What Is Document Sanitisation?

Key takeaway: Document sanitisation is the process of removing or transforming confidential information in a document so it can be safely reused, shared, or ingested by AI systems — without exposing the original client, their data, or their strategy. In consulting, this goes far beyond stripping personal data. It means handling business-sensitive content that standard redaction tools weren't built to detect.

Last updated: March 2026

A working definition

Document sanitisation is the process of identifying and treating confidential information in a document so that it can be used outside its original context — for knowledge reuse, internal training, AI ingestion, or cross-team sharing — without revealing who the work was done for or exposing non-public business information.

The term is sometimes used interchangeably with "redaction," but there's an important distinction. Redaction typically means removing information — black bars, deleted text, blanked-out sections. Sanitisation is broader: it includes removal, but also transformation. Replacing a client name with "[Client]." Swapping a precise revenue figure for a representative range. Substituting a branded colour palette with neutral colours. The goal isn't to destroy information. It's to preserve the intellectual value of the document while eliminating the confidentiality risk.

Why consulting sanitisation is different

Most document sanitisation tools — and most of the content written about the topic — focus on personal data. Names, email addresses, phone numbers, national insurance numbers, medical records. The categories come from data protection regulation: GDPR, HIPAA, PCI-DSS. The tools are built to find them.

In consulting, that's the wrong problem.

A consulting slide deck can contain zero personal data and still be entirely confidential. The sensitive content is business information — the strategic insight that was the whole reason the engagement was commissioned. None of it looks like PII. All of it is confidential.

This is why PII-focused tools fail in consulting. They're solving for a different category of sensitivity — one defined by data protection regulation rather than the realities of consulting deliverables.

What sanitisation actually involves

Proper sanitisation of a consulting deliverable involves several layers:

Direct identifiers. Content that names or unmasks the client. The obvious cases — client names, logos, project codes, email addresses — are caught by any competent process. Direct identification extends further than that, into content where context matters more than pattern matching.

Indirect inference risk. This is where most approaches fall apart. Individually harmless details can combine across a slide deck to identify the client. A 60-slide strategy deck might have the client name removed from every slide and still be identifiable from the accumulation of contextual details. Handling this requires evaluating the document as a whole, not slide by slide. See why find-and-replace approaches can't solve this.

Non-public information. Content that's confidential regardless of whether it identifies the client. Even perfectly anonymised, this information may be inappropriate for broad distribution.

Visual and structural content. Visual elements carry sensitivity that's invisible to text-only tools — detecting them requires context-aware, multimodal analysis that processes both the visual and textual layers of a document.

Why it matters now

Consulting firms have always had a sanitisation problem. What's changed is the cost of not solving it.

Firms investing in AI-powered knowledge management — enterprise search, RAG systems, internal assistants — need clean content to feed those systems. Building AI-ready knowledge bases starts with sanitisation. You can't build a useful knowledge base on 5% of your deliverables because the other 95% are locked behind confidentiality restrictions. And you can't feed unsanitised content into an AI system without creating a new category of data leakage risk.

Document sanitisation is the prerequisite. It's the step that has to happen before any of the AI-powered knowledge reuse that firms are investing millions in can actually work. For a comprehensive look at how to approach this, see our complete guide to consulting redaction.

Knovari's platform was built for exactly this problem — automated, context-aware sanitisation of consulting PowerPoint decks, using multimodal analysis to detect the full range of sensitivity that manual review and keyword tools miss. If you're evaluating how to make your firm's past deliverables safely accessible, we should talk.