Helix — AI Digital Identity System
Overview
HELIX is an AI-powered Digital Identity & Knowledge Graph that transforms scattered academic and professional documents into a structured, searchable, and evidence-backed representation of a student's growth. Instead of simply storing files, HELIX understands uploaded content, automatically categorizes information, discovers relationships across experiences, visualizes growth through a digital journey timeline, and enables natural-language retrieval using Retrieval-Augmented Generation (RAG).
PROJECT RESOURCES
Live Application https://h-e-l-i-x-peach.vercel.app
Demo Video https://youtu.be/5ONEuIMZQLc
Presentation https://drive.google.com/file/d/1lZKq4jQd_KRlNsp7IG7yQ0Dzpa9iz_Vp/view?usp=sharing
GitHub Repository https://github.com/neshandrag/h.e.l.i.x
EXPLORING - HELIX
• Register a new account (no test credentials are required).
• Upload certificates, resumes, project reports, internship letters, or images.
• Optionally connect a GitHub repository to import project information automatically.
• Explore the Documents Dashboard to review uploaded files, AI classifications, and evidence scores.
• Visualize relationships between skills, projects, certifications, internships, and achievements using the Knowledge Graph.
• View your milestones in the Digital Journey Timeline, automatically generated from uploaded evidence.
• Use Ask AI to query your digital identity in natural language and receive evidence-backed responses powered by Retrieval-Augmented Generation (RAG).
• Visit the Public Profile to view a shareable, read-only representation of your digital identity.
KEY DESIGN DECISIONS
• AI is responsible for information extraction and categorization, while verifiability, relationship depth, and path coherence are computed using deterministic algorithms for transparency and consistency.
• Classification, Verifiability, Relationship Depth, and Coherence are evaluated independently instead of being combined into a single opaque score.
• Semantic search powered by vector embeddings and Retrieval-Augmented Generation (RAG) ensures responses are grounded in uploaded evidence rather than generated assumptions.
• Original documents remain preserved in their native format and are always accessible.
• The modular architecture allows document uploads to function independently, while GitHub and Telegram integrations remain optional extensions.
DEPLOYMENT INFORMATION
Frontend: Vercel
Backend: Render
Database: Supabase (PostgreSQL + pgvector)
Note: The backend is deployed on Render's free tier. After periods of inactivity, the first API request may take approximately 30–60 seconds while the service resumes. Subsequent requests respond normally.