Synthetic Invoice Dataset Generator

A synthetic dataset is generated by a program rather than collected from real life. The goal: be flexible and rich enough to power research with machine learning models — without exposing sensitive source data.

Building ML models for invoice recognition requires large, annotated training datasets. Those datasets aren’t publicly available, because invoices are sensitive by nature. A document generator that produces realistic invoice variations is a practical way around that constraint.

What’s inside

• A method for generating synthetic invoice datasets at scale
• Per-document unique render layouts and designs
• Field-name variation that mirrors real-world invoice examples
• An approach that preserves data privacy while still supporting ML training

ML and data engineering teams that need to train invoice or document-understanding models without exposing customer or vendor data — and the compliance and privacy stakeholders who sign off on that work.