Codespy AI is an AI code detector for source code. It is built to pinpoint where AI is most likely present in a codebase and to help reviewers focus on code that may need a closer look before it is shipped or reviewed. The page describes it as a complete solution for professional firms and as a platform for managers, teams, and software managers who want to develop guardrails and processes around AI-assisted coding.
Its main function is to highlight AI-generated source code and present a visual AI-likelihood report. The service says users can paste a sample for a free instant scan, view an instant heatmap, and get reports for JavaScript, Python, Java, PHP, C/C++, and C before creating an account. It also says Codespy can identify code written by Claude, ChatGPT, Gemini, and other AI models. The page states that it helps engineers identify and correct source code errors before code goes live, and it frames the product as a way to reduce security review pressure by directing attention to likely risk areas.
Codespy AI is integrated into Visual Studio Code and is also available as a plugin in ChatGPT. The page also mentions that registration is only needed once a scan limit is reached, and that anonymous scans require a captcha. Pricing is shown with a free plan that includes 10 AI scans per month, rollover of unused scans, branded reports, white-label reports, data export, and an API available for an additional fee. Paid options listed are Consultant, Small Business, and Enterprise; Enterprise includes on-premise solutions, while the product page identifies Westbourne International LLC as the product maker.
In the LLM eval & observability space, Codespy AI takes a focused approach. It focuses on identifying AI-generated code in large codebases is difficult and time-consuming for development teams. Codespy AI is a B2B product aimed at software development teams and code reviewers. There is a free tier. It ships for the web and API.
Codespy AI first shipped in 2024. Key capabilities include AI code detection, codebase scanning, and risk highlighting. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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