Learn to extract data by intent and context rather than brittle CSS selectors, enabling scrapers to navigate structural changes seamlessly using Large Language Models.

Implementing Zero-Shot Semantic Parsing with LLMs

Discover how to create weighted similarity scores for elements, allowing your scraper to autonomously find moved or renamed components based on a rich attribute profile.

Building Resilient Selectors with Multi-Attribute DOM Fingerprinting

Explore techniques for using multimodal AI and OCR to identify and extract data points based on visual appearance and spatial positioning instead of underlying HTML.

Layout-Agnostic Scraping with Multimodal Computer Vision

Develop agentic pipelines that monitor data health scores and automatically trigger scraper logic re-calibration when a website's architecture shifts.

Designing Autonomous Validation and Self-Repair Feedback Loops

Master the engineering of self-healing web scrapers that leverage LLMs, computer vision, and structural fingerprinting to maintain data flow despite frequent DOM changes.

Autonomous Scrapers

Implementing Zero-Shot Semantic Parsing with LLMs

Building Resilient Selectors with Multi-Attribute DOM Fingerprinting

Layout-Agnostic Scraping with Multimodal Computer Vision

Designing Autonomous Validation and Self-Repair Feedback Loops