Authors:
Maximilian Orlowski
;
Emilia Knauff
and
Florian Marquardt
Affiliation:
Research Group for Cloud Computing, University of Applied Science Brandenburg, Magdeburger Straße 51, Brandenburg an der Havel, Germany
Keyword(s):
GenAI, LLM, RAG, Embedding, Network-Operator, Business-Process, Assistant, Onboarding Coaching.
Abstract:
This paper presents a coaching assistant for network operator processes based on a Retrieval-Augmented Generation (RAG) system leveraging open-source Large Language Models (LLMs) as well as Embedding Models. The system addresses challenges in employee onboarding and training, particularly in the context of increased customer contact due to more complex and extensive processes. Our approach incorporates domain-specific knowledge bases to generate precise, context-aware recommendations while mitigating LLM hallucination. We introduce our systems architecture to run all components on-premise in an our own datacenter, ensuring data security and process knowledge control. We also describe requirements for underlying knowledge documents and their impact on assistant answer quality. Our system aims to improve onboarding accuracy and speed while reducing senior employee workload. The results of our study show that realizing a coaching assistant for German network operators is reasonable, whe
n addressing performance, correctness, integration and locality. However current results regarding accuracy do not yet meet the requirements for productive use.
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