Opal Security Intelligence is an AI-driven identity governance and access management platform designed to handle access decisions for human users, service accounts, and AI agents. The platform ingests real-time identity data and applies policy intelligence alongside risk signals to dynamically manage access across an organization's environment. It is built to support the full identity lifecycle — from onboarding through break-glass access scenarios. Opal operates on a progressively autonomous model: - Initially, it augments human decision-making by surfacing risk intelligence, usage data, peer benchmarking, and business context to help security and IT teams make faster, informed access approvals. - Over time, the platform learns from human decisions — what gets approved, flagged, or escalated — and begins suggesting automations such as auto-approving low-risk requests, auto-revoking unused access, and escalating anomalies. - Eventually, it can enforce access policies autonomously, reducing the need for human involvement in routine, well-understood access decisions. Key capabilities include context-aware access orchestration using AI-assisted risk scoring and behavioral signals, support for non-human identities (AI agents and automated workloads) with ephemeral access and auditability, continuous least privilege enforcement through usage-based rightsizing, and AI-driven policy simulation that previews policy impacts and suggests improvements in real time. The platform also provides a risk layer that surfaces prioritized risk alerts, actionable remediation flows, and human oversight tooling for security leaders.