NOETIC VAULT

Where knowledge stays private, but works smarter.

Noetic Vault is a privacy-first, offline AI-powered document intelligence system designed to extract, analyze, and answer queries from large internal documents such as policies, contracts, SOPs, and government PDFs.

It combines Retrieval-Augmented Generation (RAG), multi-agent reasoning, OCR pipelines, and verification layers to deliver accurate, explainable, and secure answers — without relying on the cloud.

FastAPI React Ollama ChromaDB Sentence-Transformers PyMuPDF Tesseract EasyOCR

---

Executive Summary

Noetic Vault is built around one critical question:

How can organizations safely use AI on sensitive documents without sending data to the cloud?

This system answers that by combining:

Layer	Responsibility	Key Components
Document Processing	Extract text from all PDF types	PyMuPDF, Tesseract, EasyOCR
Intelligence Layer	Semantic understanding & retrieval	Embeddings + ChromaDB
Reasoning Layer	Multi-agent orchestration	Retriever, Generator, Verifier
Security Layer	Privacy & integrity	Offline execution + Hashing
Output Layer	Explainable results	Citations, confidence, reports

---

SCREENSHOTS

What Noetic Vault Does

• Accepts digital and scanned PDFs (including govt documents)
• Extracts structured text using a tiered OCR pipeline
• Converts documents into semantic embeddings
• Retrieves relevant information using vector search
• Generates human-like answers using local LLMs
• Verifies answers with source-backed validation
• Supports multilingual queries (English, Hindi, Marathi)
• Enables cross-document reasoning and contradiction detection
• Runs completely offline — no cloud dependency
• Provides optional blockchain-style document hashing

---

System Flow

User Upload (PDF)
        |
        v
OCR Engine (PyMuPDF / Tesseract / EasyOCR)
        |
        v
Text Cleaning + Semantic Chunking
        |
        v
Embedding Generation (Sentence-Transformers)
        |
        v
ChromaDB (Vector Storage)
        |
        v
Multi-Agent Pipeline
    |
    +--> RankerAgent (Retrieval)
    +--> GeneratorAgent (Answer)
    +--> VerifierAgent (Validation)
        |
        v
RAG Pipeline (Context + LLM)
        |
        v
Output:
- Answer
- Citations
- Confidence Score
- (Future: Risk Heatmap + Report)