ScrapeGraphAI is an open-source web-scraping framework that uses language models and graph-based workflows to extract information from websites. Instead of requiring developers to hand-code a selector and parsing strategy for every page, it allows extraction tasks to be described at a higher level and combines browser or scraping components with AI reasoning.

The project supports structured extraction and other scraping workflows that can adapt to varied web content. Its graph architecture makes the processing pipeline composable, allowing developers to combine loading, model calls, parsing, and output steps according to the needs of a particular data-collection task.

ScrapeGraphAI is useful for research agents, data pipelines, monitoring systems, lead generation, content aggregation, and other applications where website structure is inconsistent or changes frequently. It provides a bridge between conventional scraping infrastructure and LLM-based interpretation, reducing the amount of site-specific extraction logic developers need to maintain.