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Glean launches new generative AI capabilities to enhance search and discovery across organizations

Glean new features

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Glean, a company that provides intelligent search and discovery solutions for knowledge workers, announced on Tuesday a suite of new features that use artificial intelligence (AI) to synthesize and surface relevant information from across an organization.

The features, which are based on Glean’s proprietary knowledge model, aim to improve the accuracy and security of enterprise data and content, as well as enhance the productivity and collaboration of employees, especially in remote or hybrid work environments.

One feature, AI answers, can generate a single concise answer to a natural language query, drawing from various sources of content, context and permissions within an organization. Another feature, expert detection, can identify and connect users with subject matter experts within their company, based on Glean’s analysis of content, activity and relationships.

A third feature called in-context recommendations can provide users with additional content and context related to any given asset they are working on, such as a document or a presentation.

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“We built Glean with the understanding that accuracy and security were critical to our success,” Glean CEO Arvind Jain said in an interview with VentureBeat. “Glean’s governance engine ensures that users only have access to information that they’re allowed to see based on their existing access permissions in the source systems which Glean searches. This way, our customers can be confident that all their real-time enterprise data permissions and governance rules are enforced.”

Made for the enterprise customer

Glean was founded in 2020 by Jain, a distinguished Google engineer. In May, the company announced a $100 million series C funding round, which put it at a $1 billion valuation. Glean claims to have more than 70 customers across various industries including technology, media, education and health care.

“The opportunity is huge: AI can transform the way that we work by making knowledge accessible and eliminating the time and resources spent hunting for the information that employees need to do their jobs,” Jain told VentureBeat.

He continued: “But there are significant challenges when applying AI in the enterprise, and a thoughtful approach is necessary to ensure that it’s the right information that employees receive. At Glean, we believe that accuracy, security, and referenceability are crucial in any AI tool used in the enterprise.”

Increased productivity, decreased costs

According to a report by McKinsey & Company, knowledge workers spend about 20% of their time searching for and gathering information, which amounts to a loss of $1 trillion in productivity per year. The report also found that AI can help reduce this time by 35% and increase revenue by 6%.

Glean has created a trusted knowledge model that aims to meet the accuracy, security and reference capabilities that match the needs of the enterprise. The model, which took four years to develop, is based on three pillars: company knowledge and context, permissions and data governance and full referenceability.

The model retrains deep learning language models (LLMs) on a company’s unique knowledge base and applies real-time data permissions and governance rules. It also shows the sources of each piece of information and how every response is generated. Jain said that generative AI needs to be grounded in the right search foundation to be valuable in business.

VentureBeat’s mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.


Author: Michael Nuñez
Source: Venturebeat

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