At LNS, digital transformation is not about technology for its own sake. It is about solving real problems for our customers and for our teams. The XR5.0 project has been a strong driver in this journey, helping us move from ideas into concrete service improvements. A question that many industrial companies are facing nowadays is how to use AI in a way that really supports people the customers, the technicians, and the service teams. The work around Helen S. is a good example of how we approach this.
From chatbot to real service tool
Helen S. started as a simple chatbot to answer frequently asked questions. Today, it has evolved into a much more practical tool: Customers can access it on our website, in the customer portal, on the latest HMIs, and even when calling LNS by phone in some countries. When called, it provides structured, relevant answers based on real technical documentation and service data. What matters for us is not the technology behind it, but the impact:
- Faster answers for customers
- Less repetitive work for hotliners
- Better use and preservation of internal knowledge
We also made sure that Helen does not replace people. When needed, it quickly escalates to a technician, creates a ticket, and connects the customer with the right expert This is what we mean by human-centric AI: it supports the interaction, it does not try to take it over.
Adding voice: a natural next step
A recent step was the addition of voice capabilities to Helen S. Instead of only typing, customers can now interact via phone or voice channels. This brings two advantages:
- It fits better with how many customers already work (calling instead of typing)
- It makes the service accessible even outside of normal working hours
At the same time, the rollout showed clearly that technology alone is not enough. We had to adjust how the bot communicates, how tickets are created, and how customers are informed. Early feedback from teams and customers helped to improve these points quickly, for example making sure customers understand that a ticket has been created and that someone will follow up. This iterative approach is key for us: test, learn, adapt.
Strong collaboration within XR5.0
The progress we made did not happen in isolation. The XR5.0 project brought together many partners, each with different perspectives and expertise. Through regular exchanges from working group meetings to workshops we challenged our ideas and improved our solutions. For example, discussions around XR-supported service, remote diagnostics, and user experience directly influenced how we position Helen S. and our digital service offering. What was particularly valuable:
- Open and constructive discussions with partners
- Sharing real use cases, not just concepts
- Learning from different industries and approaches
This helped us stay pragmatic. Instead of building “nice demos”, we focused on solutions that can be used in daily operations.
Moving the service offering forward
The combination of AI (Helen S.), XR concepts, and the learnings from XR5.0 is now clearly shaping our service model. We are moving towards:
- More remote support and fewer on-site interventions
- Better use of technician time
- Faster response times for customers
This also supports our sustainability goals, as less travel is required and resources are used in a more efficient way.
What comes next
We are still at the beginning of this journey.
The next steps will focus on:
- Further improving the quality and accuracy of AI answers
- Making the voice interaction more natural and clearer for customers
- Connecting Helen S. even more closely with our internal systems and processes
- Exploring how XR can be used together with AI in real service situations
The XR5.0 project will continue to support this work, not just through technology, but through collaboration.
Conclusion
XR5.0 is not just a research project for LNS. It is a practical framework that helps us test, learn, and improve how we deliver service. With Helen S., and now also with the voice extension, we have taken concrete steps towards a more modern and customer-focused service model. The key takeaway is simple: AI works best when it supports people.