AI agents are rapidly becoming part of everyday business operations - but governing them hasn't kept pace.
Traditional security tools discover AI activity. Governance platforms understand business risk.

Every AI agent introduces a new operational identity with its own permissions, data access, decision-making capabilities, and relationships across the business:
For CISOs, every new agent expands the organization's attack surface.
For GRC teams, every new agent introduces new governance decisions, compliance gaps, and policy risk.

Unlike traditional software, AI agents aren't introduced through a centralized procurement process. They're created by employees, teams, and developers across the organization, making visibility, ownership, and governance dramatically more difficult.

The challenge is no longer discovering AI. It's understanding which AI agents expand your risk surface and which can be trusted inside your organization.

That's why we built AI Agent Posture Management.

Want to see this in action?
Join us September 9 for a live walkthrough of Mine’s AI Governance platform, where we’ll show how to identify which AI agents are risky, why, and what to do next: Save your seat here.

Understand Which AI Agent Deserves Your Attention

Every organization has hundreds, if not thousands, of AI agents.
The challenge isn't discovering them. It's knowing which ones deserve your attention.

Agent Posture Management continuously discovers AI agents, skills, LLMs, Tools, MCP servers, and related AI assets across employee endpoints, giving security teams complete visibility into how AI is being used across the business.

Visibility is only the starting point. Security teams need to understand where risk exists, what deserves immediate attention, and what can be confidently approved.

Posture Changes the Conversation

Security teams already know how to evaluate software risk.

They rely on software inventories, SBOMs, dependencies, CVEs, identities, permissions, OAuth scopes, exposed secrets, network exposure, and third-party risk to understand the security posture of applications.

Those signals remain essential.

AI agents introduce another layer of operational risk that technical controls alone cannot explain.

An agent may have no known vulnerabilities, approved permissions, and secure authentication, yet still introduce significant business risk because it accesses regulated data, violates internal AI policies, interacts with unapproved vendors, or makes autonomous decisions without oversight.

This is where AI discovery ends - and Agent Posture Management begins.

Every discovered AI agent is continuously evaluated using the governance context security teams already rely on to manage organizational risk.

Mine enriches endpoint discovery with the GRC context security teams already rely on to govern risk. Business purpose, sensitive data access, vendor approvals, policy compliance, ownership, agent lineage, and skill vulnerabilities are evaluated together to reveal each agent's true business risk.

That continuous posture drives governance actions, including assessments, approvals, remediation workflows, monitoring, and policy enforcement based on organizational risk.

Instead of asking What AI agents exist?, CISOs can answer the questions that drive real governance.

• Which AI agents have access to regulated data?
• Where are unapproved vendors introducing AI risk?
• Which autonomous workflows violate internal AI policies?
• Which AI can be confidently approved?
• Where is business risk accumulating across connected agents?

Every AI agent has a posture. Mine gives security teams the context to understand what matters, prioritize risk, and take the right action.

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Agent Lineage Reveals the Risk You Can't See

Security teams have spent years securing software supply chains because they understand that risk rarely exists within a single application. It emerges through relationships, dependencies, and third-party services.

AI introduces an entirely new execution model - one where agents invoke other agents, activate tools, access data, and trigger autonomous workflows across the business.

A single AI agent may invoke another agent, connect to multiple MCP servers, retrieve sensitive documents, call external APIs, interact with SaaS applications, and trigger downstream workflows before completing a single task.

Looking at one agent in isolation only tells part of the story.

The real risk lies in what happens next.
That's why lineage alone isn't enough. Security teams also need the governance context that explains whether that execution path violates policy, reaches regulated data, or introduces unacceptable third-party risk.

An agent with limited permissions can become high risk because of the systems it activates, the sensitive data it reaches, or the vendors and models it relies on.

Mine combines agent lineage with GRC context to expose how risk moves across AI agents, business systems, third-party vendors, and sensitive data. Security teams gain a continuous view of where risk originates, how it propagates, and which governance action should come next.

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Govern AI with Confidence

AI adoption will continue to accelerate across every business function.

The organizations that lead won't be the ones that simply discover the most AI agents. They'll be the ones that understand which agents can be trusted, which require oversight, and which should never reach production.

By combining AI discovery, GRC intelligence, agent lineage, and automated governance, Agent Posture Management gives security leaders the continuous understanding they need to stay ahead of AI risk while accelerating responsible AI adoption.

Every AI agent has a posture. The organizations that understand it will be the ones that lead AI adoption securely.

Ready to see Agent Posture Management in action?
Schedule a demo and See how Mine helps security teams discover, assess, and govern AI agents using the GRC context and lineage traditional AI discovery tools can't provide.

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