Case Study - Chatbot for Dialogue with Technical Manuals

Challenge

As a partner to a provider of technical information, we took on the challenge of building an AI chatbot for a major player in the machinery manufacturing industry. The goal was to enable fast and efficient information retrieval in extensive technical manuals for service technicians.

Project setup

The scope of the project was limited to a couple of service manuals. This laid the groundwork for a smooth and focused project, where we could concentrate on quality and user-friendliness and prove the solution's usability on a, to begin with, small scale.

Solution

Our solution was based on RAG technology (Retrieval-Augmented Generation), which combines a search engine with an AI chatbot. By breaking down the manual's content into smaller segments and indexing these in a vector database, we were able to create an effective method for finding and presenting relevant information.

Outcome

Our work resulted in a functional chatbot that could handle specific requests from an extensive manual. In the pilot, we saw clear effects for service technicians and support teams:

• Response time for common manual questions dropped from minutes to seconds.
• First-line support could resolve more cases directly without escalation.
• Service technicians reached the right manual sections faster, reducing downtime during troubleshooting.

Learnings

The greatest insight from this project was the importance of high-quality data. The success of an AI-driven solution heavily relies on the quality of the underlying data. Close collaboration with the client is crucial to ensure access to and processing of relevant data.

This project proves our ability to deliver innovative and practical AI solutions. Our customized chatbot technology has the potential to revolutionize information management and support technical processes in large-scale industrial environments.

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Next steps

Want to use RAG/LLMs to make manuals and knowledge searchable in your organization? Contact us and we’ll set up an intro call.