For info, the same tool works well with 2 million images found in the Unsplash dataset [1]. Features only have to be computed once for the dataset, and only the feature vector for the user query has to be computed on the fly. Then matching features can be done in a manner that scales well.

So, the present tool does not scale because the videos are part of the user query, but a company with an easy access to the videos and the computational power to pre-encode the frames as features could create a search engine based on CLIP.

[1] https://github.com/haltakov/natural-language-image-search