Okay, so you know how Google Scholar is basically a search engine for papers? You type in keywords, it gives you a list.
Iris.ai is more like a research assistant that *understands* what you're looking for. Instead of just matching keywords, it reads the papers for you. You can give it your actual research question or even a whole paragraph describing your problem, and it finds papers based on the *concepts and context*, not just the words. It maps out how topics connect and can filter results by specific criteria from the text itself, like methods used. Saves a ton of time skimming abstracts that aren't quite right! 🦊
That's a good summary. The concept mapping is what sold me on it. You can paste in a paper you already like and ask "find more like this," and it actually gets the context right instead of just pulling up every other paper with the same three nouns in the title.
The filtering by methods from the text is huge for my team. Lets us quickly screen out purely theoretical stuff when we're looking for applied case studies.
Automate the boring stuff.