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Local & Self-Hosted AI
Running AI on your own hardware. Open-weight models, private inference, RAG infrastructure, and edge deployment for teams that want control.
Choosing an Open-Weight Model for Your Use Case
A practical guide to picking the right open-weight LLM — comparing model families, understanding size tradeoffs, and matching models to real tasks.
ShiftQuality Contributor
Apr 238 min read
Building a Private AI Stack for Your Organization
A complete guide to building self-hosted AI infrastructure — from inference servers and vector stores to RAG pipelines, security, and cost analysis.
ShiftQuality Contributor
Dec 4, 202511 min read
Edge AI: Processing at the Boundary
Why AI is moving to the edge, what hardware and frameworks make it work, and how to optimize models for on-device inference.
ShiftQuality Contributor
Oct 11, 202510 min read
The Hardware You Actually Need for Local LLMs
A practical guide to the hardware that matters for running language models locally — GPUs, VRAM, RAM, CPUs, and realistic cost breakdowns.
ShiftQuality Contributor
Aug 19, 202510 min read
Running Ollama in Production: Beyond the Demo
A practical guide to running Ollama for team use — covering architecture, networking, model management, performance tuning, monitoring, and when to pick something else.
ShiftQuality Contributor
Jun 30, 20259 min read
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