PII redaction at scale
Sharing documents for analytics, training, or third-party work requires PII to be removed. Doing it manually is slow, error-prone and never scales past a handful of files.
AI detects and redacts PII across structured and unstructured data with auditable controls, producing clean artefacts ready for downstream use.
- 01
The pipeline detects PII categories defined in your policy (names, addresses, IDs, account numbers, sensitive attributes).
- 02
Detection confidence is logged per entity, with low-confidence cases queued for human review.
- 03
Redaction preserves document structure and analytical value where possible.
- 04
Every redaction decision is logged for audit, with the original retained in a restricted vault.
- 05
A dashboard shows redaction volume, PII categories found, and reviewer override rate.
at 95 percent plus detection accuracy for common PII categories.
Ranges drawn from production deployments and public enterprise benchmarks. For a specific rupee or dollar figure tailored to your volume, use the calculator below.
Prerequisites for a clean deployment.
- A defined PII schema aligned to your data protection policy
- Sample documents across the use cases you need to cover
- An approved redaction policy signed off by compliance
- A reviewer team to own low-confidence cases
Put your own numbers on it.
“At 1,000 documents a month and a loaded monthly cost of ₹1,50,000 per person, pii redaction at scale would typically save ₹13 L to ₹14 L a year.”
Range uses this use case’s typical automation rate (85 to 95 percent) against the baseline time per task for documents work, with your cost per person converted at 160 working hours a month.
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