Extractor vs Ollama

“Schema-driven extraction with LLM fallback is exactly right. Traditional scrapers break on every site redesign — Extractor adapts because it understands the content semantically. The TypeScript-first approach with strong typing on outputs is chef's kiss for building data pipelines.”

“The Docker of LLMs. Pull a model, run it, use the API. Privacy, no cloud costs, works offline. Essential tool for any developer experimenting with local AI.”

“LLM extraction costs add up fast at scale. But for the use cases where you need it — scraping sites with unpredictable layouts, extracting from pages that change frequently — the reliability improvement over CSS selectors easily justifies the token spend.”

“Local models still lag behind cloud models in quality. But for development, testing, and privacy-sensitive use cases, Ollama is the obvious choice. Free is hard to beat.”

“I have been using this to pull structured data from competitor landing pages and product directories. The schema definition is intuitive and the extraction quality is surprisingly consistent even across wildly different page designs.”

“Local AI is the future for privacy and cost. As models get smaller and hardware gets better, Ollama becomes the default way to run AI. They are building the runtime layer.”