FinTechForge is an open-source modular platform designed to provide smart, AI-powered financial tools and insights. From sentiment analysis of financial news to secure authentication and dashboards, this project empowers developers, analysts, and students to build and extend finance-focused applications.

This stock screener analyzes correlations between a company’s financial performance and its website, search, and foot traffic. It takes into account several alternative data sources to predict a company's future earnings by performing linear regressions on data from previous quarters. In addition, it performs sentiment analysis of news headlines, tracks insider buys, analyst price target changes, tweets, and reddit discussion. Stock analysis in displayed in one comprehensive dashboard.

A dashboard of news and sentiment for your financial trade

A modern, interactive web dashboard for financial news analysis, powered by state-of-the-art AI, NLP, and real-time data visualization.

Frontend for a financial news sentiment app and stock chart dashboard

Financial data visualization dashboard with news sentiment analysis and time series charts, using the Alphavantage APIs

Real-time financial intelligence dashboard — NLP sentiment analysis, Truth Social correlation, 12-type news classification, and ML data collection pipeline. Python · Flask · React 18

A financial dashboard built using Streamlit, fine-tuned Transformers models and Prophet. Includes auto summarisation, sentiment analysis, and trend forecasting of stock and crypto news.

Interactive Python & Streamlit dashboard for real-time portfolio optimization, risk-return analysis (CAPM), financial metrics, and market sentiment using Yahoo Finance and news data. Visualize performance, track risk, and make informed investment decisions.

A Final Year Project using NLP and time-series analysis to collect data from Reddit, Twitter/X, and financial news. Applies transformer models (e.g. FinBERT) to analyse sentiment and visualise correlations with asset price movements in an interactive dashboard.

A full-stack AI-powered financial analytics pipeline that ingests, processes, and analyzes real-time stock market data using Kafka, PySpark, DuckDB, and machine learning models. The system provides real-time stock price forecasting and sentiment analysis of financial news, accessible via an API and visualized through a Streamlit dashboard.

This Streamlit-powered dashboard combines real-time stock market data with intelligent sentiment analysis from recent news headlines. It’s like a mini Bloomberg Terminal built with Python

AI-powered financial research dashboard that provides real-time news analysis, sentiment scoring, and a conversational AI assistant to help you make smarter investment decisions. (HackwithNewYork 2025)

Build a multi-cloud data intelligence platform that ingests stock market data + social sentiment + financial news, processes it at scale, applies AI models to generate price forecasts, and provides near-real-time dashboards & alerts.

Prototype for an Financial Insight Partners Dashboard to make data informed decisions on software and technology stocks in the public market with a focus on: Financial data extraction and summarization o Investment thesis generation o News and sentiment analysis o Benchmarking and competitive landscape mapping

An intelligent, real-time stock advisory dashboard powered by LLMs and financial data analysis. It combines stock price trends, news sentiment analysis, and smart decision logic to generate actionable investment recommendations (Buy / Hold / Sell) for selected companies.

This project analyzes financial news articles to extract insights and visualize their potential impact on the stock market. It uses Natural Language Processing (NLP) techniques to perform sentiment analysis, named entity recognition, and generate word clouds from news headlines. An interactive dashboard is also provided to visualize the results.

MarketPulse RT is a real-time AI-powered dashboard for Indian & US markets. It combines live stock prices, financial news, sentiment analysis, and RAG-based LLM Q&A into one Streamlit app. Track tickers, analyze events, and query market insights interactively.

Quantara is an AI-powered FinTech platform that combines historical stock data and financial news sentiment to forecast market movements with XGBoost, provides real-time conversational portfolio analysis via LangChain and FastAPI, and delivers an interactive React dashboard for transparent, scalable insights.

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AI-powered financial news sentiment analysis pipeline using FinBERT, multi-source news ingestion, and a Streamlit dashboard to analyze sentiment-driven stock signals.

A real-time financial news sentiment dashboard that fetches headlines, analyzes sentiment with FinBERT, and visualizes trends alongside stock prices. Built with Next.js, Tailwind, and Vercel.

Real-time, interactive financial sentiment dashboard built with Streamlit. It securely fetches current headlines via NewsAPI, uses the specialized FinBERT model to conduct sophisticated sentiment analysis, and visualizes the 5-day rolling average sentiment trend and overall distribution for any stock ticker.

An AI-powered Full Stack web application that automatically fetches financial news, summarizes lengthy articles, and analyzes market sentiment. This project demonstrates the integration of Data Engineering pipelines, Natural Language Processing (NLP), and modern Web Development to create an insightful dashboard for investors.

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Financial Sentiment in Focus: A Dashboard for Corporate News Analysis

FinBERT sentiment analysis on HK financial news with Streamlit dashboard

Real-time financial news sentiment dashboard — Module 01 of Finance × AI

The News Sentiment Dashboard provides financial market insights through these two main functions: Q&A querying based on financial news data, Sentiment analysis of news articles.

Sentiment classification of financial news using FinBERT and multiple NLP models with interactive dashboard