Keyword filters are a solved problem — solved by predators. They learned years ago to spell things differently, avoid flagged words, and simply groom slowly enough that no single message triggers a filter. The result: every major platform relying solely on keyword detection is running safety infrastructure that the most dangerous users have already mapped and bypassed. SENTINEL takes a different approach. Instead of asking "does this message contain a bad word?", it asks "does this person's behavior, over time, resemble the trajectory of a predator approaching a minor?" This post covers how that works at an engineering level. The Four Signal Layers SENTINEL's risk scoring is built on four independent signal layers feeding into a weighted ensemble: 1. Linguistic Analysis NLP signals beyond keyword matching: sentiment trajectory across a conversation, escalation in intimacy markers, attempts to isolate the target from other users, and lexical similarity to known grooming conversation patterns.…