Universities face unique challenges when it comes to plagiarism detection. Unlike individual educators checking a single class, institutions must enforce consistent academic integrity standards across hundreds of courses, thousands of students, and multiple departments — each with different submission formats, grading timelines, and disciplinary conventions.
An effective institutional solution needs to scale beyond what consumer-grade tools can offer. It requires the ability to build internal document databases, generate branded reports suitable for academic integrity proceedings, support volume deployments across departments, and integrate with existing academic workflows. Plagiarism Detector addresses these institutional requirements through features specifically designed for university-scale deployment.
The Plagiarism Detector Accumulator Server (PDAS) is a dedicated server solution that allows universities to build and maintain their own private database of previously submitted student work. Every paper checked through the system can be added to this institutional repository, creating a growing archive that catches recycled submissions — students reusing papers from prior semesters or submitting work originally written for a different course.
Unlike cloud-based services that pool documents from all subscribing institutions into a shared database, PDAS keeps your institution's data separate and under your control. This is particularly important for universities that handle sensitive research, classified projects, or proprietary academic content. The PDAS server runs on your infrastructure, giving your IT department full oversight of document storage, retention policies, and access controls.
Academic plagiarism often involves copying from published research papers, journal articles, and conference proceedings — sources that may not appear in standard Internet search results. The SciPap database is a specialized index of scientific publications that Plagiarism Detector uses to cross-reference submitted work against the scholarly literature.
This is especially critical for graduate programs, doctoral research, and any department where students are expected to engage with published scholarship. The Combined check mode in Plagiarism Detector runs both Internet and SciPap searches simultaneously, ensuring that submissions are compared against the broadest possible range of sources — from web pages and news articles to peer-reviewed journals and academic papers.
When a plagiarism case reaches an academic integrity committee or disciplinary board, the quality and professionalism of the evidence matters. Plagiarism Detector's Branded Originality Reports feature allows universities to generate reports that carry the institution's name and branding, giving them an official appearance suitable for formal proceedings.
These reports include detailed source matching, similarity percentages, highlighted passages, and AI content detection results — all presented in a professional format that academic integrity officers can use with confidence. The branded approach reinforces that the institution takes originality seriously and uses professional-grade tools to enforce its standards.
Download a free demo or purchase a license to start checking for plagiarism and AI-generated content.
Deploying plagiarism detection across an entire university requires a licensing model that works at scale. Plagiarism Detector offers volume licensing options for institutions that need to equip multiple departments, labs, or faculty members. Organizational licenses include multi-install permissions, allowing the software to be deployed across as many workstations as the license covers.
The one-time payment model means institutions avoid the recurring per-student or per-document fees that make cloud-based solutions increasingly expensive as usage grows. With Plagiarism Detector, costs are predictable and fixed. Universities can also request custom contracts tailored to their specific deployment requirements, including multi-year agreements and department-specific configurations.
Plagiarism Detector is designed to fit into the workflows that universities already use. Faculty members can check documents individually or use Folder Watch batch processing to scan entire class submissions at once. The software supports 12+ file formats (DOC, DOCX, PDF, RTF, PPT, PPTX, TXT, ODT, HTML), covering every format commonly used in academic submissions.
The Microsoft Office add-ins for Word and PowerPoint integrate directly into the tools faculty use every day. The desktop-based architecture means no integration with LMS systems is required — faculty simply check documents on their workstations. For institutions that need AI content detection, the built-in detector with 0.98 sensitivity identifies text generated by ChatGPT, Gemini, HuggingChat, and other models as part of every scan.
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