Barad-dûr AI platform
A personal homelab R&D stack: hardware I spec'd and built, a 100+ TB Unraid array, and a local operator console for chat, tools, evals, and multi-GPU inference — with approval gates so agents cannot run wild on my network.
This is not a client deliverable. It is the sandbox where I pressure-test agent patterns, local inference routing, and operator safety before I adapt the ideas into paid work.
Why it exists
A place to learn faster than cloud rent allows
I wanted full control over storage, GPUs, and services for AI and automation experiments — without shipping homelab internals to a client environment. Barad-dûr is the hardware plus the operator console that sits on top of it.
Honesty boundary: this write-up stays pattern-level. No internal hostnames, credentials, or client-adjacent data. The point is to show how I think about infra, agent safety, and local AI — not to expose the homelab map.
What I built
Hardware underneath, operator console on top
Homelab hardware & storage
Self-built Unraid server with a 100+ TB storage array, Docker service stack, Home Assistant integration, and multi-GPU nodes (GTX + RTX classes) used for local inference routing.
Barad-dûr operator console
FastAPI backend and Next.js UI for local Ollama chat, admin diagnostics, a code workbench, eval/benchmark harnesses, and SQLite-backed threads, settings, and watchdog runs.
Approval-gated agent tools
Homelab health checks, workspace edits, Home Assistant actions, web search, memory, operator KB search, weather/time lookups, GPU status, and host probes — staged until I approve.
Safety & routing
Multi-GPU routing between lighter and heavier nodes; code edits stay staged until an explicit apply step; bounded modes for experimentation without turning the whole LAN into an open tool surface.
What it proves for clients
Infra depth you can trust when I design your systems layer
Clients rarely need a homelab. They do need someone who understands how data, GPUs, agents, and humans share responsibility — and who has actually operated all three together.
Self-hosted fluency
- Unraid + Docker operations
- Multi-TB storage planning
- LAN-safe service exposure
Agent governance
- Human-in-the-loop tool gates
- Evals & benchmark loops
- Staged code / diff apply
Transferable patterns
- RAG / context layers
- Routing & degradation
- Operator docs & runbooks