StructiFi

What is StructiFi?

StructiFi is an AI-powered data extraction tool that transforms unstructured files into structured, actionable data. Leveraging advanced optical character recognition (OCR) and machine learning, it extracts text, tables, and key information from PDFs, images, and scanned documents with high accuracy. Whether you need to convert image to text, extract sales leads from business cards, or digitize exam papers, StructiFi simplifies the process.

Key features include robust OCR for multiple languages, intelligent table extraction, and automatic field mapping. It supports batch processing, allowing you to upload multiple files simultaneously. The tool also offers customizable extraction templates for recurring document types, such as invoices or catalogs. With a user-friendly web interface, no coding is required—just upload and download structured data in formats like Excel, CSV, or JSON.

Benefits include significant time savings by eliminating manual data entry, reduced errors through AI precision, and seamless integration with existing workflows. Use cases range from digitizing historical archives to automating lead generation from contact lists. StructiFi is ideal for businesses handling large volumes of documents, researchers needing quick data extraction, and developers seeking a reliable API for custom applications.

Technical details: StructiFi uses deep learning models trained on diverse document layouts. It supports PDF, JPG, PNG, and TIFF inputs, with output in structured formats. The beta version offers free usage with limitations on file size and number of pages per month. Pricing is based on a freemium model, with premium plans for higher volume and advanced features. Data security is ensured through encrypted uploads and processing. Currently in beta, StructiFi is continuously improving its accuracy and expanding language support.

Use Cases

Key Features

Who is it for?

business analysts, data entry teams, document processors, researchers, administrative staff, sales teams, archivists

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