SafeRoom
A local, customer-aware confidentiality layer for preparing legal documents for external AI analysis.
Protect the client. Preserve the contract.
The problem begins before the AI prompt.
A legal document can reveal a client through far more than the visible party name. Names, email domains, signature blocks, comments, tracked changes, metadata, thumbnails, project names and contextual clues can all carry identity into an external AI workflow.
Protect the customer first
SafeRoom starts with the protected client, then classifies counterparties, people, affiliates and other entities relative to that customer.
Preserve legal meaning
Contract structure, clause wording, commercial terms, comments and tracked changes remain useful for analysis wherever possible.
Local by design
Document processing is designed to happen on the user's computer, with the original never overwritten and uncertainty shown for review.
Five simple steps, almost no technical decisions.
The normal workflow is intentionally minimal. SafeRoom infers what it can, asks the user to confirm the customer, and only surfaces uncertain items that need attention.
Open or drop
Start with a DOCX or supported PDF.
Confirm
Answer the core question, who are we protecting?
Analyse
Run local detection across text, identifiers and hidden document artefacts.
Review
Check only uncertain items and contextual clues that remain.
Use
Copy Safe Text or save a sanitised working copy and audit.
Semantic replacements keep the relationships intact.
Instead of replacing everything with generic labels, SafeRoom uses role-aware names that preserve the difference between the customer, counterparty, affiliates and other actors.
SafeRoom looks beyond visible body text.
The Word workflow is designed around the places confidential identity actually survives in negotiated documents.
Could someone still work out who the customer or matter is?
SafeRoom treats contextual confidentiality as a separate risk. Project codenames, matter numbers, internal URLs, customer-specific systems, unusual locations and identifying transaction descriptions can all survive ordinary anonymisation.
Customer protection check
One problem, solved extremely well.
The initial release is focused on preparing Word agreements for external AI review in a few clicks, completely locally. PDF text extraction follows, with OCR and full PDF redaction treated as later controlled phases.
SafeRoom will become part of the wider LegalOps product suite.
The longer-term direction includes Word integration, broader PDF support, policy profiles, batch processing, controlled intake and optional Master Contract Log integration.