The market has incumbents who observe and report, and emerging players moving toward real-time controls. But every incumbent shares an architectural commitment: supervised learning pipelines with scheduled model updates. When a novel agent threat appears, their detection layer waits for the next release cycle.

ForgeProof differentiates on two architectural commitments, not one. Real-time enforcement at the moment of agent action — vendor-agnostic, signed, auditable. And adaptive detection grounded in published research — novel threat classes integrated in hours via few-shot learning, not weeks via retraining.

Competitors can add enforcement features. They cannot retrofit the detection architecture without a foundational rebuild. The combination is the category position, and it’s defensible because it’s architectural, not featural.