Automation for small and mid-sized manufacturers
In a small manufacturer the margin leaks in the technical office and in purchasing: requests for quotation that take days to answer, supplier orders that depend on someone remembering and a production report built by hand every Monday. We chain those processes to the ERP data, with AI where a drawing, a request or a delivery note has to be read.
Signs you need this
- A request for quotation can sit in an inbox for a week before anyone looks at it.
- Purchases are triggered when material runs out, not when consumption predicts it.
- The Monday report is built by copying data from three different spreadsheets.
What we automate in this sector
The catalogue processes that come up most often here. Each card links to the full spec.
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Quotes and proposals
Quotes, contracts and reports generated from your templates and your price lists in seconds.
- In
- A customer record, an email request or a tender document.
- Out
- A document ready to review, sign or send, with its version saved in the CRM.
Outcome: Quotes the same day instead of the following week, with no pricing mistakes.
See the full spec : Quotes and proposals -
Purchasing and suppliers
Purchase orders prepared, confirmed and tracked until the goods actually arrive.
- In
- A purchase need, a stock minimum or a request from the team.
- Out
- Order confirmed, a committed date, and an automatic alert if it slips.
Outcome: Fewer stockouts caused by delays nobody was watching.
See the full spec : Purchasing and suppliers -
Intelligent document extraction
Any document turned into structured data, without rigid templates.
- In
- Orders, tenders, job sheets, payslips, policies, scans and paper forms.
- Out
- Data ready to enter your system, with a confidence level per field.
Outcome: Manual transcription ends, including on the documents that never arrive the same way twice.
See the full spec : Intelligent document extraction -
Automated reporting
The numbers pulled together and explained, without spending Monday morning in Excel.
- In
- Sales, production, stock or cash data spread across several sources.
- Out
- A report in your inbox every week, written in business language rather than tables.
Outcome: Decisions based on yesterday’s data instead of last month’s.
See the full spec : Automated reporting
A typical scenario
Example scenario, not a client: a maker of custom components selling to other businesses.
- Situation
- Requests for quotation arrive by email with drawings attached. The technical office reviews them when it can, the quote is written by hand and nobody follows up if the customer does not reply.
- What we build
- Every request lands in the CRM with the data extracted from the email and the drawing, the AI drafts a quote with the usual rates and lead times, and the system schedules reminders to the customer and alerts to the salesperson.
- What changes
- Answers go out in hours instead of days, no quote is left without follow-up and management sees the status of all of them every Monday without building the report.
What we get asked in this sector
- Our ERP is old and has no API. Is that a problem?
- It is the usual case. There are other ways to read from and write to an ERP: scheduled exports, databases, exchange files or screen automation. We pick the most stable one for your case and explain it in the diagnosis.
- What if the AI misreads a drawing or a request?
- It never sends anything on its own. It prepares a draft with the data it has read and flags the doubtful values; a person reviews it before it goes out. The aim is to remove the typing, not the judgement.
Does any of this sound familiar?
Tell us the one that takes most of your time. The diagnosis is free and in writing, with a fixed scope and price. If automating it does not pay off, we will tell you.
Scenarios are illustrative examples, not clients. The concrete target for your process is set after the diagnosis, in writing.