What Running an On-Premise LLM Actually Takes
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.
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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.
Eight AI agent roles for a small business, ranked by operational impact, each grounded in what a self-hosted node can actually deliver today.
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.
A practical guide to evaluating data isolation for AI agents: which boundaries matter, where the tradeoffs sit, and what to ask before committing to a platform.
What an AI office assistant handles, what it cannot do on its own, and how to deploy one on a server you control. A practical setup guide.
A practical guide for small business owners: how to evaluate conversational AI tools on data control, cost structure, channel support, and human oversight.
Agentic automation handles variable paths that fixed rules cannot. Learn what distinguishes it, what controls it, and when your process needs it.
A practical framework for evaluating AI customer service agents for small business: where data lives, which actions need your approval, and how costs scale.
Eight virtual assistant AI examples for a small business: what each does, when it fits, and where a human approval gate applies before anything leaves the server.
Learn how an AI agent reads incoming supplier emails, checks your order records, and drafts a reply that you approve before anything is sent.
Nine questions to answer before choosing an AI assistant for business: data ownership, cost structure, human oversight, and infrastructure fit.
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.
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