Local Model Solution
Local LLM RAG
A retrieval-augmented generation pattern that keeps documents, prompts, model inference, citations, and audit logs inside a local or restricted environment.
Outcomes
What this solution should deliver
The solution is designed around practical delivery outcomes, not only a demo interface.
Architecture
Architecture areas
These are the main architecture pieces to design, deploy, and operate.
Local document store
Retriever and context selector
Grounded prompt builder
Local model runtime such as Ollama
Citation builder and audit log
Runtime status checks and fallback behavior
Available kits
Implementation kits and resources
Start with these SovAIHub kits or resources, then adapt the implementation to your environment.
SovAI Air-Gap AI Starter v0.2 Ollama
Local RAG workflow using Ollama, llama3.2:1b, citations, and audit logging.
OpenModel Selection Guide
Interactive guide for choosing a model based on data sensitivity, infrastructure, and use case.
OpenImplementation Planning
Discuss how local LLM RAG should fit your data, model, and deployment constraints.
OpenGovernance
Controls to plan from the beginning
For enterprise and sovereign AI environments, governance needs to be part of the architecture, not an afterthought.
Contact
Need this solution adapted for your environment?
Share your data environment, model strategy, deployment constraints, and governance requirements to map the right implementation path.
Turn the solution pattern into a deployable plan.
The right path depends on your data sensitivity, runtime restrictions, platform stack, artifact supply chain, and operating model.