Industry
Manufacturing & process industry
For machinery and plant builders, component manufacturers and process industry whose service inbox, quote desk and complaint process see more cases than the team can read.
01Where the volume is
Which workflows carry the effort
In a mid-sized manufacturer, the technical service inbox, the quote desk and the complaint process each handle thousands of cases a year. Each case means reading, looking things up in the ERP, the CRM and the document archive, and writing something back. That is where agentic workflows earn their keep.
02Starting points
Four workflows we see first
Each one follows the same mechanics: intake, context, proposal, release, write-back.
- 01
Technical service requests: classify, pull machine history and documentation, draft the answer, engineer releases
- 02
Quote requests for parts and configured products: extract the request, check availability and price rules, draft the quote, sales releases
- 03
Complaints and warranty claims: assemble evidence, check against policy, propose a resolution, quality decides
- 04
Supplier documents: order confirmations, certificates and delivery notes checked against the order and posted
03Constraints
What makes it harder here
Machine data and OT stay where they are. Federated IT across plants, works-council agreements and safety-relevant documentation set the frame. Every agent gets read access first and write access only after the shadow phase.
04First quarter
Where we usually start
Usually with the service inbox or the quote desk: high volume, a clear owner, measurable cycle time, and the data already sits in the ERP and the ticket system.
Where to go next
Service
Workflow Assessment
Four weeks: which workflow first, what it is worth, what the build takes.
Use case
Service triage
Incoming service and technical requests classified, enriched with context, answer drafted. A person releases.
Guide
The quoting process in manufacturing: steps, KPIs and AI agents
The quoting process in manufacturing has eight steps from request to follow-up. An AI agent takes over reading, matching and checking, while engineering and sales decide on feasibility, price and release.
Guide
AI agents in manufacturing: ten examples from service, quality and procurement
An AI agent in a manufacturing company takes over steps in the ERP, CRM and QM system, with a named owner and clear release points. The strongest first candidates sit in service, quoting, quality, procurement and order entry, not in machine control.
Next step
Strategy call
30 minutes on your workflow, no obligation.