Summary
- Validation rules are found automatically, not configured by hand.
- Issues are corrected automatically wherever possible, not just flagged.
- Clean data is treated as a requirement, not a nice-to-have.
- Sits underneath your existing HR systems. No need to replace what you use.
The Problem
You can't do anything useful with bad data.
Automation, reporting, and every AI agent you connect to your HR systems are only as good as the data underneath them. Get that wrong, and it doesn’t matter how sophisticated the layer on top is. It’s building on a foundation that can’t hold it up.
How It Works
Validation rules are found automatically, not typed in by hand.
Instead of asking your team to configure every validation rule one by one, Data Validation identifies the rules your data should follow directly from the data and processes you already have, keeping manual setup to a minimum.
Automatic Correction
Where possible, it doesn't just flag the problem. It fixes it.
A list of data issues for someone to work through manually is only half the job. Wherever a correction can be made automatically, Data Validation makes it. That closes the loop instead of creating another queue for your team.
Better Together
Data Validation + Integration Hub
Data is validated and corrected before it ever reaches the next system.Data Validation + Peoplebase
Keep the one directory your AI tools rely on clean from the start.