MemoryVerse AI – Intelligent Personal Digital Identity Vault

Problem Students and professionals store certificates, projects, resumes, internship letters, and academic documents across folders, cloud drives, and platforms. Finding the right proof for job applications or interviews is slow and stressful. Existing storage tools only keep files — they do not understand achievements, skills, or how documents connect. Solution MemoryVerse AI is an AI-powered digital identity vault (not another Drive). It automatically categorizes documents, extracts skills and metadata, maps relationships between achievements, and supports semantic search in natural language so users can retrieve originals instantly. How it works I built a multi-stage AI pipeline that accepts documents, certificates, resumes, GitHub repositories, and portfolio links. The system extracts text (parsers + OCR where needed), generates embeddings with sentence-transformers, and stores vectors in ChromaDB. An intelligent categorization layer classifies content into Projects, Skills, Certifications, Internships, Achievements, and Academics. Extracted metadata builds a knowledge graph linking certifications → skills → projects → internships → career milestones, plus a journey timeline of growth over years. A semantic retrieval layer lets users ask questions like “Show my AI projects” instead of hunting by filename. The dashboard unifies the vault, timeline, relationship graph, and AI retrieval — with extras such as job-fit scoring, elevator pitch, and interview-ready proof packs. Outcome Successfully delivered an AI digital identity system that organizes achievements without manual folder sorting, enables natural-language retrieval with original file download, and visualizes career growth through an interactive knowledge map. Success metric: “I never have to search through folders again.” Next With more time: stronger multimodal document understanding, multi-user / campus access, richer date parsing, and a scalable cloud deployment with role-based access.