Self-hosted AI guides
Chroma vs Weaviate for Self-Hosted Deployments: What Actually Matters
Compare Chroma and Weaviate for self-hosted vector search, including setup complexity, filtering, scalability, and maintenance trade-offs.
Read the guide →CPU vs GPU for AI Inference: Which One Makes Sense?
Compare CPU vs GPU for AI inference, including cost, latency, throughput, power use, and when each option makes sense for self-hosted model serving.
Read the guide →How to Deliver Digital Products from a Self-Hosted Stack
A practical guide to self-hosted digital product delivery, from file access and license workflows to payment-triggered fulfillment.
Read the guide →Document Search AI for Private Data: A Practical Architecture
Build document search AI for private files, policies, and internal docs with secure ingestion, retrieval, and answer grounding.
Read the guide →Embeddings Pipeline Best Practices for Self-Hosted Search
Improve semantic retrieval with a better embeddings pipeline, from preprocessing and chunking to versioning, reindexing, and evaluation.
Read the guide →How to Use Grafana for Monitoring Self-Hosted Services
Learn how to use Grafana dashboards effectively for self-hosted monitoring, from data sources and panels to alert-friendly layouts.
Read the guide →How to Set Up Listmonk for a Small Business Newsletter
A planning-focused overview of Listmonk setup, from server planning and SMTP configuration to subscriber forms and campaign sending.
Read the guide →Local AI Model Serving: What It Takes to Run Models Reliably
A practical look at local AI model serving, including runtimes, APIs, hardware planning, and the operational habits that make self-hosted inference sustainable.
Read the guide →How to Build a Local Document Q&A System Without Sending Files to SaaS
Create a local document Q&A system for PDFs, notes, and internal docs using self-hosted embeddings, vector search, and grounded answers.
Read the guide →Local Embedding Models: A Practical Guide for Private Search and RAG
Understand local embedding models, when to run them on CPU or GPU, and how they support private semantic search, clustering, and retrieval workflows.
Read the guide →Make vs n8n: Which Automation Platform Fits AI Workflows Better?
A practical comparison of Make vs n8n across pricing, flexibility, self-hosting, integrations, and AI workflow design for technical teams.
Read the guide →Matomo Setup Guide for Self-Hosted Analytics on Your Own Server
A planning-focused guide to planning, installing, and operating a self-hosted Matomo instance for privacy-aware website analytics.
Read the guide →How to Build a Membership Site Without SaaS Lock-In
A practical blueprint for building a membership site without relying entirely on SaaS platforms for access, billing logic, and customer ownership.
Read the guide →No-Code AI Automation: What It Does Well and Where It Breaks
A grounded look at no-code AI automation, including common use cases, operational limits, and how to design safer workflows.
Read the guide →Observability Without SaaS: A Stack You Can Maintain
How to build observability without SaaS using self-hosted metrics, logs, dashboards, and alerts that stay manageable over time.
Read the guide →How to Set Up Ollama for Local AI on Linux or macOS
A practical Ollama setup guide covering installation, model pulls, API usage, and hardware expectations for a useful local AI endpoint.
Read the guide →Open-Source Contact Management for Businesses That Outgrew Spreadsheets
How to evaluate open-source contact management tools when spreadsheets and shared inboxes no longer provide enough structure.
Read the guide →Open-Source Model Hosting: How to Serve Models You Control
A practical guide to open-source model hosting, including storage, runtimes, APIs, and the tradeoffs involved in serving models on infrastructure you control.
Read the guide →Plausible vs Umami for Self-Hosted Analytics: Which Should You Choose?
A practical comparison of Plausible and Umami for teams that want lightweight, privacy-friendly self-hosted web analytics.
Read the guide →Privacy-First Contact Forms That Still Convert
A practical framework for building privacy-first contact forms that still convert well and integrate with your own systems.
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