The text discusses a new, open-source system for redacting personally identifiable information (PII) from text data. The system uses two fine-tuned large language models to detect and redact PII, achieving near-perfect recall rates for highly sensitive information such as social security numbers, IP addresses, passport numbers, and driver's licenses. The system outperforms existing open-source libraries like Presidio in some categories, with improvements ranging from 16.82% to 46.74%. The text also highlights the importance of understanding detection rates, which represent how effectively a system identifies different types of personal information in text data. While real-world performance may vary depending on factors such as text quality and formatting, the system is designed to be easy to use and integrate into existing workflows.