Overview
Building on the Local LLM Deployment project, this follow-on connects a cloud-hosted assistant interface to a locally-running LLM for inference processing. The cloud layer handles user authentication, session management, and orchestration of agentic workflows, while all ground-truth data, model inference, and sensitive processing remain on local infrastructure. This creates clear security boundaries between the ingress/orchestration layer and the execution/inference layer.
Applied Skills
- Hybrid cloud-local architecture design and implementation
- Security boundary modeling between orchestration and inference layers
- API integration between cloud-hosted services and local endpoints
- Agentic workflow orchestration across distributed environments
Deliverables
A working hybrid system with architecture documentation showing isolated security zones. Demonstrates a deployment pattern highly relevant to regulated industries (healthcare, finance, government) where sensitive data must remain on-premises while leveraging cloud-based user interfaces and orchestration.