AI / Model Training

Labeled synthetic documents at the volume model training needs, with no real borrower data in your pipeline. Large data sets on demand to satiate model hunger.

AI / Model Training

Labeled synthetic documents at the volume model training needs, with no real borrower data in your pipeline. Large data sets on demand to satiate model hunger.

AI / Model Training

Labeled synthetic documents at the volume model training needs, with no real borrower data in your pipeline. Large data sets on demand to satiate model hunger.

What it is

STICKBUG produces labeled, fully synthetic mortgage documents at the volume model training and testing require, without exposing real borrower data to your pipeline or third-party vendors.

What you get

Volume: Generate large sets of realistic documents rather than scraping or anonymizing scarce production files.

Coverage: Synthetic data on-demand for the true edge case scenarios that are rarely found in legally restricted production data.

Structure: Output is mapped to MISMO and aligns to UMDP standards, so documents carry consistent, standards-aligned structure your models can learn from.

Safety: No real borrower PII enters your training pipeline or leaves your control.

When to use it

  • Training document classification and extraction models

  • Building test sets for model validation

  • Augmenting thin or imbalanced real-world datasets

  • Sharing realistic data with vendors without privacy exposure

Why it works

Real loan data is exactly what model teams need and exactly what they are least able to use freely. Synthetic, standards-aligned files close that gap.

Want to see it in action?

Want to see it in action?

Request a demo to get started.

Request a demo to get started.

Realistic data. Zero exposure.

Realistic data.
Zero exposure.

Realistic data.
Zero Exposure.