International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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InquestIQ - AI Savings Recommender & Investment Advisor

Author(s) Dr. Preetha S, Dr. Mahalakshmi B S, Mr. Mohammed Ayan Mulla, Mr. Mujagond Shashank, Mr. Nithin N S
Country India
Abstract In recent years, integration of artificial intelligence and financial analytics has significantly transformed investment decision-making processes. Proposed work presents InvestIQ, an intelligent web-based stock analysis and advisory platform that leverages machine learning and large language models to assess stock performance and provide user-centric financial insights. The system employs historical market data and technical indicators extracted from livestock feeds to predict stock risk levels using a trained predictive model. The architecture integrates Flask as the backend framework, SQLite for data management, and Google Gemini Application Programming Interface (API) for generating context-aware investment suggestions through natural language interaction. The application offers an interactive dashboard for stock evaluation, trend visualization, and Artificial Intelligence (AI)-driven chat support, enabling investors to make informed decisions with enhanced accuracy and transparency. Experimental results demonstrate that the proposed system achieves effective classification of stock risks while maintaining scalability and usability for real-time financial forecasting.
Keywords Stock Market Prediction, Machine Learning, Flask Framework, Financial Analytics, Gemini AI, Predictive Modelling, Web Application, Artificial Intelligence, Investment Risk Analysis.
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-29
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.61859
Short DOI https://doi.org/hbdsrq
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