InsightPulse β AI News Research Tool
Turn financial news and reports into instant, actionable insights using AI.
Amaan Kazi
Freelancer
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16-01-2026
Submitted
The Problem
Financial professionals, investors, and researchers often struggle to keep up with the huge volume of stock market news, financial articles, and PDF reports. Manually reading long documents is time-consuming, inefficient, and error-prone, making it difficult to quickly extract relevant insights or make informed decisions.
The Solution
This project uses Retrieval-Augmented Generation (RAG) to intelligently analyze financial news and documents. Users can upload news article URLs or PDFs and ask natural language questions. The system retrieves only the most relevant information from the data and generates accurate, context-aware answers using a large language model. This approach significantly reduces reading time, improves information accuracy, and enables faster decision-making.
About This Project
This is AI-powered News Research Tool designed to help users analyze financial news articles and PDF documents using natural language queries. The tool eliminates the need to manually read lengthy reports by allowing users to upload news URLs or financial documents and ask context-aware questions to extract meaningful insights related to stock market trends and financial analysis. The system leverages Retrieval-Augmented Generation (RAG) to retrieve relevant information from large document sets and generate accurate, contextual responses. It supports semantic search through vector embeddings, ensuring precise and efficient information retrieval. πππ² ππ¨π§πππ©ππ¬ ππ¬ππ: β’ Retrieval-Augmented Generation (RAG) β’ Vector embeddings & semantic search β’ Prompt engineering β’ Real-world dependency & API handling This project provided hands-on experience in GenAI system design, handling real-world API dependencies, debugging evolving AI libraries, and building production-ready AI workflows.