System's functionality
/ 01
StrikePlagiarism.com is a multi-database plagiarism detection system that searches open internet sources, university databases, and publisher repositories.
The system performs large-scale similarity verification across:
- Billions of indexed web pages
- Scientific journals and academic repositories
- University internal databases
- Publishing house collections
- Partner institutional databases
StrikePlagiarism.com supports 200+ languages and enables cross-source plagiarism similarity detection at institutional scale.
All internal repositories operate under GDPR-compliant, EU-based secure infrastructure.
/ 02
StrikePlagiarism.com is an AI-generated content detection system designed to identify AI-written and AI-assisted text in academic, research, and editorial documents.
The AI detection module is fully integrated into the Similarity Report and provides structured, fragment-level probability analysis.
Key capabilities:
- 98%+ detection accuracy
- Less than 1% false-positive rate
- Multi-language AI detection (100+ languages)
- Detection of AI-generated and AI-assisted writing
- Dedicated AI Content Report
- Five probability ranges with standardized color coding.
- Extended text blocks are highlighted to identify large - AI-generated segments, while darker shades indicate higher probability of AI authorship.
The system detects content generated by leading AI models, including GPT-based systems (such as ChatGPT), Claude, Gemini, and other advanced large language models.
AI detection is continuously updated to address new model versions and evolving generative AI architectures.
If you want to learn more, click here.
/ 03
StrikePlagiarism.com integrates with leading Learning Management Systems (LMS) globally, enabling seamless deployment within institutional digital ecosystems.
Supported platforms include: Moodle, Canvas, Blackboard, Brightspace, Schoology
Integration architecture includes:
LTI 1.3 compliance
REST API connectivity
Single Sign-On (SSO)
Automated submission processing
AI-generated content detection within LMS workflows
Structured similarity reporting inside assignment modules
The platform ensures scalable enterprise deployment across universities, research institutions, and national education systems.
/ 04
Grammatical and spelling errors often appear in student and even scientific papers. They are often ignored, however, errors related to grammar, spelling, style, punctuation, and so on are one of the main criteria for the quality of written work.
In addition, grammatical errors have become increasingly used by some students to bypass the anti-plagiarism system, for example, the author adds some kind of error to the entire text to break the order of words and prevent the search for similarities.
To save the teacher's time in searching for the above mentioned errors, as well as to prevent attempts at manipulation, we have created a module for searching for grammatical, spelling and other types of errors.
Advantages of the module:
- Supports more than 30 languages,
- Displays hints for corrections,
- Simple navigation through the text,
- Displays errors by category, where each category has its own color code.
If you want to learn more, click here.
/ 05
System recognizes manipulations with text fragments in the form of:
- changing the order of words,
- adding or removing words,
- replacing words with synonyms,
- being translated,
As a result, the system will underline the âchangedâ fragments and highlight these fragments.
This function serves the purpose of clarifying whether a fragment was accurately paraphrased, or even if there was an attempt to bypass the system and intentionally hide the copied fragment.
Additionally, the system uses the SmartMarks feature to identify subtle alterations in text, such as changing word sequences, adding or omitting terms, and using synonyms to rephrase content. These alterations are displayed with lighter shading to indicate potential paraphrasing manipulations.
When hovering over highlighted text, a comparison with the original source is shown, making it easier to assess whether the changes are intentional attempts to obscure copied material.
This functionality is particularly useful for identifying fragments that maintain conceptual similarity while avoiding direct duplication, ensuring a thorough evaluation of document originality.
/ 06
The translation plagiarism search algorithm allows you to find similarities in the translated text. The system supports more than 100 languages, including English, Spanish, German, French, Arabic and even Chinese. Having loaded the work into the systems, you can choose the combination you need, after which the system will show which fragments were found as similar in the translated text.
To enable this feature, the user simply selects the desired language combination while uploading the document. The system translates the documentâs content and compares it against databases, including the RefBooks database, partner institutions' databases, and internet resources. Fragments identified as similar in the translated text are highlighted, ensuring thorough and accurate verification.
The search of translated similarity module was created with the support of a machine learning algorithm, ensuring adaptive and precise analysis. The translated fragments and their original counterparts can be viewed side-by-side in the interactive similarity report for detailed assessment.
Click here to watch the video presentation.
/ 07
Management of Assignments is one of the most time-consuming processes. A user-friendly and an intuitive module of Assignment management that allows instructors in a few simple steps create, update, close Assignment, monitor deadlines and enroll students. To simplify a process of evaluation we have developed a Peer-Review module, that allows teachers and students collaborate in evaluation process. Peer-Review is available for any type of client.
