Example post: Why manual redaction doesn't scale
[Example content] Every legal, finance, or healthcare team eventually hits the same wall: a document review process built around a black marker or a PDF redaction tool doesn't scale past a handful of files a week.
The problem isn't effort — it's that manual redaction asks a human to catch every instance of sensitive information across every page, every time, with zero tolerance for a missed name or account number. That's a search problem, not a diligence problem, and search is what software is good at.
Where the time actually goes
In most manual workflows, the bottleneck isn't marking up the page — it's finding what needs marking in the first place. Reviewers re-read the same document several times looking for different categories of sensitive data, which is slow and inconsistent between reviewers.
What changes with automated detection
An AI-assisted first pass doesn't replace review — it changes what review is for. Instead of hunting for sensitive data, a reviewer confirms or adjusts what's already been flagged, which is a faster and more consistent task regardless of document length.
That's the shift this blog will keep coming back to: redaction tooling isn't about removing the human from the loop, it's about giving them a better starting point.