Case 02 · CNC-RAG · industrial holding
Finding answers in CNC machine documentation
An employee asks a question about machine documentation and gets an answer with a page link, including drawings and diagrams. The system can run on the company's own infrastructure.
An industrial holding has more than a hundred manuals for CNC machines, over 53,000 pages. Much of the information people need is not in the text but in drawings, wiring diagrams, CNC screen captures and tables inserted as images. Ordinary text search doesn't find it.
We built a system from scratch that an engineer can ask a question in Russian. It finds the answer in the manuals, including in images, and backs it up with links to the document, page and figure. If the documentation doesn't contain the answer, it says so.
The system can run on local models on your own infrastructure: everything it needs fits on a single GPU.
Example questions
The project in numbers
- More than a hundred manuals, over 53,000 pages and 53,000 figures.
- 94.5% accuracy on a test set of 311 questions.
- An answer usually takes 30–60 seconds, up to several minutes for complex questions. The search progress is visible on screen.
- The whole stack fits on a single GPU.
What the system does
- Finds answers not only in the text but also in drawings, wiring diagrams, screen captures and tables inserted as images.
- Understands exact identifiers: alarm and parameter numbers, connectors, part numbers.
- Attaches links to the file, page and figure to every answer. A link opens the manual page, so the answer is easy to check.
- Reports when the documentation doesn't contain the answer.
- Questions can be asked in Russian while the documentation is in English or Russian. Search can cover one manual, a machine series or the whole library.
- The web interface shows the answer, the sources and the search progress step by step. Other systems connect via an API.
- Quality is checked automatically after every change: against a set of questions with reference answers, some of which can only be solved from images.
Project interface
Fortune AI
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