Best practices: Building Enterprise Applications that leverage GenAI
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Damir
daenet
Lead Sofwtare Architect
In a recent large-scale .NET project, we tackled the challenge of analyzing nearly 1 billion records stored in a database. The data encompassed various details about individuals, requiring the system to generate comprehensive reports, including connections and economic scoring. Traditional manual analysis by specialists could take days for a single individual. To overcome this, we implemented an AI-driven solution powered by a Large Language Model (LLM).
After training the model and integrating it into the system, the AI now delivers reports that are up to 80% more accurate than manual reviews. This session will explore our journey in designing, training, and deploying AI in a .NET environment, addressing challenges, optimizing performance, and achieving transformative results.
World Congress 2025
Damir
daenet
Lead Sofwtare Architect
Yan Cui
Lumigo
Developer Advocate
Oliver Will
Obungi
Head of AI
Tomislav TipuriΔ
Nephos
CTO