Webhound runs long-lived autonomous AI agents that continuously browse websites, extract structured data, and compile research findings for analysis and downstream workflows.
Webhound is an autonomous AI agent platform designed for long-running web research and large-scale data extraction. It continuously navigates websites, follows links, and collects structured information without requiring constant human supervision. The tool is built to handle complex, multi-step research tasks that go beyond simple scraping or one-off queries, making it suitable for ongoing monitoring and analysis of web content over time.
Webhound offers configurable agents that can be tailored to specific domains, query types, and data schemas, allowing users to define what information to extract and how it should be structured. It supports crawling dynamic websites, handling pagination, forms, and JavaScript-rendered content to capture data that traditional scrapers may miss. The platform includes mechanisms for error handling, retries, and progress tracking so that long-running jobs can recover from interruptions and maintain reliability. Webhound also integrates with common data destinations and formats, enabling users to export results into databases, spreadsheets, or analytics pipelines.
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