Amazon Web Services (AWS) has announced the general availability of Amazon Kendra, an easy-to-use enterprise search service powered by machine learning. With just a few clicks, organizations can now index all of their internal data sources, make that data searchable, and allow users to get precise answers to natural language queries.
When users ask a question, Amazon Kendra uses finely tuned machine learning algorithms to understand the context and return the most relevant results, whether that be a precise answer or an entire document.
As an example, an employee can ask a specific question like “when does the IT help desk open?” and Amazon Kendra will give them a specific answer like “9:30 AM,” and highlight the passage in the source document where it found the answer, along with links back to the IT ticketing portal and other relevant sites. Amazon Kendra is also optimized to understand complex language from multiple domains, including IT (e.g. “How do I set up my VPN?”), healthcare and life sciences (e.g. “What is the genetic marker for ALS?”), and insurance (e.g. “How long does it take for policy changes to go into effect?”).
Amazon Kendra requires no machine learning expertise and can be set up completely within the AWS Management Console.
As the company puts it, Amazon Kendra reinvents enterprise search by allowing end-users to search across multiple silos of data using real questions (not just keywords) and leverages machine learning models under the hood to understand the content of documents and the relationships between them to deliver the precise answers they seek (instead of a random list of links).
Currently, Amazon Kendra supports industry-specific language from IT, healthcare, and insurance, plus energy, industrial, financial services, legal, media and entertainment, travel and hospitality, human resources, news, telecommunications, mining, food and beverage, and automotive.
AWS has plans to include additional industry support coming in the second half of this year.