Amigotor

By transforming static document archives into conversational knowledge bases, Amigotor eliminates the need to manually search through long documents to find specific information, delivering the relevant content in response to natural language questions.

Document format support is comprehensive: standard PDFs and Word documents are handled natively, while image recognition technology extends coverage to scanned physical documents and book pages that have been photographed with a mobile device.

This OCR-powered image-to-text capability means that physical documents in any formatprinted reports, handwritten notes, textbook pagescan be uploaded as photographs and made immediately queryable through the same conversational interface.

Instant summarization, information extraction, and follow-up question generation make Amigotor effective for users who need to process large volumes of documents quickly.

Rather than reading every page of a lengthy contract, research paper, or policy document, users can ask Amigotor for the key points, specific clauses, or critical data points they needand receive targeted answers with source references that allow them to verify information in the original document if needed.

Team collaboration is supported through shared workspaces where multiple team members can access the same AI-powered document manager.

New documents can be added to the shared knowledge base continuously, and team members can ask questions across the entire document collectionmaking Amigotor a practical solution for teams managing shared research libraries, client document collections, or internal knowledge bases that multiple people need to query simultaneously.