Magic Import Document Extractor is a WordPress plugin designed to convert documents into structured data using AI-powered processing. The tool enables users to upload documents in a variety of formats, including PDF, DOCX, PNG, JPEG, GIF, CSV, JSON, and XML, with support for over eleven file types. Its primary function is to automatically extract and map data from these documents directly into form fields, streamlining workflows such as contact forms, applications, and data entry tasks.
The extraction process utilizes Claude AI, which provides intelligent field mapping and semantic understanding to achieve high accuracy in identifying and populating relevant form fields. Users can upload documents with a simple drag-and-drop or one-click interface, and the platform handles the extraction and field mapping automatically. Processing times typically range from three to eight seconds per document. Notably, the service emphasizes secure processing, stating that document contents are never stored on its servers.
Magic Import Document Extractor is accessible through a 24/7 online portal and is positioned for teams seeking to streamline their data entry processes within WordPress. The tool offers a free forever plan that does not require a credit card to get started. This positions it as an accessible solution for organizations or individuals looking to automate the transformation of document data into structured formats within their WordPress sites.
Magic Import Document Extractor is an AI project. It focuses on extracting structured data from uploaded documents in WordPress forms without manual entry. It is built as a B2B product for wordPress site owners needing document data extraction. A free plan is available. It ships for the web and API.
It is developed by magicimport, and it first shipped in 2025. Key capabilities include AI document extraction, multilingual support, and drag & drop interface. The interface is available in English and Chinese. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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