We’re pleased to announce that we’re releasing our first free integration — KvasirA for Slack!
KvasirA for Slack started life as an internal tool, allowing our team to quickly make and demonstrate queries to one another without having to use another application. The benefits of being able to search for relevant content and share it instantly was a big help when developing the technology and we think it can provide value to others.
Rather than just sending a team member a link to a webpage, you can contextualise it with relevant articles from Wikipedia, academic papers, patents and more. This helps everyone get a better grip on the content itself and where to go for further exploration.
KvasirA for Slack adds an extra
/kvasira slash command into your workspace that lets you make queries to our curated set of document libraries. Queries take the form of webpages. KvasirA extracts the content of the webpage and returns a set of links to semantically similar documents in a given document library. To successfully extract text from the webpage, the page must be public (i.e. you can’t query pages protected by passwords).
We also support document libraries in languages other than English and for now in Slack we offer versions of Wikipedia in Arabic, Hindi and Spanish. Queries to these libraries don’t even need to be in the same language as the library - you can for example query the Arabic Wikipedia with English documents! In the near future users will be able to create their own private document libraries in over 10 different languages.
Our plans for the future are not to just for our users to consume document libraries that we’ve indexed but also to be able to host their own. Users will be able to upload their own documents and manage their indexes via our web app or an intuitive API. The entire machine learning pipeline will be managed and hosted by us — no need to do any ML work to get started with semantic search!
To try KvasirA for Slack out, click the ‘Add to Slack’ button below and follow the instructions in the next window.
You can email us at email@example.com We’d love to hear any feedback or feature requests you may have about KvasirA for Slack or the KvasirA technology itself.