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Deploy a private on-prem conversational RAG system with configurable containers.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "minima" yet — see the docs or source repo.
Use minima to deploy an on-prem conversational RAG system in containers, connect our product docs and FAQs, and provide the recommended service components, deployment steps, and baseline configuration suggestions.
An internal knowledge assistant deployment plan with container components, document ingestion, and configuration guidance.
I want to use minima to build a private Q&A system for the engineering team. Plan how to import API docs, design the retrieval flow, configure container services, and support multiple users.
A private RAG plan for engineering teams covering document ingestion, retrieval architecture, and container deployment design.
Use minima to design a conversational retrieval solution that stays inside the internal network, uses local deployment and configurable containers, and explain key architecture and operations considerations for sensitive materials.
A security-focused knowledge retrieval architecture recommendation emphasizing on-prem deployment and container configuration.
Set up a local RAG server for private knowledge search and QA.
Query private knowledge bases with modular RAG, hybrid retrieval, reranking, and observability.
Search local knowledge packs and retrieve chunks for stronger AI answers.
Store and retrieve text semantically with local vector memory for conversations.
Let AI securely search private local documents with semantic and keyword retrieval.
Build modular RAG workflows for document Q&A, semantic search, and knowledge bases.