Local AI Foundry -- Private Model Operations

A local model is not a platform until you can route work, observe health, recover failures, and explain its limits.

Local AI Foundry turns an Apple Silicon workstation into an operable private AI environment. It joins machine inventory, workload benchmarking, runtime selection, private networking, launch persistence, model health, semantic-memory boundaries, and recovery testing.

What you get

• Hardware and workload inventory before model recommendations
• Measured generation, prompt-ingestion, cold-load, memory, and concurrency evidence
• Ollama/MLX/runtime routing based on observed fit
• Private LAN or tailnet exposure with explicit authentication boundaries
• Health, logging, restart, boot, disk, network-loss, and model-eviction checks
• A capacity map and operator runbook for the actual machine

This is for builders running coding agents, private chat, embeddings, batch work, or shared model APIs on Apple Silicon. It does not copy benchmark expectations between machines or quietly change power, GPU-memory, firewall, or remote-access settings.

Pairs with Baton for continuity and Evidence Gate for proving that installed services are actually reachable and healthy.