@mastersthesis{Shivaraju2025,
  type      = {Master Thesis},
  author    = {Shivaraju, Anusha},
  title     = {LLM-Driven Multi-Agent System for Market Trend Analysis and Capability Mapping},
  organization    = {Creatum GmbH},
  institution = {Fakult{\"a}t Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019)},
  school    = {Hochschule Offenburg},
  pages     = {47},
  year      = {2025},
  abstract  = {This thesis presents a multi-agent AI system for automated market trend analysis by processing emails, newsletters, and PDFs. The system employs a structured workflow of autonomous agents for content extraction, summarization, subtopic identification, and topic clustering, leveraging OpenAI's GPT-4 within an Autogen-based framework. Key features include multi-tenant adaptability, customer-specific trend analysis, and Azure SQL integration for structured data storage. The system demonstrates good accuracy in trend extraction and classification, addressing challenges like varying LLMs output and multi� schema architecture. This research underscores the potential of AI-powered automation in business intelligence, optimizing decision-making and strategic market analysis.},
  language  = {en}
}