Use cases

Common AI operating problems.
Direct controls.

Deploy Cortega where your AI runs: Edge or Core. Define posture, route traffic, prevent attacks, and turn governed traffic into intelligence — including from gateways you already run.

Use case 01

"We handle patient, financial, or government data and can't let it reach external AI providers."

For healthcare, financial services, defense, public sector, and regulated technology teams.

Cortega inspects AI traffic before it leaves the boundary. Sensitive data is detected, blocked, redacted, or routed to an approved destination — deterministically, with no third-party scanner.

CUI and PII detections tracked by surface and department.

Use case 02

"Employees are creating their own agents and IT doesn't know about them."

For organizations where employees use AI tools faster than IT can approve them.

Cortega gives IT a way to redirect unmanaged AI traffic into governed paths using existing enterprise controls. Unmanaged traffic becomes a first-class governance signal.

Shadow AI policy can alert or block unauthorized users, models, MCP servers, and tool calls.

Use case 03

"We have agents running everywhere and we don't know what they're all doing."

For CIO, IT, security, and platform teams with AI activity spread across groups.

Cortega creates a live view of AI usage from the traffic path — including from gateways you already run. Who called, what model was requested, what data moved, what policy fired.

Gateway events show users, departments, requested models, used models, and timestamps.

Use case 04

"Our security or legal team is blocking our AI program."

For AI program owners who need security, legal, and governance teams to say yes.

Cortega turns an abstract risk debate into evidence. Route a single real request through the gateway, show the policy decision and replayable log to the security reviewer.

Policy controls show who can use which models and MCP tools.

Use case 05

"Our AI bill is growing and we don't know which agents are responsible."

For IT, engineering, finance, and platform teams trying to attribute and control AI spend.

Cortega attributes spend to the caller, app, team, model, provider, and environment because all governed traffic passes through the control point.

Budget controls enforce spend by scope, period, and mode.

Use case 06

"We're building agents for a government or healthcare customer and they need compliance evidence."

For vendors and enterprises that need audit-ready proof, not AI governance slideware.

Cortega records the operational evidence auditors ask for — identity, data categories, policy decision, approval, model, provider, outcome — mapped to control IDs.

Security and compliance teams see unauthorized agents, models, MCP servers, and more.

Use case 07

"We need to understand what is happening across AI usage without becoming log analysts."

For IT, security, finance, and compliance leaders who need plain-English answers.

Cortega Insights turns governed traffic — from Cortega gateways and yours — into an explorable AI usage map built on OTEL-standard data.

Insights turns gateway telemetry into an explorable map of AI activity.

Use case 08

"MCP servers are becoming another AI surface we need to govern."

For enterprises adopting MCP tools, internal tool servers, and agent-to-tool workflows.

Cortega brings MCP servers into the same identity, policy, audit, and observability model as model calls and agent traffic — with bidirectional 2025↔2026 protocol bridging.

MCP servers are registered, restricted, monitored, and governed as first-class AI surfaces.

Tell us which use case sounds like you.

We'll map your current AI traffic path, the controls you need, and the fastest way to experience Cortega in your environment.

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Common AI operating problems.Direct controls.