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Generative AI Case Study

Financial B2B Credit Risk Deals Analysis

Business Challenge

 

 

  • Manual analysis of unstructured documents for extracting risk-related insights was time-consuming and required a dedicated team.
  • Hundreds of deal memos were reviewed manually, leading to inefficiencies.
  • Lack of historical records and control over documentation and analyzed insights.

Solution

AI Case Study
  • Infrastructure: Fully hosted on-prem, with the exception of Claude Sonnet 3.5.
    • MinIO for Object Storage (AWS S3 compatible).
    • Embedding Model served via LangServe in Kubernetes.
    • Qdrant Vector Store deployed in Kubernetes.
    • Entire application hosted within Kubernetes.
  • Functionality:
    • Insights processed into a database with a custom UI.
    • LLM self-evaluation and correction, enhanced with human feedback.Functionality:

Key Outcomes

 

 

  • Efficiency: Reduced document review time by up to 90%.
  • Control: Business SMEs manage the solution, providing full oversight of AI-generated results.
  • Scalability: The solution is reusable, enabling quick onboarding of additional departments.

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