to learn about extracting this text here in a second. Now, if we were to try a simple PDF parser for a PDF like this that includes um a table here, it has an image, there's captions, and there's regular sections of text, well, we might get an answer like this here on the right in markdown. You know, this might be very fast and cheap to run even on CPU, but the issue is is that a lot of this text has been truncated, has been merged, and isn't decipherable even by me as a human. And if I sent this to a model, I don't think I could trust that the model could extract specifics from, say for example, this table. Because the table has been kind of just spit out linearly, and this information isn't fit for most use cases where I need to ask questions or have an agent do validation and extraction on this source data. So, this isn't going to cut it, right? There's undesired page headers, we don't understand the table, and where's the content from the image, right? It's not