Back-Office Automation

Extract Telecom Billing Data to Excel

Automate the extraction of itemized charges and usage data from recurring telecom statements. Define your schema, review extracted data side-by-side, and export clean files for your finance workflow.

Template-based extraction
Side-by-side review interface
Custom schema definition
Spreadsheet-ready exports
Review-first
Workflow design
Template-ready
Recurring processing
Minutes
Data extraction time

How the workflow works

1

Define Extraction Schema

Set up custom fields for account numbers, billing periods, and itemized charges to match your internal ledger.

2

Apply Reusable Templates

Upload recurring bills and use templates to automatically map data from specific carrier formats.

3

Review and Export

Verify the extracted data against the original document before exporting into a clean Excel-ready file.

Manual vs structured workflow

Manual process

Manual data entry from multi-page PDFs leads to frequent typos and missed rows.

Structured workflow

AI-driven extraction ensures structural consistency across all document pages and cycles.

Manual process

Re-formatting itemized charges for accounting spreadsheets takes significant manual effort.

Structured workflow

Data is exported in a pre-structured, spreadsheet-ready layout that fits your existing workflow.

Manual process

Difficulty tracking usage trends across thousands of rows in separate PDF files.

Structured workflow

Reusable templates allow for standardized data collection across all monthly telecom billing cycles.

Common finance use cases

  • Itemized charge auditing
  • Multi-line cost allocation
  • Historical billing trend analysis
  • Automated utility cost tracking

Frequently asked questions

How does it handle recurring monthly bills?

You can create a reusable template for each carrier to ensure consistent data extraction across every billing cycle.

Can I review the data before exporting to Excel?

Yes. The platform provides a split-screen review interface where you can verify extracted data directly beside the original PDF.

Does it support complex itemized tables?

The extraction engine is built to handle structured tables, making it effective for parsing long lists of itemized charges and usage fees.