Torq unveils SOC Brain, a self-learning layer for its AI SOC platform
Security hyperautomation platform company Torq Ltd. today introduced Torq SOC Brain, a new layer of its artificial intelligence security operations center platform that trains on a customer’s own investigation history and analyst decisions instead of treating every alert as a fresh problem.
Torq said most autonomous investigation tools retrieve similar past cases and pass them to a large language model at the point of decision. Its argument is that retrieval is not learning. SOC Brain is built to reason from precedent, absorb the way a given security operations center weighs evidence and revise its judgment after every closed investigation.
Three capabilities sit underneath it.
Torq Recall pulls up relevant historical cases using deterministic matching on observables such as IP addresses, file hashes, URLs and hostnames, then ranks them by relevance and works out how earlier analyst decisions should bear on the verdict at hand. It reads analyst notes, identifies conflicting precedent and adjusts confidence according to how strong the evidence is. Analysts do not have to tag cases or write rules for any of it to work.
