<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Pii on René Zander | AI Automation Consultant</title><link>https://renezander.com/tags/pii/</link><description>Recent content in Pii on René Zander | AI Automation Consultant</description><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 21 Apr 2026 10:00:00 +0000</lastBuildDate><atom:link href="https://renezander.com/tags/pii/index.xml" rel="self" type="application/rss+xml"/><item><title>95% of PII Redaction Doesn't Need an LLM. The Other 5% Is Where Your Masker Leaks.</title><link>https://renezander.com/blog/pii-redaction-deterministic-vs-llm/</link><pubDate>Tue, 21 Apr 2026 10:00:00 +0000</pubDate><guid>https://renezander.com/blog/pii-redaction-deterministic-vs-llm/</guid><description>&lt;p&gt;A VP at an SAP shop told me recently: &amp;ldquo;Every time we copy production to our lower environments, PII leaks. And no, we&amp;rsquo;re not throwing an LLM at it. That&amp;rsquo;s a thousand times the compute of what we already run.&amp;rdquo;&lt;/p&gt;
&lt;p&gt;He&amp;rsquo;s right.&lt;/p&gt;
&lt;p&gt;Most of the PII redaction problem in enterprise data isn&amp;rsquo;t a neural network problem. It&amp;rsquo;s a lookup table problem. And the incumbents already solve it. SAP TDMS, Delphix, Informatica, IBM InfoSphere Optim. All schema-aware. All row-level. All deterministic.&lt;/p&gt;</description></item></channel></rss>