Saviynt has launched an identity security solution designed to govern AI agents alongside human and non-human identities across enterprise environments.
The announcement positions the solution as a response to a growing security gap in enterprise AI deployments, where agents operate autonomously at machine speed but largely outside the scope of existing identity and access management (IAM) frameworks.
According to Saviynt, 91% of enterprises currently face blind risk exposure stemming from unmanaged AI agent activity. AI agents are being used to write code, execute financial transactions, respond to customers, and orchestrate business workflows, yet most organisations lack the tooling to monitor or restrict what those agents do once deployed.
Three-pillar governance architecture
The platform is built around three core capabilities. The first is Identity Security Posture Management (ISPM) for AI, which delivers continuous discovery of all autonomous agents, including unauthorised ones, and surfaces real-time risks and over-privileged access. The second is Identity Lifecycle Management, which governs each agent from registration through decommissioning, assigning ownership to ensure accountability throughout. The third is an Agent Access Gateway, which evaluates every agent interaction in real time and blocks unauthorised activity, whether agent-to-agent or agent-to-enterprise application.
The solution integrates with major agent development environments, including Amazon Bedrock, Microsoft Copilot Studio, Google Vertex AI, ServiceNow AI, and Salesforce Agentforce. It also ingests external risk signals from security partners including CrowdStrike, Zscaler, Wiz, and Cyera, providing security teams with a broader view of AI-related risk across their infrastructure.
Saviynt has indicated that the platform was developed in close collaboration with enterprises already running agents in production, among them Hertz, The Auto Club Group, and UKG. These organisations participated as design partners, shaping the platform around real-world operational requirements at Fortune 500 scale.
Governance gap in enterprise AI
The launch reflects a broader tension in enterprise AI adoption: the pace at which AI agents are being deployed has outrun the identity security models originally designed for human users and deterministic workflows. Legacy IAM infrastructure, built on static access controls and periodic reviews, is poorly suited to environments where agents act continuously and make autonomous decisions in real time.
Saviynt's approach treats AI agents with the same governance rigour applied to human identities, an important distinction as regulatory scrutiny of AI systems increases across major markets, including the EU, where the AI Act introduces risk-based requirements for automated decision-making systems in enterprise contexts.
The platform is designed to support a range of developer profiles, from pro-code engineers to no-code business users, reflecting the varied ways in which AI agents are being built and deployed across organisations today.
