Pattern C: Agent as Orchestrator

The agent coordinates multiple workflows, making decisions about what to trigger, in what order, and how to synthesize results across them. The agent is the decision-maker; each workflow is a capability it can invoke.

flowchart TD Agent["Orchestrator Agent"] --> KYC["KYC Verification<br/>Workflow"] Agent --> Sanctions["Sanctions Screening<br/>Workflow"] Agent --> EDD["Enhanced Due Diligence<br/>Workflow"] Agent --> Account["Account Provisioning<br/>Workflow"] KYC -->|result| Agent Sanctions -->|result| Agent EDD -->|result| Agent Agent -->|"conflicts detected"| Human["Human Review"] Human -->|decision| Agent Agent --> Account style Agent fill:#f3e8ff,stroke:#9333ea

When to Use

  • The process requires dynamic coordination across multiple sub-processes
  • The sequence of steps depends on intermediate results
  • You need to synthesize information from multiple workflows before deciding the next step
  • The agent is the decision-maker, not just a participant

Complete Example: Customer Onboarding

An orchestrator agent that onboards a business customer ā€” running identity verification, sanctions screening, and conditionally triggering enhanced due diligence.

json
{
  "objective": "Onboard business customer: {{input.company_name}}\n\nCustomer details:\n- Company: {{input.company_name}}\n- Country: {{input.country}}\n- Registration: {{input.registration_number}}\n- Contact: {{input.contact_name}} ({{input.contact_email}})\n\nProcess:\n1. Run identity verification\n2. Run sanctions screening\n3. If any concerns, run enhanced due diligence\n4. If still uncertain, request human review\n5. If approved, provision the account\n6. Send welcome email",
  "tools": [
    { "type": "workflow", "name": "identity_verification" },
    { "type": "workflow", "name": "sanctions_screening" },
    { "type": "workflow", "name": "enhanced_due_diligence" },
    { "type": "workflow", "name": "account_provisioning" },
    { "type": "action", "name": "gmail_send" }
  ],
  "config": {
    "model": "gpt-4",
    "max_iterations": 20,
    "timeout_ms": 600000,
    "on_stuck": { "iterations": 3, "action": "escalate" }
  }
}

Sample Reasoning Trace

text
Iteration 1:
  Thought: "Starting onboarding for Acme GmbH. First step is identity verification."
  Action: __log_progress__
  Input: { "message": "Starting onboarding", "milestone": "begin" }

Iteration 2:
  Thought: "Let me run the identity verification workflow."
  Action: __run_workflow__
  Input: {
    "workflow_name": "identity_verification",
    "input": {
      "company_name": "Acme GmbH",
      "country": "DE",
      "registration_number": "HRB 12345"
    },
    "wait": true, "timeout_ms": 120000
  }
  Observation: {
    "status": "completed",
    "result": { "verified": true, "confidence": 0.92, "source": "trade_register" }
  }

Iteration 3:
  Thought: "Identity verified. Now I need to run sanctions screening."
  Action: __store_memory__
  Input: { "key": "kyc_result", "value": { "verified": true, "confidence": 0.92 } }

Iteration 4:
  Thought: "Running sanctions screening."
  Action: __run_workflow__
  Input: {
    "workflow_name": "sanctions_screening",
    "input": {
      "entity_name": "Acme GmbH",
      "country": "DE",
      "registration_number": "HRB 12345"
    },
    "wait": true
  }
  Observation: {
    "status": "completed",
    "result": { "matches_found": 1, "match_type": "partial_name", "risk_level": "medium" }
  }

Iteration 5:
  Thought: "Sanctions screening found a partial name match with medium risk. This
  needs enhanced due diligence before I can proceed."
  Action: __log_progress__
  Input: { "message": "Partial sanctions match ā€” triggering EDD", "milestone": "edd_required" }

Iteration 6:
  Thought: "Running enhanced due diligence workflow."
  Action: __run_workflow__
  Input: {
    "workflow_name": "enhanced_due_diligence",
    "input": {
      "entity_name": "Acme GmbH",
      "country": "DE",
      "sanctions_match": { "match_type": "partial_name", "risk_level": "medium" }
    },
    "wait": true, "timeout_ms": 180000
  }
  Observation: {
    "status": "completed",
    "result": {
      "conclusion": "false_positive",
      "confidence": 0.78,
      "reasoning": "Name similarity to sanctioned entity 'Acme Holdings Ltd' but different jurisdiction and industry."
    }
  }

Iteration 7:
  Thought: "EDD concluded false positive but confidence is only 78%. Since this is
  below 85%, I should get human confirmation before provisioning."
  Action: __pause_for_human__
  Input: {
    "question": "EDD concluded false positive (78% confidence) for Acme GmbH sanctions match. Should I proceed with account provisioning?",
    "options": ["Approve ā€” proceed with onboarding", "Reject ā€” deny application", "Request additional documentation"],
    "context_summary": "KYC verified (92%), sanctions partial match on name, EDD says false positive (78%)",
    "urgency": "medium"
  }

  ā€” Agent pauses. Human reviews and responds: "Approve ā€” proceed with onboarding" ā€”

Iteration 8:
  Thought: "Human approved. Let me provision the account."
  Action: __run_workflow__
  Input: {
    "workflow_name": "account_provisioning",
    "input": {
      "company_name": "Acme GmbH",
      "country": "DE",
      "contact_email": "[email protected]",
      "approved_by": "human_review"
    },
    "wait": true
  }
  Observation: { "status": "completed", "result": { "account_id": "acc_xyz789" } }

Iteration 9:
  Thought: "Account provisioned. Sending welcome email."
  Action: gmail_send
  Input: {
    "__oauth_account__": "[email protected]",
    "to": "[email protected]",
    "subject": "Welcome to Our Platform ā€” Acme GmbH",
    "body": "Dear Hans,\n\nYour account (acc_xyz789) has been provisioned..."
  }
  Observation: { "sent": true, "message_id": "msg_abc" }

Iteration 10:
  Thought: "Onboarding complete. All steps passed."
  Action: __complete__
  Input: {
    "answer": "Onboarding complete for Acme GmbH. KYC verified, sanctions false positive confirmed by human review, account acc_xyz789 provisioned, welcome email sent.",
    "confidence": 0.95,
    "summary": "4 workflows executed, 1 human review, account provisioned"
  }

What Makes This Pattern Powerful

Dynamic sequencing. The agent decided to run EDD because sanctions screening returned a partial match. If screening had returned clean, it would have skipped EDD entirely.

Cross-workflow synthesis. The agent combined results from KYC, sanctions, and EDD to make a holistic decision ā€” and recognized that 78% confidence was too low to proceed without human confirmation.

Conditional escalation. The agent used a confidence threshold to decide when to involve a human. Clear cases flow through automatically; uncertain cases get human review.

Full audit trail. Every workflow triggered, every result received, every human decision, and the agent's reasoning about all of it ā€” captured in one trace.

Key Design Considerations

  • Set max_iterations higher for orchestrator agents (15ā€“20). They make more tool calls because they coordinate multiple workflows
  • Set timeout_ms appropriately. Orchestators wait for sub-workflows, so total time is the sum of all sub-workflow durations plus agent reasoning time
  • Use __store_memory__ to save intermediate results. The agent's context window grows with each iteration, but explicit memory storage makes retrieval reliable
  • Include __pause_for_human__ as a tool. Orchestrators make high-stakes decisions and should have the option to escalate

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