AI Classification

Primary AI Classification is an AI-driven policy intelligence platform designed for enterprise unified control planes. It ingests telemetry from across an organization's environment — including users, AI agents, applications, devices, data systems, APIs, models, networks, and infrastructure — and uses machine learning and behavioral reasoning to correlate events into coherent workflows rather than treating each event as an isolated alert. Core functions: - Telemetry correlation: Collects and connects signals from identity platforms, devices, browsers, applications, data systems, APIs, models, networks, and security infrastructure to reconstruct full activity sequences. - Risk detection: Identifies multi-step risk patterns such as compromised identity, agent overreach, coordinated data exfiltration, and policy drift by analyzing relationships across north-south and east-west traffic. - Policy generation: Translates detected risk patterns into reviewable policy recommendations expressed through visual controls, natural language, or advanced rule logic, with supporting evidence and reasoning. - Policy simulation: Tests proposed controls against historical and live activity to estimate protection coverage and operational disruption before deployment. - Enforcement coordination: Applies approved policies across connected enforcement points including identity, DLP, browser, endpoint, network, cloud, application, and AI agent controls. - Continuous policy refinement: Monitors for policy drift, redundant rules, and outdated assumptions, recommending targeted updates as enterprise behavior evolves. - Human-in-the-loop governance: Retains human judgment for consequential decisions, allowing administrators to approve, modify, reject, or automate AI-generated recommendations. The platform operates as a closed-loop system in which telemetry informs detection, detection drives policy, and policy outcomes improve future decisions.