Endor Labs’ Stiefel said Python is only the beginning. “Our model is introduce one language — in this case, we prioritize Python because of its dominance in the ecosystem — but then continue to extend it to other languages. Especially in the enterprise space, we tend to see a lot more Java, where in smaller shops, we tend to see adopting Rust and other newer languages more often. We support all those different customers.”
Jason Andersen, VP and principal analyst at Moor Insights & Strategies, is excited about this announcement, and pointed to AI management and governance as a big issue in 2025. “What Endor has here is very helpful since it can detect and enforce policies,” he said. “However, this is not a trivial task with over a million models out there. I think that Endor’s scoring system is a good way to go, as we are still early in the market. Different companies may have different appetites for risk or will work to identify and mitigate business-critical models that may not be high-scoring.”
Not yet a complete solution
However, noted Thomas Randall, director of AI market research at Info-Tech Research Group, the new tool is not yet a complete solution. “Potential users should be aware of the limitations of Endor Labs’ AI Model Discovery tool (as with all software composition analysis tools on the market),” he said. Since the tool is currently limited to Python, he recommends that companies use it as part of a broader software composition analysis program, which also includes keeping records of the open-source models and datasets in use, including URLs, authors, and repositories, regularly auditing AI systems to mitigate risks from malicious or insecure components, and developing custom scripts to scan for common open source signatures, copyright notices, or comments in model files.