Process automation
AI and workflow automation can support repeatable processes, task routing, exception handling and system-to-system updates.
Manufacturing and Supply Chain
Keep orders, documents and operational updates moving
ETT helps manufacturing and supply chain teams reduce rekeying across purchase-order processing, supplier-document validation and exception routing. Extraction accuracy is measured, and anything the system cannot read with confidence goes to a person.
Where we start
The workflows we lead with in this sector
Proposed use cases based on how this work is usually organized. None of these is a published client result.
Purchase-order processing
Reading an incoming order or acknowledgement, extracting the lines, matching them against the agreement, and raising what does not match instead of rekeying the lot.
Supplier-document validation
Checking certificates, specifications and delivery paperwork for the fields the process depends on, and holding a delivery where a required document is missing or expired.
Exception routing
Getting a discrepancy to the buyer, planner or quality owner who can act on it, with the document, the mismatch and the affected order attached.
How it would be measured
Measures to agree before anything is built
A baseline taken after the fact is not a baseline. These are the measures we would ask you to agree, and what each one means, so the before-and-after comparison holds up.
| Measure | What it means |
|---|---|
| Order processing time | Time from document arrival to a confirmed system record, measured across a full week including the backlog. |
| Extraction accuracy | Field-level accuracy against a human-checked sample, reported per document type rather than as a single blended figure. |
| Exception backlog | Open exceptions and their age at the end of each day. |
| Rekeying effort | Person-hours spent typing information that already exists in a document. |
Who this is for
Supply Chain Director or Head of Procurement Operations, with the ERP owner and the quality or compliance lead.
What has to be true first
- A representative document sample across every format you actually receive, including the poor scans
- ERP write access, or an agreed staging route
- A named owner for the exception queue
The challenge
What teams in this sector face
Manufacturing and supply chain teams often work across complex, fast-moving operational environments.
Processes may depend on data from suppliers, production systems, inventory platforms, spreadsheets, documents, scheduling tools and internal teams. When those systems do not connect cleanly, teams lose time chasing information, updating records manually or reacting late to problems.
The challenge is not always a lack of data. It is often a lack of connected, usable information at the point where decisions need to be made.
ETT helps organizations identify where AI and automation can reduce friction, connect workflows and create clearer visibility across operational processes.
Where AI can support
Practical use cases
Document processing
AI can help extract, classify and route information from purchase orders, delivery notes, invoices, forms and supplier documents.
Scheduling support
Automation can support scheduling workflows by surfacing relevant information, flagging conflicts and helping teams respond to changing conditions.
Forecasting and planning insight
Data and analytics can help teams identify demand patterns, bottlenecks, capacity issues and areas where automation may improve visibility.
Operational reporting
Dashboards can help teams see activity, delays, workflow performance and process gaps across connected systems.
Example workflow
Example workflow: from document to operational action
One request, end to end. Each stage shows what happens and the ETT solution behind it, with people kept in control wherever judgement is needed.
Illustrative workflow. The actions, integrations and controls are defined for each deployment. This is not a customer result.
- 01Document receivedAgentic AI and Automation
- 02Information extractedAgentic AI and Automation
- 03Data checkedData and Analytics for AI
- 04Workflow triggeredAgentic AI and Automation
- 05Exception reviewedAgentic AI and Automation
- 06Dashboard updatedData and Analytics for AI
Each stage in detail below, with the systems involved and where a person stays in control.
Document received
A purchase order, delivery note or supplier form arrives by email, portal or scan. It enters the workflow the instant it lands, in whatever format it came in.
Typical technologiesEmail / EDIScan & capture
How ETT helpsAgentic AI and AutomationInformation extracted
Document capture and AI extraction read the fields that matter and score each one for confidence. Anything below the agreed threshold is not written to the system of record — it goes to a person with the specific field flagged.
Typical technologiesOCR / IDPOpenAIConfidence scoring
How ETT helpsAgentic AI and AutomationData checked
Extracted data is validated against your systems and rules, flagging mismatches before they cause downstream problems. Bad data is caught at the door.
Typical technologiesERP / MRPDatabricks
How ETT helpsData and Analytics for AIWorkflow triggered
The matching workflow fires: stock updated, order acknowledged and the next team notified across connected platforms. Information moves without a human carrying it.
Typical technologiesUiPathSystem APIs
How ETT helpsAgentic AI and AutomationException reviewed
Anything that does not reconcile is routed to a person with the context attached, instead of stalling silently. Exceptions get attention; the routine runs itself.
Typical technologiesHuman-in-the-loopCase queue
How ETT helpsAgentic AI and AutomationDashboard updated
Operational dashboards update in real time, so teams can see flow, delays and bottlenecks as they happen. Visibility stops depending on a weekly spreadsheet.
Typical technologiesDatabricksOperational dashboards
How ETT helpsData and Analytics for AIWhen it cannot complete
A field is extracted below the agreed confidence threshold, a required certificate is missing or expired, or the ERP rejects the write. Nothing is written to the system of record. The document goes to the exception queue with the specific field and the reason shown.
Where to start
One document type, accuracy measured before scale
Take one document type and one supplier group. We measure extraction accuracy against a human-checked sample first, agree the confidence threshold below which a document goes to a person, and only then connect the write-back to your ERP.
The solutions involved
- Agentic AI and AutomationFor automating workflows, routing tasks, handling exceptions and connecting actions across operational systems.
- Data and Analytics for AIFor turning fragmented operational data into dashboards, insight and AI-ready intelligence.
- AI Strategy and DeliveryFor identifying which use cases should be prioritized and how automation should fit into the wider operating model.
- Data Discovery and Classification for AIFor locating, structuring and preparing data across documents, systems and operational sources.
- AI Infrastructure as a ServiceFor organizations building or running AI workloads that need dedicated compute, MLOps or stronger infrastructure control.
Analect: fewer tokens, less storage, proven on your documents.
ExploreFAQs
Common questions
How can AI automation support manufacturing operations?
It can help with workflow routing, document processing, scheduling support, reporting, exception handling and operational visibility.
What is manufacturing process automation?
Using technology to reduce manual work across repeatable operational tasks, such as routing information, processing documents, updating systems and flagging exceptions.
Can AI help with supply chain visibility?
Yes. AI and analytics can help bring together information from different systems, documents and workflows so teams can see patterns, delays, bottlenecks and areas for improvement.
What types of documents can AI help process?
Purchase orders, invoices, delivery notes, supplier documents, forms, emails and operational records.
Does automation replace manufacturing teams?
No. Automation should support teams by reducing repetitive manual work, improving access to information and helping people act faster when issues need attention.
Ready to reduce friction across your operational workflows?
Request an AI session to explore where AI automation could support process visibility, document handling, scheduling and workflow performance across your manufacturing or supply chain environment.
Around four minutes. Indicative guidance based on your answers.