Use case
Use case3 min readBy The Data Workers Team

Agentic controllership, run by agents

Controllers spend the month chasing reconciliations, approvals and evidence across ERP, billing and spreadsheets. Here is how Data Workers runs it instead.

Key takeaways

  • •The problem today. Controllers spend the month chasing reconciliations, approvals and evidence across ERP, billing and spreadsheets.
  • •What changes. Agents run the controllership checklist continuously: reconciliations, anomaly checks and evidence capture, with every adjustment routed to the controller.
  • •What stays with your people. Journal entries and adjustments: controllers sign them.
  • •The result. The controller reviews exceptions instead of chasing the checklist.

The problem today

Controllers spend the month chasing reconciliations, approvals and evidence across ERP, billing and spreadsheets.

What changes with Data Workers

Agents run the controllership checklist continuously: reconciliations, anomaly checks and evidence capture, with every adjustment routed to the controller.

The workflow: Quality Monitoring agent (run_quality_check) → Quality Monitoring agent (get_anomalies) → Data Access & Governance agent (generate_audit_report) → Autonomous Data-Conductor (request_governance_review).
Fig. 1:The workflow: Quality Monitoring agent (run_quality_check) → Quality Monitoring agent (get_anomalies) → Data Access & Governance agent (generate_audit_report) → Autonomous Data-Conductor (request_governance_review).

The workflow, step by step

  1. 1.The Quality Monitoring agent calls run_quality_check and runs reconciliations daily.
  2. 2.The Quality Monitoring agent calls get_anomalies and flags unusual entries.
  3. 3.The Data Access & Governance agent calls generate_audit_report and captures evidence.
  4. 4.The Autonomous Data-Conductor calls request_governance_review and routes adjustments to the controller.

The impact metrics we move

  • •Reconciliation status: from about a week to 15-20 min
  • •Unusual entry flagged: from about a week to under 1 h
  • •Evidence package: from about 2 weeks to 4 h
Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.
Fig. 2:Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.

What goes on autopilot

  • •The checklist runs every day, so close is review, not rework.
  • •Evidence is captured as work happens, so audit asks are fast.

Where your people stay in charge

Journal entries and adjustments always go to a named approver, because controllers sign them. Everything starts at L1, observing only, and autonomy rises only on evidence.

The pilot

  • •Scope. The close checklist for one entity.
  • •First week. Agents run at L1, observing only, and show the fixes they would have made, with receipts.
  • •By week two. The routine work above runs on its own; anything sensitive stays with a named approver.
  • •At day 30. We review the impact metrics against your baseline:
  • •Reconciliation status: from about a week to 15-20 min
  • •Unusual entry flagged: from about a week to under 1 h
  • •Evidence package: from about 2 weeks to 4 h
  • •Cost. Start with a pilot ($7,500 one-time, credited in full against the first year). Scale is from $1,000 a month and Enterprise from $3,000 a month, billed annually, with unlimited seats, no usage meter and no markup on model spend. See pricing.

Related: The finance and accounting page · The full team playbook

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