Looking for Mac Mini Local AI Stack Setup — Ollama + n8n + AnythingLLM (Paid, $500, Denver,CO)

Hey everyone, I’m looking for someone who can physically or remotely set up a Mac Mini M4 for 24/7 local AI operations. This is a paid one-time project, $500 fixed.

What needs to be set up:

  • macOS hardened (FileVault, firewall, dedicated user account)

  • Ollama running and tested with at least one model

  • n8n self-hosted, running as a persistent service that survives reboots

  • AnythingLLM connected to local Ollama

  • ChromaDB for vector memory

  • Telegram bot integration via n8n

  • One end-to-end workflow test confirming everything talks to each other

Deliverable is a working machine + written setup summary.

Location: Denver, CO. On-site preferred, but remote screen share works if you’re confident in Mac-based local AI setups.

DM me or reply here if you’ve done something similar. GitHub or homelab examples welcome.

Budget: $500 fixed.

3 Likes

why what can i learn here?

Hey, this is right up my alley - I run a similar stack in production on my own VPS (self-hosted n8n + Docker + LLM APIs + Telegram bot).

I’ve built 4 production n8n workflows including a Telegram support bot with AI classification and a market monitoring pipeline. All on GitHub: GitHub - penkayone/n8n-automation-portfolio: Production-grade n8n workflow automations — AI lead intelligence, competitive market monitoring, customer support bot, multi-API company research. 4 enterprise workflows, 62 nodes, 9 AI calls, 40+ tech signatures. · GitHub

I haven’t worked with macOS specifically for this kind of setup, but the stack itself (Ollama, ChromaDB, n8n as a service, AnythingLLM) is all stuff I’ve configured and debugged before on Linux. Happy to do it via remote screen share.

DM me if you want to chat - I’m in CET timezone, flexible on hours.
Email: [email protected]

Telegram - @antongoloskokov

Anton saw the portfolio impressive n8n work. Since you mentioned your experience is primarily Linux/VPS, I have two specific ‘Mac-side’ questions to ensure this stays 24/7 stable:

  1. Persistence: macOS doesn’t use systemd. How do you plan to ensure n8n and ChromaDB survive a reboot and run as background services without an active user session logged in?

  2. M4 Performance: Since this isn’t a VPS with shared vCPUs, how will you ensure Ollama leverages the M4’s Unified Memory/GPU efficiently without interfering with the macOS window server?

  3. Connectivity: I’m in MST (7 hours behind you). Are you comfortable with a handoff/sync window between 1 PM and 5 PM MST?

If you’re confident you can translate your Linux stack to a hardened macOS environment, let’s talk.

Docker networking between Ollama and n8n is where most of these setups silently break — models load fine, but the agent never actually talks to the local inference layer.

Shipped a private document-search system for a law firm last month: zero cloud calls, fully hands-free, live in 36 hours.

First move today: I’d validate your Mac Mini’s virtualization config and wire the container network correctly before touching any model.

Want a working docker-compose scaffold sent to you tonight — free, no strings?

— Richard | [email protected]

Hi there,

I can remotely set up your Mac Mini M4 for a robust, 24/7 local AI operation. I have extensive experience self-hosting n8n and integrating it with local LLM stacks, ensuring everything is persistent and survives reboots.

How I will handle your setup:

  • Hardening & Persistence: I’ll configure macOS security (FileVault/Firewall) and set up n8n and Ollama as background services (using launchd or Docker) so they auto-start on boot.

  • The AI Stack: I’ll deploy Ollama, connect it to AnythingLLM, and spin up ChromaDB as your vector store. I’ll ensure the M4’s Unified Memory is properly utilized for optimal inference speeds.

  • Telegram Integration: I’ll build a “Heartbeat” workflow in n8n that connects your Telegram bot to the local Ollama instance, confirming the end-to-end data flow.

  • Documentation: You’ll receive a Written Setup Summary with all local endpoints, service commands, and a “Quick Restart” guide.

Why me: I’m a developer focused on production-grade automations. I don’t just “install” apps; I build systems that stay online. I’m comfortable working via remote screen share and can adjust to your Denver timezone for the session.

My Work (Self-hosted & AI): https://mikedevai.netlify.app/ Connect: @hely_chatbots (Telegram)

Ready to start this weekend and get your M4 AI-ready. When can we hop on a screen share?

Best regards, Mihail Rogal

Anton, saw the portfolio—impressive n8n work. Since your experience is primarily Linux/VPS, I have two specific ‘Mac-side’ questions to ensure this stays 24/7 stable:

  1. Persistence: macOS doesn’t use systemd. For a headless Mac Mini, how do you plan to ensure n8n and ChromaDB survive a reboot and run as background services without an active user session logged in?

  2. Hardware Optimization: How will you ensure Ollama is correctly leveraging the M4’s Unified Memory/GPU (Metal) rather than just hitting the CPU?

  3. Scheduling: I’m in MST (7 hours behind you). Note that I am unavailable on Mondays, Wednesdays, and Fridays between 5 AM and 1 PM local time. Does that sync window work for you?

If you’re confident you can translate your Linux stack to a hardened macOS environment, let’s talk