Google Adds Natural Language Support to Enterprise Search Tool

Cloud Search now lets users search for enterprise content scattered across databases, documents and other sources using natural language.

Google search

Google has added support for natural language processing in its Cloud Search tool for customers of its G-Suite collection of cloud-hosted productivity apps.

The new feature allows office workers to use intuitive, natural language commands to search for documents, files and other content in their organizations.

Users can type in simple queries like "Docs shared by Mary" or "what docs need my attention" and have Cloud Search pull up so-called answer cards containing the relevant information, G Suite Engineer Albert Puig said on Google's The Keyword blog Sept. 19.

Google Cloud Search, introduced in February this year, is basically a scaled-down version of Google Search released specifically for use within enterprises. The tool is designed to help workers more easily find enterprise content that might be scattered across emails, databases, documents, spreadsheets, forms, slides, pictures and internal websites.

The need for such internal search capabilities has increased in recent years with corporate data getting scattered across on-premises, cloud and hybrid environments. The average knowledge worker in fact spends up to 20 percent of their workweek looking for and consolidating information needed for their jobs, Google had noted when it launched the tool earlier this year.

Google has described Cloud Search as using machine-learning techniques to improve its search capabilities and also to provide more tailored search experiences for users. For instance, Cloud Search can help users stay on top of their work by using information from Calendar and other apps to suggest files that might need immediate attention or to serve up information needed for an upcoming meeting.

Cloud Search also can help users search through their company directory for specific people, get contact details, and see if others might be attending the same events or sharing the same files, Google has noted.

"Today, we’re making it possible to use natural language processing (NLP) technology in Cloud Search so you can track down information—like documents, presentations or meeting details—fast," Puig said.

Research from analyst firm Gartner has shown that some 30 percent of all search queries for enterprise data start with a "who" "what," "when" or "how," he noted. The NLP capability now makes it easier for enterprise users to conduct searches using such terms.

Many other vendors of enterprise search tools have also begun integrating artificial intelligence (AI)-driven cognitive search features into their products in a manner similar to what Google is attempting to do with Cloud Search.

"Old keyword-based enterprise search engines of the past are obsolete," Forrester Research analyst Mike Gualtierihad noted in a blog this June. "Cognitive search is the new generation of enterprise search that uses artificial intelligence (AI) to return results that are more relevant to the user or embedded in an application issuing the search query."

Forrester defines cognitive enterprise search products as those that integrate machine learning and natural language processing capabilities to "ingest, understand, organize, and query digital content from multiple data sources." The analyst firm has identified multiple vendors as leaders in this space, including Coveo, Attivio, Hewlett Packard Enterprise (HPE), IBM and Squirro.

Google Cloud Search is currently available globally for enterprises using the G Suite Enterprise and G Suite Business editions. Google has said it will add more features to Cloud Search in coming months. That includes integration with third-party applications so enterprise users will be able to search for and find information within G Suite as well as other application environments, the company has noted.

Jaikumar Vijayan

Jaikumar Vijayan

Vijayan is an award-winning independent journalist and tech content creation specialist covering data security and privacy, business intelligence, big data and data analytics.