Recall Brings Implicit Learning to the SOC

Torq Recall captures institutional knowledge from security teams’ daily workflows without extra manual effort, learning implicitly from resolved cases and analyst notes to apply historical context to new alerts. Instead of standard semantic search (RAG), Recall uses deterministic retrieval on exact observable matches such as IP addresses, file hashes, and URLs, and is designed as “honest AI” that flags conflicting precedent or poor data quality rather than forcing unreliable recommendations.