RAGStack: A Privacy-First GenAI Retrieval-Augmented Generation Architecture for Secure Enterprise Document Intelligence Article Swipe
RAGStack is a fully local, privacy-first Retrieval-Augmented Generation (RAG) framework for enterprise document intelligence and question answering. It integrates PyMuPDF for parsing, SentenceTransformers for embedding generation, FAISS for local semantic retrieval, and Ollama-hosted large language models (LLMs) for response generation. Featuring auto-indexing, manifest-based deduplication, self-healing index rebuilding, and normalized (0–1) similarity scoring, the framework enables compliance-ready AI deployment in offline or air-gapped enterprise environments. Recommended Citation: Srivastava, M. (2025). *RAGStack: A Privacy-First GenAI Retrieval-Augmented Generation Architecture for Secure Enterprise Document Intelligence (v1.0.1)*. Zenodo. https://doi.org/10.5281/zenodo.17878948
Related Topics
Concepts
Computer science
Enterprise architecture
Enterprise information security architecture
Enterprise integration
Software deployment
NIST Enterprise Architecture Model
Embedding
Architecture domain
Enterprise information system
Enterprise architecture framework
Architecture
Software engineering
Enterprise architecture management
Key (lock)
Semantics (computer science)
Knowledge management
Enterprise software
World Wide Web
Intelligence analysis
Enterprise life cycle
Enterprise modelling
Artificial intelligence
Similarity (geometry)
View model
Architecture framework
Applications architecture
Intrusion detection system
Applications of artificial intelligence
Index (typography)
Business architecture
Enterprise data management
Integrated enterprise modeling
Database
Solution architecture
Enterprise system
Information retrieval
Metadata
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- other
- Landing Page
- https://doi.org/10.5281/zenodo.17878948
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W7114783641
All OpenAlex metadata
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https://openalex.org/W7114783641Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.17878948Digital Object Identifier
- Title
-
RAGStack: A Privacy-First GenAI Retrieval-Augmented Generation Architecture for Secure Enterprise Document IntelligenceWork title
- Type
-
otherOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
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2025-12-10Full publication date if available
- Authors
-
Srivastava, MohitList of authors in order
- Landing page
-
https://doi.org/10.5281/zenodo.17878948Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.5281/zenodo.17878948Direct OA link when available
- Concepts
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Computer science, Enterprise architecture, Enterprise information security architecture, Enterprise integration, Software deployment, NIST Enterprise Architecture Model, Embedding, Architecture domain, Enterprise information system, Enterprise architecture framework, Architecture, Software engineering, Enterprise architecture management, Key (lock), Semantics (computer science), Knowledge management, Enterprise software, World Wide Web, Intelligence analysis, Enterprise life cycle, Enterprise modelling, Artificial intelligence, Similarity (geometry), View model, Architecture framework, Applications architecture, Intrusion detection system, Applications of artificial intelligence, Index (typography), Business architecture, Enterprise data management, Integrated enterprise modeling, Database, Solution architecture, Enterprise system, Information retrievalTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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