Local AI Deployment Blueprint
100% Private • Zero Data Leakage • Small Business Configuration
The 100% Private Software Stack
This section details the software required to achieve your goal. Crucial finding regarding NotebookLM: It does not currently have a local, offline mode. It relies on Google's cloud infrastructure (Gemini 1.5). To keep company data strictly "out of the wild," we must replace it with a Local RAG (Retrieval-Augmented Generation) application that hooks into your Obsidian vault.
1. The Vault (Obsidian)
Your existing shared company vault remains the single source of truth. It stores raw markdown files. By keeping it local/synced via a private server, data remains secure.
2. The Engine (Ollama)
Replaces the "Cloud API" (like OpenAI). Ollama runs locally on your Mac, downloading and executing open-source models (like Llama 3) entirely on your local silicon.
3. The Interface (AnythingLLM)
Your NotebookLM Alternative. An open-source desktop app that connects to Ollama. You point it at your Obsidian folder, and it "reads" your vault to answer questions securely.
Why AnythingLLM or Open WebUI over NotebookLM?
NotebookLM sends your document text to Google servers for processing. AnythingLLM processes documents locally using a local embedding model, storing the vector database on your own hard drive. Zero data leaves the Mac.
Hardware: Apple Silicon Strategy
This section analyzes whether an M5 Ultra is necessary compared to a standard M4/M5. For Local AI, the most critical specification is Unified Memory (RAM) capacity and bandwidth, not purely CPU/GPU cores. Unified memory allows massive AI models to load entirely into VRAM.
Maximum LLM Parameter Size by Unified Memory
*Assuming 4-bit/8-bit quantization (standard for local inference). Larger models are "smarter" but require more memory.
The "M5 Ultra" Verdict
An Ultra chip combines two Max chips. It provides double the memory bandwidth (up to 800GB/s). This means the AI generates words much faster. However, it is overkill for a small team unless:
- You want to run massive 70B+ parameter models (like Llama-3-70B).
- Multiple employees will be querying the AI simultaneously (high concurrency).
The "Standard/Max" Sweet Spot
A Mac Studio M4 Max (or upcoming M5 Max) configured with 64GB or 128GB of Unified Memory is the ideal small business workhorse.
- It easily runs excellent 8B to 32B parameter models.
- It handles document retrieval (RAG) rapidly.
- It is significantly more cost-effective than the Ultra tier.
Starter Tips & Configuration
This section provides the actionable steps to deploy your private AI system once your Apple hardware arrives. Click each step to reveal configuration details.