USE CASE

Take Control of Shadow AI and Agentic Systems

Unreviewed model swaps and new tools quietly expand your attack surface. Miggo gives security teams a live view of AI behavior in production: what’s running, what it touches, and which changes create real risk.

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Why AI Runtime Observability Matters

Stop Shadow Drift Before It Becomes Enterprise Risk

Developers swap models and add tools to solve immediate problems without security review. Miggo makes this "hidden-by-design" risk visible by capturing the dynamic assembly of agents as it happens.

Close the AI Governance Gap

Miggo automatically maps what’s actually running in production, from agents, models, tools, to frameworks, MCP integrations, and connected data sources based on real execution. Together with deep runtime execution and data access flows and AppDNA mapping, Miggo enables security teams to gain control of AI governance.

Replace Assumptions with Evidence

When behavior changes daily, policies written at deployment go stale. AI-BOM and guardrails give your security teams a living source of truth and enforceable control.

How Miggo Delivers AI Runtime Observability

Continuous Discovery & Control over Your Agentic Topology

Detect AI App and Agentic Risk With Context

Miggo surfaces actionable findings grounded in runtime evidence, including:

Active, reachable CVEs and exploitable paths

Unapproved model usage with data access context

Dangerous tool usage (e.g., code execution) tied to the agents invoking it

Govern AI Behavior with AI Runtime Observability

Miggo turns visibility into control by enabling teams to:

Detect behavioral drift (models, tools, data access) over time

Review, approve, or reject changes before they expand exposure

Enforce compliance with runtime evidence (e.g., internal policy, EU AI Act readiness)

Prioritize by Blast Radius

Miggo scores risk based on what matters most: data exposure, system impact, and internet reachability—so teams focus on the changes that can actually hurt the business.

Miggo provides the visibility and control required to govern AI safely at scale.