A curated guide to building a fully open-source RAG pipeline in 2026 — from web extraction to embedding models to vector databases to LLM inference.
An overview of web scraping legality in 2026: hiQ v. LinkedIn, robots.txt, ToS violations, GDPR, and best practices to keep your scraping defensible.
RAG or fine-tuning? A practical decision guide covering costs, update frequency, and when web scraping feeds your LLM better than baked-in training.
Most RAG systems are frozen at ingestion time. Learn how to add a live web layer to your pipeline for hybrid retrieval that combines long-term memory with real-time data.
Most web scraping produces garbage for LLMs. Learn what LLM-ready markdown is, how to evaluate it, and what KnowledgeSDK strips out for clean output.
A plain-English explainer on web scraping APIs: how they work, what they replace, and why every AI agent needs one. Get started in 5 minutes.