Flagship product
Agentic Command Center
A secure control layer for developers building agentic AI orchestration, automation and workflow systems — and a command surface for the enterprise teams accountable for them.
Live surface
The console your operators actually live in.
Active agents
14
of 27 registered
Token spend (today)
$1284.40
budget $5,000
Pending approvals
3
2 high-risk
wire-transfer-approver
AGT-0421 · core-banking.transfer
12.4kescalatedkyc-onboarding-bot
AGT-0418 · idv.verify
84.1kactiveclaims-triage
AGT-0411 · crm.ticket.create
21.7kactiveoutbound-campaign
AGT-0407 · voice.dial
3.2kpauseddata-export-helper
AGT-0398 · warehouse.query
0.6kblocked
- 14:02:11POLICYwire-transfer-approver → human approval required (>$10k)
- 14:02:09TRACEkyc-onboarding-bot ▸ idv.verify ▸ 312ms
- 14:02:07BLOCKdata-export-helper denied: tool warehouse.query not allowed
- 14:02:04COSTtenant=acme department=ops spend +$1.84
- 14:02:01TRACEclaims-triage ▸ crm.ticket.create ▸ 198ms
Core capabilities
Six capabilities — six places agents go wrong without you.
| Capability | Description | Enterprise value |
|---|---|---|
| Agent Policy Control | Define what each AI agent can access, execute, approve, escalate or reject. | Reduces unauthorized or unsafe agent behavior. |
| Tool Usage Governance | Control APIs, plugins, files, databases, business systems and external services. | Prevents uncontrolled tool execution and data exposure. |
| Workflow Tracing | Track multi-step automation, handoffs, retries, failures and agent-to-agent activity. | Improves debugging, auditability and operational visibility. |
| Human Approval Workflows | Require approval before sensitive actions like payments, external messages, exports or production changes. | Keeps high-risk workflows under enterprise control. |
| Audit Trail | Capture prompt summaries, model responses, tool calls, user actions, decisions and system events. | Supports compliance, incident review and accountability. |
| Cost Controls | Track and limit LLM usage by user, agent, app, workflow, model or department. | Controls token spend and prevents runaway automation cost. |
Integration flow
Five steps to ship an accountable agent.
STEP 01
Register Agent
Add each AI agent, workflow, automation task and tool to the MetzuAI registry.
STEP 02
Attach Policy
Assign permissions, model limits, allowed tools, escalation rules and approval gates.
STEP 03
Trace Execution
Capture prompts, responses, tool calls, token usage, latency and workflow status.
STEP 04
Control Actions
Allow, deny, pause, resume or stop actions based on role, policy and risk level.
STEP 05
Report & Optimize
Analyze performance, cost, compliance, exceptions and optimization opportunities.
SDK
Wire it into your agents in minutes.
import { Metzu } from "@metzuai/sdk";
const metzu = new Metzu({ apiKey: process.env.METZU_KEY });
// 1. Register
await metzu.agents.register({
id: "wire-transfer-approver",
owner: "ops@bank.com",
env: "production",
});
// 2. Policy
await metzu.policy.attach("wire-transfer-approver", {
tools: { allow: ["core-banking.transfer", "crm.lookup"] },
models: { allow: ["gpt-4o", "claude-3-5-sonnet"], maxTokens: 8000 },
approvals: [{ when: "amount > 10000", role: "ops.lead" }],
});
// 3. Trace every step
const run = metzu.trace("wire-transfer-approver");
await run.tool("core-banking.transfer", { amount, to });
Observability · Command · Cost
Three operating modes, one control plane.
Trace · Debug · Measure · Audit
Agent steps, workflow paths, tool calls and system events with latency, success rate, token usage and full audit trails.
Registry · Status · Kill switch
Pause, resume, escalate or stop any agent, workflow, tool or automation instantly. Action-level controls per role.
Usage · Budgets · Models · Alerts
Track tokens by user, agent, app, workflow, model or department. Set budgets and trigger alerts on anomalies.
RBAC
One control surface, six different jobs.
| Role | Access | Purpose |
|---|---|---|
| Admin | Full access to agents, policies, users, workflows, logs, cost controls and environments. | Owns platform configuration and governance. |
| Developer | Integrate the SDK, create agents, inspect logs, debug workflows and view tool traces. | Builds and maintains agentic applications. |
| Compliance Officer | Audit logs, policy history, approval records and exception reports. | Reviews risk, control and accountability evidence. |
| Finance Team | Token usage, model spend, budgets, alerts and cost optimization reports. | Controls LLM consumption and budget discipline. |
| Operator | Pause, resume, stop, escalate or approve workflows based on permissions. | Runs day-to-day command and control operations. |
| Business User | Approved dashboards, workflow results, summaries and operational reports. | Uses AI outcomes without platform administration. |
Where it runs
Developer use cases & supported environments.
Developer use cases
- · Agentic AI orchestration platforms
- · Enterprise AI assistants
- · Multi-agent systems
- · Workflow automation engines
- · API-driven agents
- · Internal copilots and operators
Supported environments
- · Backend services
- · Agent frameworks
- · Automation platforms
- · Enterprise apps
- · Cloud
- · Private cloud
- · On-premise
Ready to put your agents under control?
Book a 30-minute walkthrough of the MetzuAI SDK — governance, command and cost control, live on your stack.
