AI solutions for businesses and manufacturing pay off where data already exists: in technical documents, in machine and plant data, in fault messages and reports. We first check where AI makes sense in your operation – and say so when a simpler tool will do.
AI solutions for businesses rarely fail because of the model; they usually fail because of the data. Before we propose a method, we look at what your operation already has: manuals, datasheets and inspection records as PDF, signals from PLCs and OPC UA, messages from MES and maintenance software, tables in Excel. If the quality is not sufficient, we say so – and propose what to do first. Often that is a data connection or a dashboard, not yet AI.
AI in manufacturing has three fields where it works reliably today: searching technical documents and extracting values from them, detecting deviations in machine and plant data before they become a fault, and sorting fault messages or shift reports by cause and urgency. For other things – decisions without a reliable history, for instance – we do not recommend AI. Every output names its source and a confidence score, so maintenance engineers and shift leaders can trace what a suggestion is based on.
Not a platform, but four tools that each take over one task in your operation. Each can be used on its own and verified against your own documents and signals.
Three steps, each with a result you can check. After each step you decide whether to continue.
In about 30 minutes we talk about the task you want to solve and the data available for it. At the end you know whether AI is a sensible means here – or whether we recommend something else. Free and without obligation.
We review a subset of your documents or signals, define success criteria and build a pilot. You check the results against values your specialists know. Only when the hit rate meets the agreed criteria does a quotation for the roll-out follow.
The solution is connected to your DMS, PLCs, MES or ERP and extended in two-week cycles. We train users and key users on the live application, monitor model quality and run the system in the EU or at your plant – for as long as you wish.
From the ralwo blog – background, worked examples and checklists, each with its sources.
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An AI solution rarely stands alone. It is often preceded by custom software development, followed by process automation, and a dashboard makes its results visible to shift leaders and management.
Free · No obligation · approx. 30 minutes
In a free initial consultation we clarify your goals, your data situation and the feasibility – with no obligation.