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Smart Node 1.12.52 fixes five quietly-failing behaviours: the daily email digest now arrives on every node, updates finish in fewer steps, custom workflows survive platform updates, the approval gate starts on fresh installs, and the voice service confirms readiness after restart.
A practical guide to what a self-hosted AI assistant actually takes: server specs, setup sequence, honest limits on data isolation, and what goes wrong first.
What a local AI server is, which hardware it needs, and what it costs to run one: architecture facts without promotional claims.
Running an LLM on your own hardware means choosing between hybrid and fully local inference. Here is what each option requires in hardware and operations.
Open-weight models run on your hardware; frontier APIs route through a controlled egress boundary. Which tasks belong where, and what compute each path needs.
Self-hosted AI agents cut per-seat fees by running the runtime on your own server. Here is what that costs instead and how to set one up.
Not all self-hosted AI keeps your data local. These 8 properties show what real infrastructure control requires, with concrete specs and honest tradeoffs.
A plain-terms guide to running an AI chatbot on your own Linux server: what stays on your machine, what leaves, and what it takes to set it up.
What an AI server for a small business actually requires: hardware specs, infrastructure tiers, privacy tradeoffs, and the steps to get one running.
AI agents can run on vendor cloud, a VPS, or local hardware. This guide explains the real tradeoffs in data flow, cost, and control before you decide.
What running a personal AI assistant on your own server actually means: what stays local, what can transit external networks, hardware numbers, and setup steps.
Understand what on-premise AI agents actually control locally, where inference still crosses external networks, and whether the operating model fits your team.
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