Industry · Manufacturing & engineering
AI agents for manufacturing, from quote to after-sales.
Machine builders, component suppliers and plant engineers run on documents: specifications, drawings, order confirmations, service reports, non-conformance forms. That is where language models and agents pay off first, well before anyone touches the shop floor. We build them to fit your ERP, your PLM, your export-control obligations and your works council.
Where AI pays off in industry
The biggest gains in manufacturing are not on the machine. They are in the offices around it, where skilled people spend their days reading, retyping and searching.
A quote for a customised machine costs an engineer days: reading the customer's specification, finding comparable past projects, checking which options are feasible, pricing with a configurator that never quite fits. Order intake retypes PDF orders into the ERP. Service technicians search manuals and old tickets from memory. Quality documents are written by hand after every deviation. None of this is what these people were hired for.
Agents can read the specification and prepare the technical and commercial parts of the quote for an engineer to check. They can extract an order into the ERP and draft the confirmation. They can answer a technician's question from the manual, the service history and the parts catalogue, with the source shown. They can turn a deviation into a draft non-conformance report in the right format.
We focus on these document- and knowledge-heavy processes because they are measurable, they relieve exactly the people who are hardest to hire, and they can be built without touching the production network. Our agentic workflow and knowledge assistant services are the usual starting points.
- Typical clientsMachine and plant builders, component suppliers, contract manufacturers, engineering offices
- SystemsSAP, Microsoft Dynamics, proALPHA, abas and other ERP; PLM and CAD vaults; ticketing and service tools
- First resultsTypically a production-grade pilot in 6–8 weeks
- Working modeOn site at the plant when useful, in German or English
Use cases in manufacturing and engineering
Each of these is a real workflow with a human checkpoint, not a chatbot on the website.
Quote and tender preparation from technical specs
The agent reads the customer specification and tender documents, extracts requirements, finds comparable past projects and configurations, flags deviations from your standard scope and drafts the technical and commercial sections. The sales engineer reviews, adjusts and releases.
Order intake and confirmation
Incoming orders as PDF, email or portal download are read, matched against the quote and master data, entered into the ERP and confirmed to the customer. Discrepancies in prices, quantities or delivery dates go to a person before anything is booked.
Service knowledge and spare-parts identification for technicians
Technicians in the field ask in plain language and get answers from manuals, wiring diagrams, service bulletins and past cases, with sources and the specific machine's configuration taken into account. From a photo, a description or a machine number to the right part number, its alternatives and availability.
Quality documentation and non-conformance reports
Deviations recorded on the line become structured non-conformance reports, 8D drafts and supplier claims in your templates. The quality engineer reviews the draft; the agent keeps the record consistent across ERP, QMS and the customer's portal.
Supplier communication and expediting
Order confirmations, delivery-date changes and quality queries from suppliers are read, compared with the purchase order and answered or escalated. Buyers see exceptions, not inboxes. Related: AI agents for procurement.
Knowledge capture from retiring experts and document search
Structured interviews, annotated walkthroughs and the expert's own notes become a maintained knowledge base that answers the questions the next generation will ask. Add search across drawings, change notes, specifications and standards by meaning rather than filename.
After-sales service agents
Warranty questions, service scheduling and documentation requests are handled with the customer in the portal or by email. The agent knows the machine, the contract and the history, and hands over to a person as soon as goodwill, safety or money is involved.
Constraints specific to manufacturing
OT/IT separation stays intact
Agents live on the IT side: ERP, PLM, ticketing, document management. We do not connect language models to control systems or the production network. Where machine data is useful, it arrives read-only through the historian or MES exports that already cross the boundary.
Machine and master data quality
Sensor data is noisy, material masters are inconsistent, and the as-built configuration often lives in a technician's head. We check data readiness before promising a use case and plan the data foundations work where it is needed.
ERP and PLM landscape
SAP, Microsoft Dynamics, proALPHA, abas and a PLM or CAD vault with years of history. Agents connect through existing interfaces and respect the ERP as the system of record; nothing is booked without a person or a rule releasing it.
Export control and confidentiality of drawings
Drawings, specifications and customer data can be subject to export-control rules and NDAs. We define which documents may be processed by which model and where (EU hosting, on-premises) and keep the audit trail. Your legal counsel confirms the classification; we build to it.
Works council and shift work
Agents change how office and service staff work and touch performance-related data. We involve the works council early with plain descriptions and design the systems so that they support people rather than monitor them.
Multilingual plants and customers
Manuals in German, service reports in Polish, customer specifications in English. Language models handle this well, but terminology must be controlled: we build glossaries per product line so that a part is called the same thing in every language.
How we start
The path is the same as in other industries, with a plant visit at the beginning.
Plant visit and process walk
We walk the offices and the shop floor with sales, order processing, service and quality, look at the documents they handle and ask where the time goes.
Readiness assessment
ERP, PLM and document systems, data quality, export-control and confidentiality requirements, works council situation. Output: the first three use cases with effort, prerequisites and metrics. See the readiness assessment.
Pilot to production
One workflow, typically quoting, order intake or service knowledge, built inside your systems with the people who use it. Measured against the baseline, with human checkpoints wherever money or safety is involved.
Scale across product lines and plants
Once the first agent runs, the pattern repeats: the next workflow, the next plant, the next language. Your IT and department heads take over operation with our documentation, or we run it as managed AI operations.
Frequently asked questions
Do we need to connect AI to our machines?
No. The use cases with the fastest payback are in quoting, order processing, service and quality documentation, all on the IT side. Machine data helps in some cases such as maintenance knowledge, but it comes through existing exports, read-only, never through a direct connection to controls.
How do you handle export-controlled drawings and customer NDAs?
By classifying documents before any model sees them and choosing the processing location accordingly: EU-hosted models, a German data centre or on-premises for the most sensitive material. Access follows your existing permissions. We describe the setup for your export-control officer and legal team; they decide the classification.
Our ERP is heavily customised. Is that a problem?
Usually not. Agents read from and write to the ERP through the interfaces you already use for EDI, portals or reporting, and a person or a rule releases every booking. Heavy customisation mostly affects the integration effort, which we estimate in the assessment.
How do we keep the knowledge of experts who retire next year?
Start now. Structured interviews, annotated walkthroughs of typical faults and the expert's own notes go into a knowledge base that the expert reviews while still on site. Combined with past service cases, it becomes the assistant the next generation uses.
What does the EU AI Act mean for industrial use?
Most office and service use cases described here are low-risk under the AI Act, but safety-related applications or systems that affect employees may fall into stricter categories. We classify each use case in the assessment and recommend confirming the status with legal counsel, since obligations phase in over time.
Related pages
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Agentic workflow automation
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Enterprise knowledge assistants (RAG)
Assistants that answer from your SharePoint, Confluence, DMS, ERP and ticket history: permission-aware, with citations, evaluated, hosted in the EU.
AI agents for operations & supply chain
Order intake from email and PDF into the ERP, document processing, supplier follow-ups and exception handling, with people deciding on every deviation.
Let's find the first workflow worth automating.
A 30-minute intro call, no slides and no obligation. We listen, ask about your processes, and tell you honestly where AI agents would pay off and where they would not.