Zefektivnění a automatizace procesu vyhledávání potenciálních kauz v oblasti financování soudních sporů s využitím AI: praktická aplikace

This bachelor's thesis focuses on streamlining the identification process of potential cases in the field of third-party litigation funding (TPLF) using artificial intelligence. The aim of the thesis is to design and implement a fully automated market screening system at LitFin Capital. Methodologically, the work is designed as a case study featuring a comparative analysis of the original manual process versus the new automated one. The proposed solution combines an automated architecture with large language models (LLMs) to extract structured information from selected sources and predict case attractiveness. The results demonstrate that the system achieves a 94.5% success rate in identifying relevant cases and reduces the operational cost per identified lead by approximately 45 %. The thesis confirms that intelligent automation with human-in-the-loop integration proactively detects market opportunities and significantly increases information availability within the organization.