> For the complete documentation index, see [llms.txt](https://docs.uptiq.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.uptiq.ai/ai-workbench-qore/start-here/control-center.md).
# Control Center
Manage platform governance, monitoring, access, usage, quality, cost control, and audit.
Control Center is the account-wide administration and monitoring surface of the Qore platform. It's where you watch how your apps and agents are used, evaluate the quality of their output, enforce guardrails and kill switches, inspect logs, manage costs, and control who has access.
Control Center as an operator sees it, with the modules listed below in the left navigation.
## At a glance
* **What it's for:** monitoring, quality control, governance, and administration across your whole Qore account — not building apps or agents (that happens in Console), but overseeing them.
* **Who uses it:** account admins and operators day-to-day; developers and integrators for API keys, logs, and permissions; anyone who needs to see usage, cost, or audit history.
* **How it's organized:** seven modules in the navigation: Operator, Observe, Cost Control, Evals, Govern, AI Gateway, and Admin.
* **Scope:** everything in Control Center is account-wide. There is no project selector for the space itself, though most screens can be narrowed to one project.
## Control Center modules
The Control Center navigation lists seven modules:
* [**Operator**](/ai-workbench-qore/control-center/governance-operator.md) — the Governance Operator: ask about the account, and approve what it proposes.
* [**Observe**](/ai-workbench-qore/control-center/observe.md) — who's using your apps and agents, with what outcomes, and every run, change, model call, request, and database operation. Includes exports and reports.
* [**Cost Control**](/ai-workbench-qore/control-center/cost-control.md) — track credit usage and set hard limits and alerts.
* [**Evals**](/ai-workbench-qore/control-center/evals.md) — define evaluators that score agent output, watch them run on live traffic, and review flagged executions by hand.
* [**Govern**](/ai-workbench-qore/control-center/govern.md) — stop agents in an emergency, review the connectors agents may reach, and load a governed graph.
* [**AI Gateway**](/ai-workbench-qore/control-center/ai-gateway.md) — set the model families and models used across Console building and usage.
* [**Admin**](/ai-workbench-qore/control-center/admin.md) — manage users and their roles, group them into teams scoped to product spaces, and issue API keys.
## How Control Center fits together
The modules are separate views over the same account activity, so one agent run shows up in several places, each from a different angle: as a thread in **Agent Analytics**, a scored execution in **Online Eval**, a task in **Human Review** when its confidence is low, the model calls it made in **LLM Logs**, and the records it changed in **Audit Trails** and **DB Query Logs**.
Knowing which module answers which question is most of what it takes to work quickly here:
* *Is anyone using this?* → Observe.
* *Is the output any good?* → Evals.
* *Can I stop it, and what can it reach?* → Govern.
* *Who changed what?* → Observe › Audit Trails.
* *What exactly did it call and write?* → Observe › LLM Logs, Request Logs, and DB Query Logs.
* *What is it costing?* → Cost Control.
* *Who can do what?* → Admin.
***
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Maintained by Abhishek Paul AI-assisted, human-approved
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