GenAI_RAG

Smart Search with Retrieval-Augmented Generation(RAG)

Offline & Open Source RAG-Based AI Solutions

1. Private RAG (Retrieval-Augmented Generation) Solutions

  • Deploy fully air-gapped RAG systems using:
  • Ollama (LLaMA2/3, Mistral, Phi-3, etc.)
  • ChromaDB / Qdrant / FAISS for vector storage
  • LangChain or LlamaIndex for orchestration
  • Document loaders: PDFs, DOCX, CSV, TXT
  • Integrated question-answering from private corporates

2. Offline Chatbots for Teams or Intranet Portals

  • Self-contained chatbot servers hosted on-prem or laptop
  • No cloud dependency; runs on CPU or minimal GPU
  • File-based knowledge ingestion (SharePoint exports, shared drives)

3. Multilingual & Voice-enabled Offline Assistants

  • Integrate Whisper.cpp, Vosk, or Coqui.ai for STT/TTS
  • Translation using OpenNMT, MarianMT (offline-capable)
  • Run multilingual Q&A bots without internet dependency

4. Low-Power / Edge AI Deployment

  • Deploy LLMs on Raspberry Pi, Jetson Nano, or offline laptops
  • Compress models using GGUF or quantized weights
  • Ideal for field workers, defense, and low-connectivity areas

Vectorization & Indexing Services

1. Embedding & Indexing Optimization

  • Use GGUF-friendly models (e.g. all-MiniLM, BGE) for embedding text chunks
  • Tune chunking strategies:
    • Based on sentence similarity, headings, or fixed token windows
    • Adaptive chunking for tables, FAQs, policies
  • Build collections in ChromaDB or other local vector stores

2. Automated Re-indexing & Change Detection

  • Detect file changes in watched folders or DMS exports
  • Delta re-indexing: update only changed or new files
  • Version history tagging for audit trail

Document Hygiene & Preparation

1. Automated Document Cleaning & Preprocessing

  • Batch processing pipelines to:
    • Remove boilerplate text, headers/footers, and scanned noise
    • Correct encoding issues, OCR raw scans (via Tesseract or EasyOCR)
    • Normalize structure (paragraphs, lists, tables)

2. PII/Sensitive Information Detection & Masking

  • Use NER models (spaCy, Presidio, Stanza) to detect:
    • Names, phone numbers, emails, IDs, financial data
  • Replace/mask sensitive data with placeholders or metadata tags
  • Optional human-in-the-loop redaction flow

3. Document Classification & Grouping

  • Auto-categorize documents using keyword/topic extraction
  • Tag documents by department, subject, source, and priority
  • Group into logical collections before vectorization

Search & Retrieval Optimization

1. Contextual Smart Search Interface

  • Build local web interface with:
    • Keyword and semantic search toggle
    • Source highlighting, document previews, metadata filters
  • Add feedback loop (thumbs up/down) for accuracy tracking

2. Multi-source Hybrid Search

  • Merge knowledge from PDFs, DOCX, TXT, CSV, Markdown
  • Embed metadata such as file name, creation date, tags in context
  • Add optional relational DB fetch via SQLite for structured data lookup

Maintenance & Support Services

1. Managed Offline RAG System Support

  • Monthly health checks of embedding quality and index accuracy
  • Performance profiling and latency tuning
  • Continuous redaction, classification, and version sync

2. User Training & Prompt Design for RAG

  • Train internal users on:
    • Using offline chat interfaces effectively
    • Designing system prompts for accurate retrieval
    • Provide pre-built prompt templates for typical queries