PromptLoop

This feature enables users to build AI‑powered tasks that navigate websites, extract specified data points, and return structured results from large datasets. It supports single‑page, smart crawl, and deep research depths to tailor how far the system explores. The approach is designed for scaling data collection across thousands of sites with precision and formatting control.

The platform helps teams extract many rows of structured data from websites, for example names, titles, or product lists, by defining output columns and filtering criteria. Advanced steps minimize false extractions by using reasoning models that verify entity counts before extraction. Results are automatically search‑able, filterable, and exportable for further analysis.

This dynamic feature allows users to specify custom columns for extraction via a JSON definition, enabling up to six columns per task endpoint when required. It simplifies real‑time data integration by letting teams define the exact queries, instructions, and keywords for each column. Ideal for serving tailored data directly from websites into operational workflows.

The software offers automated monitoring of websites or datasets for changes, with configurable filters and job cadence (e.g., hourly, daily, every 30 days). It sends alerts and summary emails when target data changes, enabling proactive tracking of leads, hiring activity, or specific web triggers. It’s designed to keep users ahead of relevant updates.

This feature provides transparency and control by assigning a confidence score (1–10) to each output, based on factors like ambiguity, navigation complexity, and obfuscation. The platform also supplies analysis tools to review performance, filter results by threshold, and identify rows that require human‑review. It fosters reliability on a scale.