TrendPulse
AI-Powered Trend Analysis and Data Visualization Dashboard
Core Problem Statement
"Manually monitoring trends is time-consuming. Users require an automated solution that ingest large data streams and translates them into actionable visual insights."
Architectural Implementation
Monolithic Next.js 16 (App Router) with a custom Node.js entry point to bypass serverless constraints for long-running cron tasks. Integrated with Google Gemini AI and MongoDB Atlas.
Engineering Deep Dive
Detailed review of tradeoffs, database models, scaling strategies, and microservices
Structural Trade-offs & Decisions
Used a custom server.ts to support node-cron, which breaks standard serverless hosting compatibility but ensures robust background task execution.
Context & Constraints
- Trend Monitoring & Analytics.
- Data Visualization & AI Dashboard.
- Automated Background Workflows.
Database Modeling & Storage Strategy
Document-oriented structure using Mongoose, featuring time-series collections for tracking trends alongside AI summaries.