International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 10 | Oct 2025
p-ISSN: 2395-0072
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EQUITY – FUND DASHBOARD POWERED BY GROQ AI USHA RANI.K¹, GOKUL NATH T.A², ASOKAINDRAJITH A.K³, HARISH.K4 1Assistant Professor, Dept. of Computer Science Engineering, K.L.N college of Engineering, Tamil Nadu, India 2Student, Dept. of Computer Science Engineering, K.L.N college of Engineering,Tamil Nadu,India
3Student, Dept. of Computer Science Engineering, K.L.N college of Engineering, Tamil Nadu, India 4Student, Dept. of Computer Science Engineering, K.L.N college of Engineering, Tamil Nadu, India
---------------------------------------------------------------------***--------------------------------------------------------------------integrates multiple data sources into a unified analytical framework. The system provides real-time financial insights based application that leverages artificial intelligence and through natural language processing while creating an real-time financial data to provide comprehensive stock accessible, user-friendly interface for retail investors. The market analysis. The system integrates multiple technologies application visualizes complex financial data through including Groq's LLaMA AI model, Google Custom Search API, interactive charts and metrics, making sophisticated analysis and Yahoo Finance API to deliver intelligent investment tools available to everyday investors. The scope of the insights. The application employs a streamlined architecture application encompasses real-time stock data retrieval from that retrieves real-time stock data, conducts web-based Yahoo Finance, AI-powered analysis using Groq's LLaMA 3.3 research, and generates AI-powered analytical reports. Built 70B model, web-based research integration through Google using Streamlit framework, the platform offers an interactive Custom Search, interactive data visualization using Plotly, user interface with dynamic data visualization capabilities. and a responsive web interface built with Streamlit The system addresses the growing need for accessible, AIframework. This comprehensive approach democratizes driven financial research tools that can democratize access to institutional-grade financial analysis tools and investment analysis for retail investors. Key features include empowers retail investors to make more informed real-time stock price tracking, historical trend analysis, AIinvestment decisions. generated market insights, and comprehensive financial metrics visualization. The application demonstrates the 1.2.OBJECTIVE AND SCOPE OF THE PROJECT potential of combining large language models with financial data APIs to create intelligent decision-support systems for The main objective of the Finance Intelligence Pro investment research. project is to create a fully functional AI-driven stock analysis platform capable of predicting stock price trends using realKey Words: Artificial Intelligence, Stock Market time and historical data. The key objectives are: To design Analysis, Financial Technology, LLaMA Model, Real-time and develop an AI-based financial analytics platform for Data Processing, Investment Intelligence, Web APIs, stock market prediction. To collect and integrate real-time Data Visualization, Natural Language Processing, stock market data using APIs such as Yahoo Finance. To Streamlit. preprocess and analyze financial datasets using machine learning algorithms.To visualize market trends, patterns, and 1.INTRODUCTION predictions through an interactive dashboard.To support investors and analysts in making data-driven investment The financial markets generate vast amounts of data decisions by minimizing emotional bias.To ensure daily, making it increasingly challenging for individual modularity and scalability, allowing future integration of investors to make informed investment decisions. more data sources or advanced forecasting features. Traditional financial analysis requires extensive domain knowledge, access to multiple data sources, and significant The scope of this project covers the application of AI time investment. The proliferation of artificial intelligence and ML for short-term and medium-term stock market and machine learning technologies has created new prediction. It focuses on data collection, model training, opportunities to automate and enhance financial analysis analysis, and visualization, rather than direct trading or processes. Retail investors face several challenges in automated execution.The platform will primarily cater conducting comprehensive stock market research, including to:Individual investors and traders, who seek quick insights limited access to professional-grade financial analysis tools, and AI-based recommendations.Financial researchers and information overload from multiple disparate sources, time analysts, who want to experiment with predictive models constraints in processing and analyzing market data, and evaluate their performance.Educational users, who wish difficulty in interpreting complex financial metrics, and lack to understand AI applications in finance.The system of personalized investment insights. Finance Intelligence Pro currently predicts trends and sentiment for selected stocks, addresses these challenges by developing an AI-powered but it is scalable to include portfolio optimization, risk platform that automates comprehensive stock analysis and
Abstract - Finance Intelligence Pro is an innovative web-
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