Quint Ai

Quint Ai is a behavioral security platform designed specifically for monitoring and governing the actions of AI agents at the operating system level. It addresses the unique security and compliance challenges posed by autonomous agents in enterprise environments, focusing on real-time oversight and risk management without requiring code changes to the agents themselves.

The platform intercepts every action performed by AI agents on a machine, scoring each for risk in real time and generating a tamper-proof, cryptographically signed audit trail. This audit trail uses Ed25519 signatures to ensure the integrity of the recorded actions. Quint provides fleet-wide visibility, allowing organizations to see risk scores, behavioral baselines, and detect anomalies across all agents from a unified interface. It establishes behavioral baselines automatically, learning normal patterns for each agent, machine, user, team, enterprise, and even at a global industry level, using a graph neural network to encode relationships and detect deviations.

Enforcement is performed at the edge with sub-10 millisecond latency, enabling the platform to block, flag, or allow agent actions in real time. The system captures both the declared intent and the actual execution of each agent action, comparing the two to detect and respond to divergences before incidents occur. Quint operates independently of large language models in its enforcement path, opting for deterministic, reproducible decision-making to reduce attack surfaces and ensure auditability.

Deployment is achieved via a signed package that can be distributed using tools such as Jamf, Intune, or Kandji, supporting a one-time installation process with no need for agent code modification. The platform is designed for organizations operating or overseeing multiple AI agents, including roles such as engineering, data science, support, and operations, where compliance and security oversight of autonomous systems is critical.