, Other (KPI Card, Bar / Line / Pie Chart, Table, Gauge, Heatmap, Time Series, Histogram, Node Graph, ...).
  • Toolbar with dashboard title, time-range picker, auto-refresh, + Add Panel, Save.

2. Wire the Panel Up with the AI Query Builder

Panel Editor

  • Live preview canvas above; configuration pane below with Query / Visualization tabs.
  • AI Query Builder — natural-language prompt that generates a structured query.
  • Structured Query block — Virtual Entity selector, fields, filters; runs against the VDL whether authored by hand or via AI.

3. Generate, Run, and Render Live

AI Query Result

  • Generate — AI Query Builder fills the structured query, auto-titles the panel, emits a one-line description.
  • Live render against the resolved Virtual Entity.
  • Persist with Apply; refine axes / colours / thresholds in the Visualization tab.
  • Solutions Catalogue — where each Solution's mapped Views become its left navigation.
  • AI Automation — the Journey runtime; many Dashboards and Views surface its run metrics.
  • Data Plane — the Virtual Data Layer that every Dashboard query runs against.
  • Implementation Guide — production code mapping for the analytics surfaces.