Keep buyer knowledge inside.
Scan locally before text crosses into an AI product.
Local boundary: text is processed in this browser. Model files are fetched on first use; your input is not uploaded by this page.
Exact spans, not a vague score.
Run the bundled sample or paste a draft. Each finding will show its text, type, rule-tagger provenance, character offsets, and detection engine.
Found0
Selected0
Coverage—
Only sanitized text exits.
No scan yet.
Sanitized promptHASH —
Your reviewed result will appear here before any download.
Interpretation: a clean scan is not proof of safety. Rule-based NLP can miss codenames and specialized trade secrets; review business context before sharing.
Knowledge loss begins before “send.”
The useful decision happens at the boundary: which exact words need to cross, and which can be replaced without changing the task?
Local NLP tags semantic entities.The bundled rule tagger identifies person and organization names with exact offsets and provenance, without sending text to a model host.
Patterns catch exact structured disclosures.Email, phone, money, project, and account-like spans remain available if the NLP module cannot load.
You decide every crossing.Selected replacements update the visible prompt immediately; export only preserves evidence of work already completed.