Very cool piece of tech, I would suggest putting C on the priority list and then Java. Mainly because Unis and Colleges use one of them or both, so that would be a good use case
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I’m Henry, cofounder and CTO at Span (https://span.app/). Today we’re launching AI Code Detector, an AI code detection tool you can try in your browser.
The explosion of AI generated code has created some weird problems for engineering orgs. Tools like Cursor and Copilot are used by virtually every org on the planet – but each codegen tool has its own idiosyncratic way of reporting usage. Some don’t report usage at all.
Our view is that token spend will start competing with payroll spend as AI becomes more deeply ingrained in how we build software, so understanding how to drive proficiency, improve ROI, and allocate resources relating to AI tools will become at least as important as parallel processes on the talent side.
Getting true visibility into AI-generated code is incredibly difficult. And yet it’s the number one thing customers ask us for.
So we built a new approach from the ground up.
Our AI Code Detector is powered by span-detect-1, a state-of-the-art model trained on millions of AI- and human-written code samples. It detects AI-generated code with 95% accuracy, and ties it to specific lines shipped into production. Within the Span platform, it’ll give teams a clear view into AI’s real impact on velocity, quality, and ROI.
It does have some limitations. Most notably, it only works for TypeScript and Python code. We are adding support for more languages: Java, Ruby, and C# are next. Its accuracy is around 95% today, and we’re working on improving that, too.
If you’d like to take it for a spin, you can run a code snippet here (https://code-detector.ai/) and get results in about five seconds. We also have a more narrative-driven microsite (https://www.span.app/detector) that my marketing team says I have to share.
Would love your thoughts, both on the tool itself and your own experiences. I’ll be hanging out in the comments to answer questions, too.
Edit: since you mentioned universities, are you thinking about AI detection for student work, e.g. like a plagiarism checker? Just curious.
When it comes to the unis, I was thinking of both AI detection for student work. I mean like plagiarism checkers are common nowadays and the systems I know of just forces every student to upload their work and it compares similarities, one even broke it down to AST level (I think?) for detection so it didn't matter if the students renamed the variables.
But for ai detection, it's still a new area. From what I know, unis just make the students check a field when uploading their work as a contract that they never used ai tools and all is their own work, and after that is up to the teacher to go through their code and see if it looks odd or something. Some even have the students just present their code and make them explain what they did. But as of a tool for ai detection is pretty new, as far as I know.