All use case spotlights ·Analytics & Reporting ·Data Consolidation ·Knowledge Search ·Manufacturing

Multi-brand industrial manufacturer

Consolidation, forecast and pricing intelligence across four ERPs

≈ $200M revenue across five brands (approx.) · 5 brands · 4 ERPs · 1 CRM

One governed lakehouse behind an AI agent: audit-grade consolidated financials that trace to the source transaction, forecast and pipeline by business unit, large-job margin watch, and plain-English inquiry over all of it, inside the company's own Azure tenant.

Organization
Privately held industrial manufacturer, five brands built through acquisition
Systems
Four ERPs across the brands, one CRM, spreadsheet-driven consolidation
Runs on
Microsoft Azure, in the customer's own tenant, on Microsoft Fabric
Scope
Governed lakehouse, financial core, forecast and pipeline, pricing intelligence, AI inquiry

The situation

Where they started.

Each acquired brand kept its own ERP, four different systems from four eras, and the group's consolidated view lived in spreadsheets stitched together every month by hand. Leadership could not ask a simple question across brands, the controller wanted a ledger tape back to the source transaction before trusting a consolidated number, forecast accuracy by business unit was never tracked, and every new acquisition restarted the whole exercise. The group runs on Microsoft, so a second data cloud was never on the table.

What FlatClaw does

What was built.

  • A governed lakehouse on Microsoft Fabric in the customer's own Azure subscription, fed from all four ERPs and the CRM over the company's WAN, with entity matching across brands and lineage back to every source transaction.
  • The financial core on that store: consolidated financials, business-unit scorecards, forecast and pipeline, large-job margin watch, an AR and collections cockpit, and data-quality dashboards, all reading the same governed numbers.
  • FlatClaw on top, through MCP connectors: finance asks why a margin moved and gets a cited answer; sales asks about a strategic account and gets revenue, margin, pipeline and whitespace across every brand it touches, with updates written back to the CRM.
  • Pricing intelligence and aftermarket analytics as the next phase on the same foundation, because the estimate and the actual finally live in one place.
  • An onboarding pattern for the next acquisition: map the new ERP once, in weeks, and the agent, the scorecards and the consolidation inherit it.

Results

What changed.

  • One set of numbers, traceable to source, instead of a monthly reconciliation exercise.
  • Forecast versus actual tracked over time by business unit, so forecast accuracy becomes a measured thing.
  • Plain-English inquiry across brands for people who never opened an ERP.
  • Acquisitions land as a repeatable, separately priced integration instead of a project each time.
  • Nothing about the data or the model leaves the company's Azure tenant; other brands' staff join as guests with their home-tenant sign-in.

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