I will deploy a secure, fully offline Retrieval-Augmented Generation (RAG) search engine on your local workstations or private servers. Your sensitive manuals, schematics, and proprietary documents never leave your physical hardware.
I will build and deploy a hardened, fully offline RAG search engine on your private server or hardware.
Hardened offline RAG search configuration on 1 local workstation (macOS, Linux, or Windows). Ingests standard text-based PDFs. Integrates with your local Ollama setup.
Multi-user local RAG deployment on your private network/dedicated hardware. Custom ingestion pipelines tuned for complex PDFs containing technical tables, schematics, and figures.
Enterprise-grade, fully air-gapped local RAG on isolated hardware. Advanced custom chunking for specialized proprietary/technical files. Includes 30 days of direct engineering support.
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Key details about this service to help you decide. Generated by Zinn Hub, not the seller.
Value Position
Deployment Type
Supported Platforms
LLM Engine
Best For
What You'll Receive
Full Description
Most document assistants require uploading proprietary PDFs to third-party cloud servers. For professionals handling flight manuals, engineering schematics, legal documents, or ITAR-regulated data, that is a critical security vulnerability.
This service deploys a hardened, local-first RAG pipeline that runs entirely on your physical hardware using Ollama and local vector databases. No cloud dependencies. No recurring data subscriptions. Absolute data sovereignty.
What this service delivers
- Local vector database configuration: Secure indexing of your document library on local SSD storage.
- Ollama model optimization: Proper parameter tuning and model selection based on your hardware specifications (macOS, Linux, or Windows).
- Technical document parsing: Advanced ingestion pipelines capable of extracting tables, system schematics, and figures.
- Offline search interface: A direct interface to query your local knowledge base without active internet connections.
The Process Step-by-Step
- Hardware & Data Assessment: We evaluate your current hardware specifications and document formats to select the optimal open-source LLM.
- Local Pipeline Deployment: We set up the local vector store, embedding models, and Ollama integration on your server or workstation.
- Data Ingestion & Chunking: Your PDFs and technical files are parsed and embedded locally.
- Offline Validation & Testing: We verify query accuracy, speed, and local hardware utilization to ensure the system is stable and fully offline.
Packages
1. Basic: Pilot Node
- Focus: Local workstation deployment for a single professional.
- Deliverable: Full configuration of an offline RAG pipeline on one local machine (macOS, Linux, or Windows) connected to Ollama. Includes basic text PDF indexing.
- Delivery Time: 5 days
2. Standard: Hangar Server
- Focus: Multi-user private network deployment on dedicated local hardware.
- Deliverable: Multi-user local RAG deployment on your private network or server. Ingestion pipelines optimized for complex technical PDFs containing schematics and system tables.
- Delivery Time: 10 days
3. Premium: Sovereign Vault
- Focus: Enterprise-grade, fully air-gapped, high-security local RAG deployment.
- Deliverable: Complete deployment on isolated hardware. Extreme optimization for running large open-source model weights. Custom chunking strategies for highly specialized technical databases. Includes 30 days of direct engineering support.
- Delivery Time: 14 days
Why Choose This Service
This is built by CAVOK Designs. We are pilots, engineers, and builders based in Melbourne, FL. We do not build wrappers or sell software-as-a-service subscriptions. We build hardened, professional-grade systems for operators who require absolute data security and zero cloud leakage.
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Compare Packages
| Feature | Pilot Node | Hangar Service | Sovereign Vault |
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 14 days |
| Revisions | 1 | 2 | 3 |
Service Details
Frequently Asked Questions
Your data never leaves your physical hardware. The entire pipeline, including the embedding models, vector database, and large language models, is compiled and deployed to run locally on your machine. We do not use external cloud APIs. You can completely disconnect your machine from the internet during use to verify zero network activity.
For the basic workstation package, a standard modern computer with at least 16GB of RAM is sufficient. For heavier technical manuals and multi-user configurations, we recommend dedicated hardware with an Apple Silicon processor (32GB+ Unified Memory) or an NVIDIA GPU with at least 12GB of VRAM to ensure fast query response times.
Cloud-based assistants require you to send your documents to their servers, creating a major security risk for proprietary data. They also charge recurring monthly subscriptions. Our local RAG engine is a one-time setup fee, runs 100% locally on your own metal, and gives you absolute control over your private intellectual property.
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