Case study

Internal chatbot for ticket resolution

Amplify Analytix developed an internal chatbot that helped a manufacturing company mitigate delays and disruptions in their production process

15% FASTER TICKET RESOLUTION

9% LOWER OPERATIONAL COSTS

8% LESS UNPRODUCTIVE HOURS

5% DECREASE IN EMPLOYEE ATTRITION RATE

The Business Challenge

A global manufacturing company wanted a support mechanism that empowers engineers to address line performance issues independently, minimizing the reliance on experts until necessary. Currently, frequent ticket escalations for engineering issues pose a challenge, leading to delays and disruptions in the production process.​

Developing a chatbot (Internal response system) for internal troubleshooting on top of existing line performance analysis can provide support to engineers to get resolution for simpler tickets, ensuring that only complex issues are escalated to the experts. This automated chatbot can enhance overall efficiency, expedite issue resolution, and minimize potential obstacles in the production pipeline.

Internal chatbot for ticket resolution 1

The Solution

We developed a Large Language Model (LLM) powered chatbot that can resolve simpler tickets and previously observed tickets, reducing the workload on experts. A database (vector store) compiles training manuals and historical tickets for each line, serving as a comprehensive dictionary for the LLM to respond effectively to queries from any engineer.​ When an engineer poses a question, the chatbot accesses the underlying LLM for the answer, providing a simple interface for users.​ The highly scalable generative AI model requires training manuals and tickets related to a new line to the vector store to expand the model's vocabulary.

Internal chatbot for ticket resolution 2

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