laɪbnɪts has a broad range of uses but there are two groups of people for whom laɪbnɪts is particularly compelling: company knowledge management and researchers.

Company Knowledge Management

Companies waste vast amounts of money looking up the same information multiple times. laɪbnɪts can help reduce this waste by making research available to anyone who needs to access it. Not only that, laɪbnɪts does it all in the background, with no effort required from the people actually doing the research. Knowledge management for free!

The second part of the Knowledge Management capabilities is a notification system which alerts users to existing documents that are similar to their current research. These notifications can be customised to show, for example, who did the original research so you can contact that user or users. It also gives managers and knowledge management staff an overview of areas of active research so they can coordinate disparate groups to work in a more cohesive manner.

But it doesn't just end there; users can annotate documents and tag them. Tags will also auto-complete (tags are updated in real time) reducing the likelihood of a fragmented folksonomy.


As anyone who has done any research will know it isn't a linear process. A common method is to cast the net wide as you try to validate the initial idea and, as you start to refine that original idea, you focus on a few documents. The problem becomes how to find those “few documents” in amongst everything from your initial search.

This is where laɪbnɪts really shines. All those documents from your initial search have been carefully collected, saved and processed in such a way that it becomes easy to find them again using the sophisticated search engine which is at the very core of laɪbnɪts.

Furthermore you can search for documents that are similar to an existing document. This isn't based on keywords but uses natural language processing to determine if the documents are similar. This is incredibly useful if one of your search terms is a common word or when you're having difficulty determining which keywords to use.