This is a submission for the Bright Data AI Web Access Hackathon
What I Built
I built a Brand Intelligence Dashboard that gives businesses real-time insights into how their brand is perceived across social media and news platforms. The system analyzes mentions from Twitter, LinkedIn, Reddit, and news sources to provide sentiment analysis, ethical context evaluation, and trending topic identification.
The frontend is a Next.js application that provides an intuitive interface where users can input any brand name, location, and category to get comprehensive analytics. The dashboard displays sentiment breakdowns, platform-specific insights, word clouds of trending themes, and ethical highlights that might impact brand reputation.
Agent Architecture
Demo
Repository:
Backend - https://github.com/kaarthik108/Know-your-Brand
Frontend - https://github.com/kaarthik108/kyb
Live Demo: https://kyb-nine.vercel.app/
The application works in two main phases:
- Analysis Request: Users enter brand details or select from predefined options (Tesla, Apple, Microsoft)
- AI-Agent: Agent starts doing its work to find mentions across platforms using MCP server (Brightdata)
Key features include:
- Multi-platform sentiment analysis with visual breakdowns
- Ethical context identification for CSR-related themes
- Interactive word clouds showing trending topics
- Platform-specific mention tracking with engagement metrics
- Real-time polling interface during data collection
Tools:
- Google ADK (Agent) with Bright Data MCP.
- O4-mini to extract structured response
- Deployed backend on Google Cloud Run
- NExtJS frontend on Vercel
How I Used Bright Data's Infrastructure
The core of this system relies on Bright Data's MCP server to power four specialized AI agents that work in parallel:
Discovery & Access: The agents use Bright Data's infrastructure to discover and access content across Twitter, LinkedIn, Reddit, and news websites. This includes navigating complex authentication systems and dynamic content loading that would be impossible with traditional scraping.
Data Extraction: Each platform agent extracts structured data including post content, timestamps, engagement metrics, and author information. Bright Data's reliable extraction capabilities ensure we get consistent, clean data even from JavaScript-heavy social media platforms.
Real-time Interaction: The agents interact with dynamic web pages, handling infinite scroll feeds, loading more content, and navigating platform-specific UI elements to gather comprehensive mention data.
The MCP server integration allows our backend to coordinate these four agents simultaneously, dramatically reducing the time needed to gather comprehensive brand intelligence from multiple sources.
Performance Improvements
Using Bright Data's real-time web access created significant improvements over traditional approaches:
Speed: Instead of sequential API calls or unreliable scraping, our parallel agent architecture powered by Bright Data completes comprehensive brand analysis in 2-5 minutes across all four platforms.
Reliability: Traditional web scraping often fails due to anti-bot measures, rate limiting, or dynamic content. Bright Data's infrastructure handles these challenges automatically, giving us consistent data collection success rates.
Data Quality: The MCP server ensures we capture complete context around mentions - not just the text, but engagement metrics, temporal data, and surrounding conversation threads that provide richer sentiment analysis.
Scalability: The system can analyze any brand without platform-specific API limitations or access restrictions. This makes it viable for businesses of any size to get enterprise-level brand intelligence.
Real-time Insights: Unlike static datasets or delayed API responses, Bright Data enables truly current brand monitoring, allowing businesses to respond quickly to emerging trends or reputation issues.
The combination of AI agents with Bright Data's web access infrastructure transforms brand monitoring from a manual, time-intensive process into an automated, comprehensive intelligence system.