Finance Automation

Sourcing Partners: PDF Invoice Automation Pipeline

A document-to-data pipeline that turned manual, multi-step PDF invoice processing into an automated, validated flow feeding financial reporting.

Case study
  • Python
  • Power Automate
  • SharePoint
  • Power BI

The business challenge

Invoices arrived as PDF documents, not structured business data. Someone had to receive, open, read, extract, validate, enter, store and publish every invoice before analytics or downstream processes could begin. The real problem was larger than invoice processing: it was a data extraction and workflow automation problem.

The solution

Z&C designed an automated workflow using Python, Power Automate, SharePoint and database integration, converting PDF invoices into structured, validated information for downstream use — from ingestion and extraction to rule validation, storage and financial reporting.

Implementation

How the system was built, step by step.

1

Ingestion pipeline

PDF invoices are received and ingested automatically into the pipeline, removing the manual intake step.

2

Document extraction

Python pulls fields from unstructured PDFs and converts them into structured data.

3

Validation against business rules

Extracted fields become structured JSON validated against business rules before anything reaches the database.

4

Database & document management

Validated data is stored in the database while SharePoint manages documents, workflow state and collaboration.

5

Analytics consumption

Power BI consumes the structured data for financial reporting.

Business results

What changed for the business once the system was live.

Cycle time collapsed

A process that took approximately two weeks was reduced to hours, depending on volume and cycle.

Manual effort removed

Document to automated extraction, validation, structured data and reporting — without manual re-entry.

Reusable pattern

Document → Data → Workflow → Analytics: a repeatable blueprint applicable to any document-heavy process.

Case positioning

Automation, data engineering and BI combined to eliminate an operational bottleneck — and created a repeatable blueprint for the next one.