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Codequiry is a source code plagiarism and AI-detection platform built for one purpose: making sure the code that earns the grade is actually the student's own work.
1. What Codequiry Is
Codequiry checks programming assignments against peer submissions, the wider web (including GitHub and Stack Overflow), and for AI-generated code. Instructors and engineering teams get clear similarity scores, side-by-side match evidence and AI detection results, all from one platform.
The platform supports 65+ programming languages, processes hundreds of submissions in minutes, and integrates with learning management systems through LTI, as well as an API, CLI and MCP servers for custom workflows.
2. Why We Built It
Like many computer science instructors, we watched code plagiarism slip through the cracks. Existing tools were expensive, slow, or simply couldn't keep up with the volume of assignments a modern class produces. Worse, they only compared students against each other. The moment code came from the web, or from an AI model, they saw nothing.
That gap matters. When cheating goes undetected, honest students are penalised, grades stop meaning anything, and instructors lose trust in their own results. We built Codequiry to close that gap, to make authenticity the default and give educators proof they can stand behind.
We started small, working alongside a handful of instructors and teams to learn what they actually needed. Today Codequiry is trusted by universities and engineering teams worldwide, and we keep sharpening it with every check that runs through the platform.
3. How Detection Works
Authenticity has more than one enemy, so Codequiry checks for all of them at once. Every submission passes through three independent layers of analysis:
3.1. Peer and historical detection
Compares each submission against everyone else in the class, and against past semesters, to catch shared, reused or resubmitted code.
3.2. Web and source scanning
Scans across the open web, including GitHub, Stack Overflow, tutorials and forums, to surface copying that student-to-student tools miss entirely.
3.3. AI-generated code detection
Flags code that looks machine-written, from tools like ChatGPT, GitHub Copilot, Claude and Gemini, so AI submissions don't slip past as original work.
Behind every check, 20+ engines analyse the structure and logic of the code rather than just matching text, so renamed variables and reshuffled lines don't fool it. Instructors see exactly where matches occur and how strong they are, with the evidence to make a fair, defensible call.
4. Why Codequiry
Plenty of tools claim to catch plagiarism. Codequiry is built to catch what the others can't, and to make the answer clear enough to act on.
- Coverage nothing else matches. Peer, web and AI-generated code detection in one platform. Most tools do one; Codequiry does all three on every submission.
- Understands code, not just text. 20+ engines analyse logic and structure, so renamed variables, reordered functions and cosmetic edits don't hide copied work.
- Built for real class sizes. Hundreds of submissions processed in minutes, not hours. A modern MOSS alternative that keeps up with how CS courses actually run.
- Evidence you can defend. Side-by-side matches and clear similarity scores give instructors the proof they need for a fair, transparent integrity case.
5. Language Support
Codequiry works with most programming languages taught in computer science courses, including Python, Java, C/C++, JavaScript, C#, PHP, Ruby, Go, Swift, Kotlin, Rust, MATLAB, R, SQL and many others. Language support is continuously expanding.
6. The Challenge We're Solving
Computer science instructors have always struggled with code plagiarism. With so much code available online and large class sizes, it's nearly impossible to manually check every assignment for copied work.
Traditional tools like MOSS were designed for smaller classes and don't handle modern programming practices well, as our study of what MOSS misses shows. Many are also difficult to use or have long waiting times.
We wanted to build something that works better for today's computer science education environment.
7. What Instructors Say
"I can finally focus on teaching instead of spending hours trying to figure out if students copied their code."
"The web scanning catches things I would never find on my own. It's really opened my eyes to how much copying happens."
"Setup was straightforward and the results are easy to understand. My TAs can use it without any training."
8. Get Started
If you're an instructor dealing with code plagiarism in your classes, you can see how the system works for yourself.
Get started or visit the Help page if you have questions first.