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MemoryVerse AI

An AI-powered spatial archive that transforms scattered files into a structured, searchable timeline of your digital identity.

Ashwin JauharyMemoryVerse AI

100%

Automated Relationship Mapping

98%

Data Extraction Success Rate

<2s

Semantic Search Retrieval Time

Overview

๐Ÿ”— Source Code (GitHub): https://github.com/Ashwinjauhary/MemoryVerse-AI Students build incredible digital footprints over the years, but their certificates, resumes, and projects end up scattered across drives and emails. MemoryVerse AI solves this by acting as a spatial, AI-powered digital identity archive. You simply drag and drop your scattered files, and our AI pipeline automatically reads, categorizes, and structurally connects your entire life journey into a beautifully organized, searchable timeline. Key Features: โ€ข Zero-Touch Ingestion Engine: Upload any PDF or Image. Uses Tesseract OCR to extract text and Groq (Llama 3) to automatically generate summaries, exact dates, and categories without manual data entry. โ€ข Semantic Relationship Engine: Powered by sentence-transformers and Supabase pgvector, the AI analyzes semantic meaning and automatically links related milestones together (e.g., connecting a React course to a Frontend Developer role). โ€ข Chronological Timeline: A beautifully crafted, glassmorphic UI that weaves unstructured data into a continuous, color-coded timeline of your growth. โ€ข Smart Semantic Search: Search for concepts (e.g., "web development experience") and the AI will retrieve relevant projects and certificates based on vector similarity, even without exact keyword matches. Tech Stack: โ€ข Frontend: Next.js (React), Tailwind CSS, deployed on Vercel. โ€ข Backend: FastAPI (Python), Tesseract OCR, PyTorch, deployed on Render. โ€ข AI/ML: Groq (Llama-3.3-70b-versatile) for NLP, HuggingFace (all-MiniLM-L6-v2) for embeddings. โ€ข Database & Auth: Supabase (PostgreSQL + pgvector) and GitHub OAuth.

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