Code plagiarism detection for schools, hiring and legal teams

Anywhere someone hands in code and says they wrote it, the same checks apply: compare it with the others, with the web, and for AI, and show the matching lines. Here is how different teams use them.

By the Codequiry team Updated Sep 30, 2026

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95%

A take-home test, copied from GitHub Renamed, then submitted as original work

Example

Candidate submissionlru.py

1class Cache:2 def __init__(self, size):3 self.size = size4 self.d = OrderedDict()56 def get(self, k):7 if k not in self.d:8 return -19 self.d.move_to_end(k)10 return self.d[k]

Found on GitHublru_cache.py

1class LRUCache:2 def __init__(self, capacity):3 self.capacity = capacity4 self.cache = OrderedDict()56 def get(self, key):7 if key not in self.cache:8 return -19 self.cache.move_to_end(key)10 return self.cache[key]

Web sources: 1 matchOther candidates: no matchAI detection: not flagged

The same check works outside a classroom. Here a take-home answer turns out to be a public solution with the names changed (highlighted).

Used in programming courses at

Universities and schools

The core use. Instructors check each assignment against the class, earlier terms, the web and AI, with starter code left out, and take the side-by-side evidence to a student or an integrity office.

For individual teachers and for whole departments
Canvas and other LMS integrations
Window, a student IDE that records pastes as students write

Bootcamps and online courses

Large cohorts, the same projects every intake, and solutions that circulate between them. Checking each cohort against earlier ones catches the project handed down from a graduate, and the API lets a learning platform run checks on every submission automatically.

Technical hiring

Take-home tests are only useful if the candidate wrote the answer. Each submission is checked against other candidates, public solutions on GitHub and the web, and for AI-written code, as in the example above.

Detecting AI in coding interviews and take-home tests
Code authenticity checks for work samples and portfolios

Contests and hackathons

Entries are compared with each other to find shared solutions between teams, and against the web for code that was written before the event. Upload the entries in one batch, or send them through the API as they come in.

Software and legal teams

Before you ship, merge or acquire code, it helps to know where it came from. Checking a codebase against GitHub, Software Heritage and the web shows code that was copied from public projects, with a link to each source so its license can be checked.

Try it on your own code

Upload a batch and see matches against each other, the web and AI.

Start free trial

1-day free trial

One set of checks

Each other

Every submission against every other, and against earlier batches, by structure.

The web

GitHub, Gists, Stack Overflow, Software Heritage and the indexed web.

AI-written code

ChatGPT, Claude, Gemini and Copilot, with the reasons shown.

65+ languages

From Python, Java and C++ to Go, Rust, SQL and Jupyter notebooks.

Who can use it

Codequiry is for educators and organizations. Students do not hold accounts; they hand in work through an instructor. Commercial use is authorized on the Scale plan. The details are in the acceptable use policy, and plans are on the pricing page.

Frequently asked questions

Who is Codequiry for?

Anyone who needs to know whether submitted code is original: universities and schools, bootcamps and online courses, hiring teams running take-home tests, contest organizers, and software and legal teams checking where code came from.

Can companies use Codequiry commercially?

Yes. Commercial use is authorized on the Scale plan. Other plans cover education and internal use.

Can students sign up themselves?

No. Codequiry is for instructors and organizations. Students hand in work through their instructor, an LMS, or Window, and do not need accounts.

Can I check a candidate's take-home test?

Yes. The submission is checked against other candidates, GitHub, Stack Overflow and the web, and for AI-written code, with the matched lines shown side by side.

Can it run inside our own platform?

Yes. A REST API with SDKs, a command-line client and an MCP server let you run checks from your own systems and read the results back.

Check the code you were handed

Compare it with the others, the web and AI, with the matching lines side by side.