Case study · Artificial intelligence

An AI assistant that knows the manuals and the failure history

Maintenance staff at an international automotive manufacturer no longer search dozens of documents for procedures and manuals. They ask an AI assistant that answers from internal documents and enterprise systems, and always shows where the information comes from.

ClientInternational automotive manufacturer
AreaAssembly hall maintenance
Duration6 months
Team4 specialists
187questions answered during testing
61user ratings of answers
2phases: custom chatbot and MS Copilot deployment
3answer sources: documents, systems, web

Challenge and solution

Challenge

Manuals, procedures and technical documentation were spread across many documents and internal repositories. Finding the right information during a failure took time, and the answers depended on whom the technician asked.

Solution

We designed an AI assistant for internal maintenance staff. It answers questions from internal documents and publicly available technical sources, and cites the source for every answer.

  • RAG technology: the assistant first finds the relevant passages in documents and only then composes an answer
  • A simple web interface with answer quality ratings directly in the chat
  • A strong focus on security and the protection of internal data

How the assistant answers

Every answer is based on specific sources, not on the model’s “memory”.

1

Question

A technician asks in the chat, for example, how to repair a specific device.

2

Retrieval

The assistant finds the relevant parts of internal documents, systems and the web.

3

Answer with sources

They receive a clear answer, a recommended procedure and links to the sources used.

Two project phases

Phase 1: Custom chatbot

A custom-built chatbot with a web interface, connected to the GPT-4o mini model. We taught it to work with internal documents in TXT, DOCX and PDF formats.

  • Testing directly with the client’s users
  • 187 questions answered and 61 answer ratings
  • Feedback was used to fine-tune answer quality

Phase 2: Production deployment in MS Copilot

Building on what we learned in testing, we deployed the assistant to production in Microsoft Copilot.

  • Connection to the internal SharePoint repository and enterprise systems including SAP
  • Data summarisation and report creation
  • Additional information from the open web with source references

What the project delivered

Less time searchingTechnicians find a procedure or manual by asking a question instead of browsing documents.
Fewer errorsAnswers are based on official documentation and backed by sources.
A single source of truthThe same question gets the same answer, regardless of who asks.
Cost savingsMore efficient maintenance and better access to company knowledge.

Technologies used

RAGOpenAI GPT-4o miniMicrosoft CopilotPythonSQLReactSharePointSAP

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