The advantages of StrikePlagiarism.comâs peer-review system:
For Instructors:
- Time Efficiency: Peer feedback reduces the instructorâs workload, allowing for more efficient feedback distribution.
- Active Learning: Students engage more deeply with the material through reviewing peers' work.
- Encouraging Accountability: Knowing their peers will assess their work motivates students to invest greater effort.
- Customizable Assignments: Instructors can set specific criteria for peer reviews to align with learning objectives.
- Trackable Process: StrikePlagiarism.com's platform enables instructors to monitor participation and quality of feedback.
- Promotes Collaboration: The peer-review process fosters a collaborative learning environment.
/ 08
The RefBooks is Plagiat.pl's scientific database containing millions of PhD theses, publications, student papers, scientific journals and other types of documents in over 30 languages, including English, French, Portuguese, German, Spanish, Dutch, Turkish, Arabic, Ukrainian and etc. This database includes documents published also in Scopus, Web of Science, Springer, EBSCO etc. The database is used by universities, publishers and other institutions for plagiarism analysis.
Additionally, RefBooks integrates texts from trusted open-access platforms such as Arxiv.org, Paperity.com, and Termedia.pl, ensuring a diverse range of academic and professional disciplines. Through its database exchange program, it includes contributions from partner organizations, allowing institutions to broaden the scope of their checks. The system also offers advanced tools, such as AI-generated content detection, translation similarity analysis in over 100 language combinations, and automated cross-checking functionality for documents within assignments.
These features make RefBooks a comprehensive solution for identifying textual similarities, ensuring academic integrity, and addressing potential manipulation techniques such as altered characters, microspaces, and paraphrased content.
/ 09
Our Domestic Search Module (DSM) can be installed on the server of the university, which allows you to search for similarities within your database. This is done in a simple way. Our system sends to the Module the text that your user has uploaded on his account in our system. The module searches for similarities and sends metadata back to the system for the fragment that was found in the university database. This metadata is reflected in your user's similarity report, the source is your database. The module can send us only the metadata that the university has entered into its database. This service became very popular due to GDPR and copyright restrictions.
Additionally, the DSM supports full integration with the University's existing IT infrastructure, ensuring seamless compatibility and quick deployment. The system uses advanced algorithms to identify similar fragments, and the results are presented in a detailed similarity report. The report highlights the exact locations of matching text and provides direct links to the original sources within the university's database. This enables evaluators to analyze content efficiently while maintaining the integrity and security of institutional data. Moreover, DSM can be configured to automatically update the database by indexing new documents, ensuring the system remains up-to-date with minimal manual intervention.
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Cross-check Assignments against each other while they were not yet added to the database. Find similarities in the Assignment for a group of papers whether the copying from each other took place.
This feature automatically compares all documents submitted within the same Assignment, highlighting similar fragments for easy analysis. Results are displayed in a separate section of the Similarity Report, ensuring clear identification of overlaps without influencing the similarity coefficients.
Instructors can use this tool to detect potential cases of collaboration, duplication, or copying among submissions, especially in group projects or assignments. The feature helps maintain academic integrity by providing a transparent comparison process and ensuring that originality is upheld across all submitted works.
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The system detects various forms of text manipulations, resisting copy-paste, cheating, and ghostwriting.
The similarity report highlights manipulations such as characters from another alphabet, spreads, microspaces, and white characters.
Over 50 types of manipulations are identified, including:
- Characters from Another Alphabet
Replacing Latin letters with visually similar ones from other scripts.
-Spreads and Microspaces.
- Using extended or invisible spaces to alter word structure.
- White Characters.
- Adding invisible text by coloring it white.
- Paraphrasing via SmartMarks.
- Modifying word order, sentence structure, or replacing words with synonyms.
These advanced detection capabilities ensure that the system provides a reliable and accurate assessment of document originality, even in cases where attempts at manipulation are sophisticated.
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The report includes similarity coefficients (SC1 and SC2) that measure the extent of similarity between your document and the sources. SC1 reflects smaller overlapping fragments, while SC2 indicates larger text matches.
This system simplifies similarity evaluation while ensuring transparency and accuracy. The report highlights similar fragments within the sources, including both Internet-based and Domestic Database sources.
To ensure effective analysis and prevent plagiarism, StrikePlagiarism.com utilizes advanced technology that provides precise and comprehensive comparisons with multiple sources. Our system not only identifies matches but also clearly indicates where exactly in the text the matches occur, enabling quick and accurate detection of potential originality issues.
If you want to learn more, click here.