Recently Amazon announced the general availability of its enterprise search service Kendra on AWS. With the GA release of Amazon Kendra, the public cloud provider added a few new specialized features and improved service accuracy.
A preview version of Amazon Kendra was launched during re:Invent in December last year, providing customers with an enterprise search service that heavily uses machine learning. During the preview phase, Amazon gathered feedback from customers using the service and added a couple of new features and optimization based on that feedback with the GA release. The service now has:
- New connectors for Salesforce, ServiceNow and Microsoft’s OneDrive cloud storage service.
- Improved vocabulary with additional domain-specific terms across eight more fields: Automotive, Health, HR, Legal, Media and Entertainment, News, Telecom, Travel and Leisure.
- Faster indexing, and improved accuracy.
- New scaling options for the Enterprise Edition, as well as a newly introduced Developer Edition.
With Amazon Kendra, customers can index structured and unstructured data stored in different backends, such as file systems, applications, Intranet, and relational databases. The service is optimized to understand complex languages from domains such as healthcare, IT, and many others. Moreover, the multi-domain expertise of the service provides better search results. Furthermore, developers can explicitly tune the relevance of results, using criteria such as authoritative data sources or document freshness.
Julien Simon, artificial intelligence and machine learning evangelist for EMEA at AWS, wrote in a blog post on the GA release:
Kendra search can be quickly deployed to any application (search page, chat apps, chatbots, etc.) via the code samples available in the AWS console, or via APIs. Customers can be up and running with state the art semantic search from Kendra in minutes.
Customers can set up Amazon Kendra easily through the AWS Console, create a new index, wait approximately 30 minutes or so, add and configure the data source, subsequently synchronize, and then test by running queries. Note that customers can also leverage Kendra via the AWS SDKs, and the AWS CLI.
For enterprises, it makes sense to use a search service as they often have massive amounts of data that is mostly underused; a Forrester survey indicates that between 60% and 73% of all data within corporations is never analyzed for insights. Currently, Amazon is not the only cloud vendor that offers a managed search service on its platform. Microsoft provides customers with Azure Cognitive Search as part of its Azure platform, and Google offers Cloud Search, available on its cloud platform. Furthermore, there is an alternative, according to a respondent on a Reddit thread:
Haystack is an OSS alternative to implement a scalable semantic search pipeline for enterprises using the latest NLP transformer models like BERT and RoBERTa.
One of the AWS customers using Kendra is 3M, and their technical director of the Corporate Research Systems Lab David Frazee said in an AWS press release of the service:
Finding the right information is often exhausting, time-consuming, and sometimes incomplete. With Amazon Kendra, our scientists find the information they need quickly and accurately using natural language queries. With Kendra, our engineers and researchers are enthusiastic about the ability to quickly find information which will enable them to innovate faster, collaborate more effectively, and accelerate the ongoing stream of unique products for our customers.
Amazon Kendra is currently available in the Northern Virginia, Oregon, and Ireland AWS regions. Customers can choose between enterprise or developer edition, which has similar features; however, the developer edition is limited in the number of queries per day, has no scaling options, and is available only in a single availability zone. And finally, the pricing details of the service are available on the pricing page.