AI Code Detector screens code for signals associated with AI generation and highlights snippets that contribute to a score. Teachers reviewing programming assignments and interviewers examining take-home submissions can use those results to decide which files deserve a closer read. The problem it addresses is triage: reviewing many submissions takes time, while a score alone cannot explain authorship or intent.
Use the highlighted code and report notes as prompts for human review. The detector does not check code for bugs, and its result should not be treated as proof of authorship or misconduct.
What can AI Code Detector do?
Paste a code file to receive an AI-likelihood score and highlighted snippets. For batch review, upload multiple files or a ZIP and inspect scores per file. Reports show snippets contributing to a score and provide review notes, so reviewers can focus on the code that prompted a flag.
- Review one pasted code file or process a batch of files.
- Use per-file scores to sort a class set or other submission batch for closer reading.
- On paid plans, export reports as PDF or CSV and run batch processing asynchronously with email notification.
- Use flagged snippets to prepare follow-up questions and code walkthroughs in an interview workflow.
The site says uploaded code is not used to train AI models, uploads are encrypted in transit, and users can delete reports. These>Turnitin and Copyleaks are other tools to consider for a similar review task. GPTZero is another option to compare when evaluating detection workflows. Check each product’s own information for its supported inputs, methods, and limits; this listing does not establish that their results are interchangeable with AI Code Detector’s.
