TCI Insights
Risks and techniques around obfuscation, redaction, and privacy in LLM pipelines.
LLM-powered redaction tools can fail in subtle, dangerous ways — reconstructing supposedly removed PII from context, leaking information through embeddings, or hallucinating redaction where none occurred.
Documents processed through LLM redaction pipelines can contain adversarial text that manipulates the model into preserving sensitive information. This attack vector is unique to AI-powered redaction.
LLMs offer powerful contextual PII detection, but only within a pipeline that compensates for their weaknesses. Here's how TCI architects redaction systems that combine LLM intelligence with deterministic guarantees.