ManageEngine SecureAI

    Organizations are adopting AI agents faster than they are governing them. A team creates an agent in one platform, gives it a model, a knowledge base, and a set of entitlements, and then lets it call tools in other systems on behalf of the people who use it. The agents multiply across platforms, ownership goes unrecorded, and the tool calls they make reach production data without passing through any controls owned by the security team.

    ManageEngine SecureAI governs and protects the AI agents your organization already runs. It discovers agents, models, MCP servers, and entitlements across the directories, agent platforms, and enterprise AI applications in use, and records what each agent can reach and who answers for it. That access is then held to scheduled review and certification, and every tool call an agent makes to an MCP server is evaluated at runtime against a policy before it is forwarded.

    Alongside this, SecureAI assesses how securely each enterprise AI application account is configured and scores the exposure it finds. You work from a single set of records rather than from each AI platform's own console, and apply corrections either in SecureAI or in the platform that owns the object.

    Feature overview

    • AI Agents: See which agents exist across the connected AI platforms, who owns each one, and what it runs on. Unmanaged and privileged agents are listed on their own tabs.
    • MCP Servers: See which of the MCP servers your agents call that are protected by a gateway, and which servers those agents can still reach without any policy check.
    • Models: See which models the agents depend on, which providers they come from, and which agents a model's withdrawal would affect.
    • Agent Ownership Policy: Keep accountability current as agents are discovered instead of attributing each new agent by hand. Run a policy on demand when a batch of agents arrives, and check the assignment history to confirm what it did.
    • Entitlements: Review the grants held across the directories and applications in one place rather than in each source system, and record an owner for the ones that matter.
    • Access Template: Describe the access a job role needs once, then request and sign it off as a single decision instead of granting each entitlement individually.
    • Access Review Request: Act on the governance requests awaiting a decision, and record whether the access is kept or withdrawn. Requests raised and requests assigned sit in the same list.
    • Access Certification Campaign: Put the access held by chosen users or groups in front of a named certifier on a schedule, and have them confirm or revoke it. Every decision is recorded.
    • Governance Assigning Rule: Decide who handles each governance request along with which reviews and approvals it goes through before the access takes effect. Split review, approval, and execution across different help desk technicians, set the business workflow the request follows, and choose who is notified at each stage.
    • AI Risk Assessment: See how securely each enterprise AI application account is configured, and hand the specific problems to whoever runs that account. Each check names the records at fault and the steps that correct them, and a score out of 100 shows whether an account is improving.
    • MCP Server Registry: Register the MCP servers that agents are to reach through a gateway, and confirm each one is connected and exposing the tools expected.
    • MCP Gateways: Route agents through one published URL instead of letting them call each MCP server directly, so that every call passes a point where a policy applies. A server counts as protected once its agents call the gateway URL.
    • Control Policy: Control what agents are allowed to do at the moment they do it depending on the circumstances of the call: where it came from, when it was made, who initiated it, and how risky the agent is. Start from the supplied policies, which carry OWASP Top 10 and MITRE ATLAS™ references, and add policies of your own.
    • Gateway Activity: Investigate an individual tool call: who initiated it; which policies matched; what was sent and what came back; and why the call was allowed, blocked, or redacted.
    • Insight Reports: Follow gateway traffic over time with prebuilt reports on agent usage, tool activity, MCP server errors and latency, and control policy audits.
    • Reports: Generate the agent list a governance review or an audit needs (agents by platform, agents that are blocked, unmanaged, or high privileged) and the tools, knowledge bases, and guardrails those agents use. A report can also set the scope of an access certification campaign.
    • Help Desk Delegation: Give each help desk technician only the part of SecureAI their work requires, using Super Admin, Governance Manager, MCP Gateway Manager, and Risk & Audit Analyst, or roles built from individual tasks. Set a workflow role separately to decide which governance stages a technician can be given.
    • Notification Template: Notify the responsible individuals by email or SMS in your own words when a governance request is created, reviewed, approved, executed, canceled, or close to expiring. Check the notification history when a message has not arrived to see whether it was sent and what stopped it if not.
    • Application Settings: Connect SecureAI to the directories, agent platforms, and enterprise AI applications it reads, and choose the capabilities enabled for each account. Run a sync on demand when a change has just been made.
    • Dashboard: See the agent and MCP server counts, guardrail coverage, the enterprise AI risk score, and recent gateway activity in one place.

    What SecureAI reads

    SecureAI works from the accounts you onboard. Two kinds of account are supported.

    Directories and agent platforms supply the agents, models, MCP servers, and entitlements that the inventories, ownership, certification, and access protection features work on:

    • Microsoft, covering the Microsoft Entra ID directory together with Microsoft Copilot Studio and Microsoft Foundry agents.
    • Google, covering the Google Workspace directory together with Gemini Enterprise Agent Platform reasoning engines.
    • Zia Agents, covering Zia agents and their entitlements.

    Enterprise AI applications are onboarded for risk assessment alone:

    • Anthropic Claude
    • GitHub Copilot