Local AI Infrastructure

Status: Active R&D
Area: Local-first Artificial Intelligence · Systems Architecture

Purpose

This project investigates local AI infrastructure that keeps model execution, routing and orchestration under operator control while allowing components to be replaced as requirements change.

Research questions

• How should local models, remote providers and routing layers be separated architecturally?
• How can context limits, model capabilities and endpoint health be exposed instead of hidden?
• How can agent workflows remain inspectable and recoverable when individual components fail?
• Which workloads belong on local hardware and which can be delegated without compromising privacy requirements?

Current scope

• local model serving and inference endpoints
• model routing and provider abstraction
• agent and dispatcher architectures
• health checks and endpoint discovery
• context-window and resource management
• privacy-aware local-first workflows
• integration with webOwie infrastructure components

Output policy

This page represents ongoing architecture and implementation work. Model benchmarks, compatibility claims and releases will be added only when backed by a reproducible source record.