PEyeEye.ai
PII Redaction and Rehydration for LLM Prompts, Apps & Agents
PEyeEye.ai launched on April 25, 2026.
What it does
Easily Redact PII before it hits the LLM. Rehydrate it on the way back. Deterministic tokens, stateless sealed sessions, zero retention. - One API call - 62 entities detected out of the box - Bring your own custom PII entities - Python and TypeScript SDKs support
Redact PII before your prompts hit an LLM and rehydrate it on the way back. Deterministic tokens, stateless sealed sessions, zero retention. One API call, dozens of entity types, with Python, TypeScript, and Go SDKs.
Redact PII on the way into your LLM prompts and rehydrate it on the way out — in a single round-trip, with deterministic tokens and zero data retention. Your app calls /v1/redact with the user's text. TLS 1.3, optional client-side pre-hashing. Hybrid detector (regex + ML NER) identifies 62 entity types. Each value is replaced with a stable placeholder like [PERSON_1] . Forward the redacted text to OpenAI, Anthropic, Gemini, your fine-tune — anywhere. The model never sees a real name, number, or address. Pass the reply + session back through /v1/rehydrate . Tokens become real values again. The SDK wraps both endpoints into a single .shield() call that works with your existing LLM client. Or…from peyeeye.ai
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Hi HN, I’m one of the maintainers of Bridge Anonymization. We built this because the existing solutions for translating sensitive user content are insufficient for many of our privacy-concious clients (Governments, Banks, Healthcare, etc.). We couldn't send PII to third-party APIs, but standard redaction destroyed the translation quality. If you scrub "John" to "[PERSON]", the translation engine loses gender context (often defaulting to masculine), which breaks grammatical agreement in languages like French or German. So we built a reversible, local-first pipeline for Node.js/Bun. Here…
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