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Managing personal finances involves handling fragmented data, inconsistent categorization, and limited visibility into spending patterns. Traditional finance tracking tools lack intelligence, making it difficult for users to generate meaningful insights, monthly summaries, and actionable recommendations.
Additionally, integrating AI into finance workflows introduces critical challenges such as data accuracy, secure financial processing, real-time analytics, and maintaining consistent performance while handling sensitive financial information.
We designed and developed an AI-powered finance tracking platform that combines a modern Next.js frontend with a robust ASP.NET Core backend. The system enables users to track expenses, generate monthly financial reports, and interact with their financial data through an intelligent AI chatbot.
A Symmetric Kernel was implemented to securely process and structure financial data before being analyzed by AI models, ensuring both accuracy and data protection.
The platform architecture focuses on security, intelligence, and scalability. Financial data flows through encrypted pipelines, is processed by AI models, and is presented to users through intuitive dashboards and chatbot interactions.

The AI Finance Bot significantly improves financial visibility, decision-making, and user engagement by transforming raw financial data into meaningful, actionable insights.

This project demonstrates how AI can be effectively integrated into financial management systems to deliver secure, intelligent, and scalable solutions. By combining modern web technologies, robust backend architecture, and AI-driven analytics, we created a finance platform that empowers users to better understand, manage, and optimize their financial health.