VERIDYN — AI-Powered Productivity & Behavioral Analytics Platform
AI-powered productivity platform with behavioral analytics, LLM-driven insights, and real-time statistical tracking across 8 REST endpoints
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VERIDYN is an AI-powered productivity and behavioral analytics platform built to help users understand and improve how they work. It combines a React frontend with a Node.js/Express backend, exposing eight REST endpoints that handle everything from activity tracking to insight generation.
At its core, VERIDYN uses LLM integration (Groq's LLaMA 3.1 70B, with Claude as a fallback model) to analyze user behavior patterns and generate personalized, natural-language insights rather than just raw numbers. Alongside this, the platform computes rolling statistical metrics to track productivity trends over time, giving users both the "what" (data) and the "why" (AI-driven interpretation) behind their habits.
The project was built end-to-end as a full-stack system, covering frontend UI/UX, backend API architecture, database design, and third-party LLM API integration with fallback handling for reliability. It's a strong example of combining traditional software engineering with applied AI to solve a real productivity problem.
Ideal for buyers or learners interested in: full-stack development patterns, LLM/RAG-style integration into production apps, REST API design, and building AI features that go beyond simple chatbots into genuine data analysis.
Future Enhancements
Planned features include multi-week and multi-month trend comparison views, team-level analytics for collaborative use cases, push/email notifications for risk alerts, and a public API to allow third-party integrations with VERIDYN's analytics engine.
Known Issues
AI-generated insights may occasionally take a few seconds longer to load during high traffic on the Groq API. Fallback to the Claude API is handled automatically but may produce slight variation in response tone. Historical trend charts currently support up to 7-day windows; longer ranges are not yet supported.
Installation
1. Clone the repository: git clone https://github.com/Kashish995/veridyn.git
2. Navigate into the project folder: cd veridyn
3. Install dependencies: npm install
4. Create a .env file in the root directory and add the following variables: MONGODB_URI, GROQ_API_KEY, CLAUDE_API_KEY, PORT=5000
5. Start the development server: npm run dev
6. Open your browser and visit http://localhost:5000 (or the port specified in your .env)
Usage
1. Sign up or log in to your VERIDYN account from the welcome screen.
2. Add tasks through the Task Manager, setting titles, due dates, and priorities.
3. Visit the Dashboard to view your discipline score, task completion stats, and weekly performance trends.
4. Open the Insights Hub to view AI-generated behavioural analysis, including risk predictions, study/work pattern breakdowns, and a 7-day action plan.
5. Check back regularly, as the discipline score and trend charts update based on your ongoing activity.
System Requirements
Operating System: Windows, macOS, or Linux (any OS that supports Node.js)
Runtime: Node.js v18 or higher, npm v9 or higher
Database: MongoDB Atlas (cloud-hosted, no local installation required)
Memory: A minimum of 4GB RAM recommended for local development
Storage: At least 500MB free disk space for dependencies and build files
Other: An Active internet connection required for Groq API and Claude API calls; valid API keys for Groq and Claude must be configured in the .env file
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