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Service Ops & ML

Service Operations & Document Analytics

A unified analytics model across service desk, ERP and document sources, with ML-assisted extraction and live service-operations dashboards.

Azure MLSAPPower BIOCR / LLM
Service Ops & ML illustration

The challenge

Service-ops insights were locked in ticket systems, SAP and a mountain of PDFs nobody was reading. Decisions were being made on incomplete pictures.

Our approach

How we structured the work, end to end.

01
Stood up ingestion across the service desk and SAP into a governed model.
02
Built ML-assisted document extraction (OCR + LLM) to unlock data from the PDF backlog.
03
Modelled a unified service-operations semantic layer connecting tickets, transactions and document evidence.
04
Delivered live ops dashboards plus drill-down to the extracted document of record.

The architecture

From source to insight, in one governed flow.

01
Service Desk / SAP
02
Document Extraction
03
Unified Model
04
Power BI

Outcome

What changed
Service operations finally has one model. Decisions are made on the full picture, with the source document one click away.

Related work

Other engagements with a similar shape.

Process × Intelligence

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