Local-First Reversible PII Scrubber for AI Workflows Using ONNX and Regex
By
tjruesch
Toasted golden, schmeared with insight. Top of the rack.
Summary
The article discusses a technical solution to the privacy-translation paradox in AI workflows, where teams need to translate user content using third-party AI services but cannot send Personally Identifiable Information (PII). It introduces a local-first, reversible PII scrubber that uses ONNX and Regex to redact sensitive information while preserving translation quality. The system allows for reversible scrubbing so that translations can be rehydrated with original PII after processing, addressing the problem where traditional redaction destroys context needed for accurate translation.
Key quotes
· 5 pulledThe Privacy-Translation Paradox: Every engineering team eventually faces the same dilemma: You need to translate user content (support tickets, documents, chat logs) using high-quality engines like DeepL or LLMs like GPT-5, but you strictly cannot send Personally Identifiable Information (PII) to third-party APIs
The solution is seemingly simple: Redact the data. The problem? Redaction destroys translation quality.
If you scrub 'John bought a generic gift for Mary' into 'PERSON bought a generic gift for PERSON,' the translation engine loses the context needed for accurate translation
A local-first, reversible PII scrubber that uses ONNX and Regex to address this privacy-translation paradox
The system allows for reversible scrubbing so that translations can be rehydrated with original PII after processing
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