Architecting Agentic AI for Finance

The financial industry generates vast amounts of data that require advanced tools for real-time processing, interpretation, and decision-making. Traditional analytics platforms demand extensive manual effort and are prone to errors and approximations. Opensee addresses these challenges by integrating an AI-powered platform for deep and instant access to these vast amounts of data.

In our white paper, "Beyond the LLM: Architecting Agentic AI for Finance," we show how Agensee leverages both Gen AI and traditional AI to let users interact naturally with data and analytics and obtain actionable insights, with full transparency. Agensee is designed to cope with complex workflows, domain-specific language, large data volumes, and context-dependent questions, while returning answers in the most useful form, from simple figures to rich analyses.

The research highlights how giving agents more autonomy and specialization significantly improves the quality and reliability of results, and shows that architecture choices are as important as the underlying LLMs. It also outlines concrete applications across risk analytics, data quality and certification, scenario analysis, and financial and management reporting.

Download the whitepaper “Beyond the LLM: Architecting Agentic AI for Finance” to explore the full approach, findings, and use cases:
https://www.opensee.io/whitepaper/architecting-agentic-ai-for-finance