Use case
Use case3 min readBy The Data Workers Team

Quality management data, run by agents

Inspection, MES and supplier data are reconciled by hand during investigations, so root cause takes weeks. Here is how Data Workers runs it instead.

Key takeaways

  • •The problem today. Inspection, MES and supplier data are reconciled by hand during investigations, so root cause takes weeks.
  • •What changes. Agents keep inspection and process data joined and trace a defect to its lot, line and supplier in one question.
  • •What stays with your people. Holds and recalls: they are regulated decisions.
  • •The result. Root cause takes hours, not weeks.

The problem today

Inspection, MES and supplier data are reconciled by hand during investigations, so root cause takes weeks.

What changes with Data Workers

Agents keep inspection and process data joined and trace a defect to its lot, line and supplier in one question.

The workflow: Connectors agent (get_connector_status) → Pipeline Building agent (generate_pipeline) → Data Context & Catalog agent (trace_cross_platform_lineage) → Quality Monitoring agent (get_anomalies).
Fig. 1:The workflow: Connectors agent (get_connector_status) → Pipeline Building agent (generate_pipeline) → Data Context & Catalog agent (trace_cross_platform_lineage) → Quality Monitoring agent (get_anomalies).

The workflow, step by step

  1. 1.The Connectors agent calls get_connector_status and lands MES and inspection data.
  2. 2.The Pipeline Building agent calls generate_pipeline and joins process and quality data.
  3. 3.The Data Context & Catalog agent calls trace_cross_platform_lineage and traces lots end to end.
  4. 4.The Quality Monitoring agent calls get_anomalies and flags out-of-control signals.

The impact metrics we move

  • •Lot traced end to end: from about a week to 15-20 min
  • •Defect signal flagged: from about 3 days to under 1 h
  • •Quality report: from about a week to 2 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

  • •Process and quality data join continuously, so investigations start with data.
  • •Out-of-control signals are flagged, so defects are caught early.

Where your people stay in charge

Holds and recalls always go to a named approver, because they are regulated decisions. Everything starts at L1, observing only, and autonomy rises only on evidence.

The pilot

  • •Scope. Lot traceability for one product line.
  • •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:
  • •Lot traced end to end: from about a week to 15-20 min
  • •Defect signal flagged: from about 3 days to under 1 h
  • •Quality report: from about a week to 2 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 manufacturing hub · The full team playbook

Related Posts

Use case

Account intelligence data, run by agents

Account data is split across CRM, billing, product usage and enrichment vendors that identify accounts differently. Here is how Data Workers runs it instead.

Use case

Accruals and prepaids data, run by agents

Accrual schedules live in spreadsheets, and missed or stale accruals surface in review. Here is how Data Workers runs it instead.

Use case

Agent governance and audit, run by agents

AI agents act on data with no consistent approval, record or rollback. Here is how Data Workers runs it instead.

Use case

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.