Today at AWS re:Invent in Las Vegas, the company announced a new search tool called Kendra, which provides natural language search across a variety of content repositories using machine learning.
Matt Wood, AWS VP of artificial intelligence said that the new search tool uses machine learning, but doesn’t actually require machine learning expertise of any kind. Amazon is taking care of that for customers under the hood.
You start by identifying your content repositories. This could be anything from and S3 storage repository to OneDrive to Salesforce — anywhere you store content. You can use pre-built connectors from AWS, provide your credentials, and connect to all of these different tools.
Kendra then builds an index based on the content it finds in the connected repositories, and users can begin to interact with the search tool using natural language queries. The tool understands concepts like time, so if the question is something like ‘When the IT Help Desk is open,’ the search engine understands that this is about time, checks the index and delivers the right information to the user.
The beauty of this search tool is not only that it uses machine learning, but based on simple feedback from a user, like a smiley face or sad face emoji, it can learn which answers are good and which ones require improvement, and it does this automatically for the search team.
Once you have it set up, you can drop the search on your company intranet or you can use it internally inside an applications and it behaves as you would expect a search tool to do with features like type ahead.