You don't need a frontier model to redact PII

Amazon Nova Pro matched a 4GB open-weight model running on a laptop on German PII redaction: 94% exact-value recall against 93%. Nova Micro, the cheapest model in the family, tied Amazon Comprehend on the same test at roughly a twentieth of the cost per document. And the model that lost hardest was the one fine-tuned for German. Here is what we measured across six approaches, two languages, and four orders of magnitude of cost. The blocker is not the model You have data. It contains names, email addresses, phone numbers, IBANs, dates of birth, health codes, account numbers. You want a language model to summarize it, classify it, extract from it, or index it for search. The model is capable. The data is ready. The personally identifiable information in it is what stops you. GDPR, HIPAA, and data processing agreements restrict where PII can transit, and approval for your cloud provider is not approval for every service inside it. Internal access controls make it worse rather than better: legal can see contract party details and finance cannot, but those boundaries live in your systems of record and dissolve the moment raw data enters a shared RAG index or a prompt template three teams call. An analyst asking for revenue from client X can get an answer derived from a contract they have no clearance to read. Then there is the leak nobody plans for. Production data reaches development accounts constantly, through payloads copied while debugging and dumps used to build test fixtures. And when the compliant workflow takes three days and the non-compliant one takes three minutes, people take the three minutes: a support engineer pastes a complaint into a consumer chatbot, a recruiter runs a CV batch through a free tool. This is not a security failure. It's a workflow design failure. A redaction layer separates the concerns. Process the data before it reaches any model, replace identities with typed placeholders, let the model work on structure and meaning. Which scale are y