Chennai, NFAPost: Amazon Web Services (AWS) has announced the general availability of Amazon Kendra, an enterprise search service powered by machine learning. Amazon Kendra uses machine learning to enable organisations to 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. For example, businesses can use Amazon Kendra to search internal documents spread across portals and wikis, research organisations can create a searchable archive of experiments and notes, and contact centers can use Amazon Kendra to find the right answer to customer questions across the complete library of support documentation. Amazon Kendra requires no machine learning expertise and can be set up completely within the AWS Management Console.
Amazon Kendra reinvents enterprise search by allowing end-users to search across multiple silos of data using real questions 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. Because natural language understanding is at the core of Amazon Kendra’s search engine, employees can run their searches using natural language.
For 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, the company said in a release.
“Our customers often tell us that search in their organisations is difficult to implement, slows down productivity, and frequently doesn’t work because their data is scattered across many silos in many formats. Using keywords is also counterintuitive, and the results returned often require scanning through many irrelevant links and documents to find useful information,” said Swami Sivasubramanian, Vice President, Amazon Machine Learning, Amazon Web Services.
“Today, we’re excited to make Amazon Kendra available to our customers and enable them to empower their employees with highly accurate, machine learning-powered enterprise search, which makes it easier for them to find the answers they seek across the full wealth of an organisation’s data,” he added.
Amazon Kendra provides a wide range of native cloud and on-premises connectors to popular data sources such as SharePoint, OneDrive, Salesforce, ServiceNow, Amazon Simple Storage Service, and relational databases. Amazon Kendra also helps to ensure that search results adhere to existing document access policies by scanning permissions on documents, so that search results only contain documents for which the user has permission to access. PwC is a network of firms in 157 countries with over 276,000 people.
“PwC designed RegRanger for regulated industries, providing access to regulatory and compliance information as well as proprietary PwC insights,” said Chris Curran, Partner and CTO of PwC’s New Ventures organization.
“Our goal is to help our customers get to the answers they need faster – even when the right answers may be buried within documents over 100 pages long – so they can understand regulatory information faster and make decisions more quickly and confidently. As an early adopter of Amazon Kendra, PwC is now developing and testing enhanced search capabilities to be implemented in our next version of RegRanger,” he added.
