GlossIA: Enterprise Semantic Retrieval System

Architectural Blueprint for Scalable Retrieval-Augmented Generation (RAG)

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🌐 Overview

GlossIA is a high-performance architectural framework designed to solve the "context gap" in industrial and enterprise-level AI systems. Originally developed to handle complex translation audits and technical commentary, this system leverages a robust RAG (Retrieval-Augmented Generation) pipeline to provide accurate, context-aware responses.

Note: This repository contains the Architectural Blueprint and Documentation. The core source code is proprietary and remains under a private license for enterprise security.

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🏗️ System Architecture

The system is built on a modular "Hybrid-Cloud" approach, balancing local privacy (Ollama) with cloud-scale reasoning (AWS Bedrock).

graph TD
    A[Raw Data Source] --> B[Text Chunking & Preprocessing]
    B --> C[Sentence Transformers - Embeddings]
    C --> D[(Milvus Vector Database)]
    E[User Query] --> F[Contextual Search]
    D -.-> F
    F --> G{Orchestrator}
    G --> H[Local Inference: Ollama]
    G --> I[Cloud Inference: AWS Bedrock]
    H & I --> J[Contextualized Final Response]

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