Smart Stock Analyzer: Real-Time Investment Insights Using AI and Bright Data

Devesh Kumar — Sun, 25 May 2025 23:39:26 +0000

This is a submission for the Bright Data AI Web Access Hackathon

What I Built

I developed an AI-powered stock analysis system that aggregates technical, fundamental, and sentiment signals to help investors make more informed decisions. The system analyzes various factors such as recent news, technical analysis, financial fundamentals, social sentiment, and insider activity to generate an investment score. The AI model provides explanations and confidence levels for each analysis, assisting users in making smarter investment choices based on multi-dimensional data.

Key Features:

News Analysis: Sentiment analysis of the latest news related to a stock.
Technical Analysis: Evaluation based on technical indicators and price trends.
Fundamental Analysis: Assessment of the stock’s financial health, including balance sheets and earnings reports.
Social Sentiment: Insights from social media sentiment and discussions.
Insider Activity: Monitoring of insider trading and stock movements by company executives.

Demo

You can explore the project and access the full code repository here. Below are some screenshots showing the solution in action:

How I Used Bright Data's Infrastructure

To gather real-time data from various web sources, I used Bright Data's Managed Proxy Network (MCP) to aggregate and scrape technical, financial, and sentiment data. The Bright Data infrastructure allowed me to gather accurate and up-to-date stock information across multiple platforms and news sources without hitting rate limits or facing IP bans, making the data aggregation process both seamless and reliable.

Key benefits of Bright Data in my project:

Scalability: Easily access a wide variety of data from multiple websites simultaneously.
Reliability: Ensure that data is consistently updated and available without interruption.
Data Enrichment: Retrieve a rich mix of both structured and unstructured data from multiple sources to enhance my AI analysis.

Performance Improvements

The integration of real-time web data through Bright Data significantly improved the performance of my stock analysis application. By leveraging fresh data, the AI model can generate timely investment recommendations based on current market trends, rather than relying on outdated datasets. This ensures that users have the most accurate and up-to-date information when making investment decisions, giving them a competitive edge in fast-moving markets.

In comparison to traditional approaches that use static datasets or delayed reports, the Bright Data-powered system delivers a more dynamic, responsive, and actionable analysis, improving both the speed and accuracy of stock predictions.

ClipSummarizer: Audio & Video Highlights at Your Fingertips

Devesh Kumar — Sun, 24 Nov 2024 19:52:00 +0000

This is a submission for the AssemblyAI Challenge : No More Monkey Business.

What I Built

I built a two-tier web application that allows users to submit an audio clip or a YouTube video link, and it generates summarized headlines or key highlights from the provided content. The application integrates the AssemblyAI API to transcribe and summarize the audio content into concise headlines, enabling users to quickly digest the key points of any video or audio.

Features:

1. Audio Upload: Users can upload audio files, and the backend processes them for transcription and summarization.
2. YouTube Video Link: Users can provide a YouTube video link, and the application fetches the audio from the video to process it.
3. AssemblyAI Integration: The backend sends the audio data to the AssemblyAI API for transcription and summary generation, which returns key headlines or highlights.
4. React Frontend: The user interface is built in React, where users can upload files or paste video links. It displays the generated summaries clearly and efficiently.

Demo

Github
Here are some screenshots of the app in action:

Journey

Building this project was an exciting challenge, especially integrating the AssemblyAI API into the backend. Here's a breakdown of the implementation:

1. Frontend (React):
- I created a simple and intuitive interface where users can either upload an audio file or submit a YouTube link.
- The frontend is built with React and allows users to see the progress of their requests. After submitting the data, it displays the summarized headlines returned by the backend.

2. Backend (Python):
- The backend is built using Python, where I used libraries like yt_dlp to extract audio from YouTube videos.
- Once the audio is extracted, it's sent to AssemblyAI for transcription and summarization.
- The backend then processes the response and sends the summary back to the frontend.

3. AssemblyAI API:
- I leveraged AssemblyAI's transcription API to convert the audio into text and their summarization feature to condense the content into highlights.
- The integration was seamless, and the API provided accurate transcriptions and concise summaries.

4. Challenges and Solutions:
- Audio Extraction from YouTube: Initially, I ran into issues with audio quality from YouTube. I improved this by choosing the highest-quality audio stream available using yt_dlp.
- API Response Time: AssemblyAI's API can take some time for large audio clips. To handle this, I added a progress bar to the frontend to keep users informed about the status of their request.
- Error Handling: I ensured that the frontend handles errors gracefully if the audio is too long or if the YouTube link is invalid.

This project allowed me to explore the full potential of integrating AssemblyAI’s transcription and summarization services into a real-world application, and I’m excited to see how it can help users save time and quickly extract insights from media.

DEV Community: Devesh Kumar

Smart Stock Analyzer: Real-Time Investment Insights Using AI and Bright Data

What I Built

Key Features:

Demo

How I Used Bright Data's Infrastructure

Performance Improvements

ClipSummarizer: Audio & Video Highlights at Your Fingertips

What I Built

Features:

Demo

Journey