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Use Cases

🎓 Maintaining Academic Integrity with the Copyleaks API

In today’s evolving academic landscape, upholding integrity and originality is fundamental. Copyleaks is dedicated to empowering instructors and academic institutions with the tools to champion authentic student work and maintain the highest academic standards. Our mission is to provide comprehensive solutions that address the core challenges of modern education, from traditional plagiarism to the nuances of AI-generated content.

For developers, the Copyleaks API is the key to seamlessly integrating these critical capabilities directly into your institution’s unique ecosystem, such as a Learning Management System (LMS) or other academic platforms. By leveraging the API, you can empower instructors with robust plagiarism scanning, award-winning AI content detection, and a secure Shared Data Hub for assignments - all within the native workflows they use every day.

This guide will walk you through the essential API steps, from indexing documents to configuring advanced scanning options, enabling you to build a powerful, integrated solution that supports your institution’s commitment to academic integrity.


To get the most out of this document, you should first be familiar with how to submit a basic scan. If you’re new to the process, we recommend starting with the guide below.

Detect Plagiarism in Text: This guide walks you through the fundamentals of customizing your API request to scan for plagiarism, AI-generated text and grammar correction.

The Copyleaks API allows you to submit a variety of document types for analysis. You can upload files in formats such as PDF and DOCX. Additionally, you can submit documents by providing a URL.

Copyleaks also offers advanced capabilities, allowing you to upload images of text. This is made possible using Optical Character Recognition (OCR) technology.

The Shared Data Hub is a comprehensive database containing millions of user-submitted documents from institutions worldwide. This powerful resource significantly enhances academic integrity by expanding the scope of plagiarism detection beyond traditional sources.

The Shared Data Hub is particularly effective at detecting instances where students submit work that isn’t their own. For example, it can detect when:

  • A student submits an assignment previously written by a friend
  • The same paper is submitted to different institutions
  • Work is recycled from previous semesters or academic years

This detection capability helps maintain academic standards across educational institutions globally.

When you choose to scan against the Shared Data Hub, you’re not just benefiting from the collective database - you’re also contributing to it. Each document you submit helps strengthen the system for all users, creating a more robust detection network that benefits the entire academic community.

This contribution also benefits your own institution directly. Once your students’ assignments are added to the database, they cannot be recycled or reused by other students at your institution in future semesters.

You have full control over how your documents are compared within the Shared Data Hub:

  • Compare against your institution’s submissions: Use the properties.scanning.copyleaksDb.includeMySubmissions parameter to scan against documents from your own institution
  • Compare against other institutions’ submissions: Use the properties.scanning.copyleaksDb.includeOthersSubmissions parameter to scan against submissions of other users in the network
  • Use both options: Enable both parameters for the most comprehensive plagiarism detection

After completing a scan, your document is automatically indexed and stored within the Shared Data Hub. This makes it available for future comparisons against new submissions at your institution.

🗑️ If you need to remove a document from the database, you can use our delete request and set the purge parameter to true. This will completely remove the document from the Shared Data Hub.

  • Broader Detection: Access to millions of documents increases the likelihood of identifying plagiarism
  • Cross-Institutional Protection: Detect submissions that may have originated from other schools
  • Internal Protection: Prevent students from reusing assignments within your own institution
  • Community Collaboration: Help build a stronger academic integrity ecosystem for everyone

By leveraging the Shared Data Hub, you’re taking advantage of one of the most comprehensive plagiarism detection resources available while contributing to the fight against academic dishonesty.

To scan against a vast range of online sources, including many academic journals, set the properties.scanning.internet parameter to true. Internet results will be included in the Scan Completion Webhook.

  • To check for AI-written text, set the properties.aiGeneratedText.detect parameter to true.
  • Your AI detection results are delivered to a dedicated export webhook. For an example of how the data will be structured, see the Export AI Detection Response documentation.

Need help implementing these solutions? Our team is here to assist you every step of the way. Whether you have technical questions or need guidance on best practices, don’t hesitate to reach out through Copyleaks Support or engage with our developer community on StackOverflow using the copyleaks-api tag.

Schedule a Live Demo

Want to see how Copyleaks can enhance your academic integrity solutions? Our technical team can walk you through live examples of scanning against the Shared Data Hub, AI detection, and more.