Span-01

About Span-01

Span-01 is a hyper-parallel reasoning classifier built to detect complex behaviors across long production traces in a single forward pass. Rather than generating tokens sequentially, it reasons over natural-language behavior definitions and returns direct probabilities for present, absent, and not_observable. The model is trained for general classification reasoning with RLAIF before being specialized for behavior detection, allowing it to apply previously unseen definitions to new behaviors and domains instead of relying on a fixed taxonomy. At inference time, hyper-parallel definition branches evaluate multiple behaviors against the same trace context simultaneously, while hybrid attention helps preserve reasoning over long, complex inputs. Span-01 is designed for production monitoring across safety, reliability, grounding, agent behavior, and response quality, including jailbreak and prompt injection detection, privacy, and secrets.