Core Feature

Five-step AI redaction
that understands context

Most redaction tools find patterns and black them out. Dezcry runs a five-step review that reads what the document itself tells us, then asks AI to spot what those signals missed — and applies that understanding consistently across your entire document set.

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The five steps

Each step does one job well. Together they catch what a single-pass tool would miss, and tell you clearly how every result was found.

1

Quick scan

Read the obvious stuff first

We read what the document itself tells us — email From / To / Cc / Bcc headers, forwarded-email headers in the body, spreadsheet columns labelled "Name" or "Email", and recognisable patterns like email addresses and phone numbers. Fast and very reliable.

2

AI analysis

Context-aware review

The primary AI reads each document in context to spot personal information the quick scan couldn't — names mentioned in a sentence, implied relationships, sensitive details like health, politics, or finances. It understands intent and tells data subjects apart from people mentioned in passing.

3

AI double-check

A second AI reviews every finding

An independent second AI re-reads every finding from the first AI and decides whether it agrees, disagrees, or isn't sure. Acts like a second reviewer — catching false positives and missed items before they reach your queue.

4

Cross-reference

Link the same person across documents

Links the same person or detail across every document in the matter. If "J. Smith", "John Smith" and "john.smith@acme.com" are the same person, we treat them as one so your decision is consistent from one document to the next.

5

Sort for review

Humans where it matters

Sorts every finding by confidence. Very confident items are applied automatically, uncertain ones go to the top of your review queue with a plain-English reason, and low-confidence items are clearly flagged so you can have a look before approving.

Not just for DSARs

Automated redaction is useful wherever sensitive information needs to be removed before documents change hands.

Data Subject Access Requests

Redact third-party personal data from disclosure packages. Meet regulatory deadlines without throwing bodies at the problem.

Privilege Review

Identify and redact legally privileged content before production. Consistent application across the entire document set.

Ad Hoc Redaction

Sensitive board materials, HR investigations, M&A due diligence — any scenario where information needs to be removed before sharing.

Regulatory Investigations

Produce redacted document sets for regulators while protecting information that falls outside the scope of the request.

What makes this different

Context-aware: understands the difference between a data subject and a person mentioned in passing

Configurable confidence thresholds — control how much automation to apply per entity type

Sensitive categories (health, political opinions, sexual orientation) default to stricter thresholds

Checkpoint resume: if a job crashes mid-way, it picks up where it left off

Full audit trail on every redaction decision — who, what, when, and why

Deploy into your own Azure tenancy or a dedicated Dezcry environment — all AI processing stays with your data, no third-party APIs

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