Codequiry: inspect source-code similarity and AI-detection signals with matched evidence

Codequiry checks programming submissions for similarities with peer work and material found online. It also offers AI-written-code detection. These are distinct signals: a matched passage can point to a source for inspection, while an AI-detection score describes the tool's assessment of a pattern.

Compare submissions and inspect the match

The publisher describes uploading submissions, selecting their language and running peer, database or web checks. Results include highlighted sections and side-by-side code comparisons, with direct source URLs when the match comes from the web.

Codequiry also presents cluster graphs and match tables for examining a group of submissions. Its structural-analysis engines are intended to detect similarities despite changes such as renamed variables or reordered code. The useful review is the specific matched structure and its context, not the headline similarity percentage alone.

Treat AI detection as an investigation signal

The site lists a dedicated AI-code detector alongside its plagiarism checks. It advertises detection and false-flag rates, but the captured product page does not establish independent performance on your assignments, languages or student population. Those claims should not be substituted for evidence about a particular student's work.

Before taking action, examine the highlighted code, assignment constraints and explanations from the author. Starter templates and permitted collaboration can affect how a match should be interpreted. Codequiry describes recognizing base code, but users should verify that the assignment's shared material is handled as intended.

Fit the check to the course workflow

The publisher describes several engines, including MOSS, Dolos, JPlag and its own Hexagram and Zeus tools, with some engine access depending on the plan. It also lists a REST API, webhooks and MCP integration for connecting scans to other workflows.

A trial on an assignment with known examples can show whether its reports provide useful evidence for your course. Review submission handling and retention before uploading student work, then check the current plan limits and engine availability. Codequiry itself says users make the final call. A report can organize an investigation; it cannot replace the institution's policy or a fair review of the actual evidence.