In short - it means learning what information users need to see at this moment, based on the item they are currently working on, and proactively presenting it to them onscreen in real-time.
Keyword search is a technology built for the internet, where it can rely on lots of clickthrough data. That technology is not suitable for the enterprise, where such data is not available. That is why workers spend between 20-40% of their time searching for information, and still 49% of enterprise workers report they have trouble finding the information they need!
This problem isn't going away, in fact, with the exponential growth of enterprise data, it's getting worse. That is why xFind developed the first fully context-based search engine. xFind learns what information the users need in real time, from the entire item they are working on, all text and metadata, and presenting it to them onscreen. Our solution achieves much higher levels of retrieval relevance (up to 90%), much faster (3 day integration).
A test comparing the ability to retrieve the correct tagged answer to a Stack Overflow question, showed xFind achieves nearly 5x the accuracy of major enterprise search solutions, on default settings.
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.