Unosecur's Unified Identity Fabric ingests signals from 100+ integrations across cloud infrastructure, SaaS apps, IDPs, and on-prem systems to map every human identity, NHI, and AI agent into one correlated view. The graph resolves nested role chains, inherited permissions, group memberships, and cross-environment access paths that stay invisible when each tool only sees its own domain. Runtime ingestion means the graph reflects current state as fast as the source environment reports changes, eliminating stale snapshots that leave security teams deciding on outdated data. Continuous posture evaluation runs against this graph. Every identity receives a risk score derived from the entitlement gap between granted permissions and actual usage, weighted by environment sensitivity and credential hygiene. The platform surfaces privilege creep, toxic permission combinations creating escalation paths across trust boundaries, orphaned credentials persisting without an owner, and weakened MFA enforcement the moment these conditions form. Posture drift that would sit undetected until the next quarterly review is caught at runtime and routed to remediation. Threat detection is grounded in identity context, not event volume. Detection rules spanning credential stuffing, token theft, session hijacking, privilege escalation, lateral movement, and compromised service credential usage are mapped to MITRE ATT&CK techniques. The correlation engine evaluates every anomaly against the identity's behavioral baseline, access scope, and blast radius to produce high-fidelity alerts reflecting actual organizational risk. Where threshold-based systems generate alert fatigue by treating every anomaly equally, Unosecur scores a developer with read-only staging access and an admin with production-wide permissions at fundamentally different severity levels for the same deviation. NHIs and AI agents receive the same governance rigor applied to human users. Every NHI is mapped to a human owner, tracked by credential age and rotation status, and scored by blast radius so teams prioritize the riskiest orphans and most overprivileged service accounts first. Every AI agent is classified by type and deployment method, mapped to its granted permissions and resources, and monitored for behavioral patterns including IAM policy modifications, credential theft, and unauthorized data exfiltration. Shadow agents deployed outside provisioning workflows are discovered and flagged alongside sanctioned ones. Standing privileges are replaced with time-bound, usage-scoped access. The IAMOps engine analyzes actual usage patterns to generate least-privilege policies that eliminate the entitlement gap without breaking production workflows. Just-in-time access elevates permissions on approval and revokes them automatically when the window closes. No-code role creation lets teams build custom roles by selecting specific permissions, with AI-generated summaries giving approvers context for fast, informed decisions. All three capabilities route through existing ticketing and approval workflows. Response closes the loop between detection and containment. Critical findings surface a quarantine action that isolates the compromised identity across every connected system in a single step, cutting hours from attacker dwell time. Medium and high findings route to investigation with the full identity chain, cross-environment permissions, and blast radius attached. Low-severity findings are reviewed and suppressed with logged rationale. Every decision, from detection trigger to response action, is captured as an auditable record.