Technical support with AI

How the system works

1. Query recognition (Natural Language Processing – NLP):
   The AI reads and “understands” the user’s query in natural language (e.g. “Is HV 46 hydraulic oil approved for my machine?”).
   This is done through speech recognition, text analysis and classification.
2. Intent & Entity Recognition:
   The AI recognizes what the issue is (e.g. “specification”, “function”, “fault”) and which details are relevant (e.g. „model”, “error code”).
3. Solution finding (service documents, knowledge database):
   The AI searches literature, knowledge databases, previous support cases or uses trained models to suggest solutions.
   These can be simple things like “disconnect power supply” or more complex steps.
4. Response generation (conversational AI):
   The AI formulates an answer – either directly with the solution or with queries for further clarification.
   At best, this happens in natural, human-like language.
5. Learning & improvement (machine learning):
   The AI learns with every new case: Which solution worked? What was wrong? In this way, the support gets better and better.

And this is how it works in Service Support in particular

1. Training basis:
   We give AI access to the manufacturer’s service documentation, e.g.:
   • Product Funktion
   • Operating instructions
   • Care instructions
   • Troubleshooting
   • FAQ
2. Understanding the product:
   The AI “understands” the product in a similar way to an experienced support employee – but it never forgets, never gets tired and can react immediately.
3. Response generation:
   In the event of a customer inquiry, the AI searches the relevant content from the documentation and uses it to formulate a suitable, often individualized response – so no blunt copy-paste, but intelligent text compilation!

Special System Features:

• Speed: Immediate responses, even for complex queries
• Accuracy: Answers directly from the manufacturer information – technically correct
• Scalability: consistently good quality even with high request volumes
• Relief for the team: 80 – 90% of 1st level support can be automated
• Learning ability: AI can be further trained and improved with real customer questions
• Consistency: Same information for all customers, no contradictions

Possible Extension:

• Installation of a feedback loop: customers can rate whether the answer was helpful. The AI is continuously learning.
• Integration with CRM or ticket systems: This allows the AI to include personal data (e.g. “Your device is still under warranty”).
• Multimodal support: addition of images or videos in responses (“The button you need to press looks like this”).
• Voice instead of just text: The AI can also be used for telephone support or voice bots.