Glean has launched Glean Chat, a generative AI-based assistant for boosting enterprise productivity

Glean, a company founded in 2019 by former Google, Microsoft, and Meta employees, has released a new generative AI-based assistant called Glean Chat, designed to boost productivity and efficiency in enterprises. Its purpose is to help employees find information quickly across an enterprise’s applications and content repositories with source citations via a conversational search interface. In this article, we’ll explore Glean Chat’s features, functionality, Glean’s infrastructure and funding, as well as the competition.

Features of Glean Chat

Glean Chat is touted as the “Power BI of unstructured data,” with its main feature being its ability to help employees find information easily and efficiently. It offers an experience very similar to OpenAI’s ChatGPT but is limited to an enterprise’s content and resource boundaries. What makes Glean Chat stand out is its ability to provide source citations, which makes it easier for employees to find the needed information. It is designed to be user-friendly, which means employees don’t have to be tech-savvy to use it.

Functionality of Glean Chat

When a user makes a natural language-based query, the company’s search technology uses APIs to check all the content and activity – including information in applications – pertaining to the query before storing it in a customer’s cloud environment. This process ensures that the query is directed to the appropriate person or team.

Layers of Glean

Glean is built on five layers consisting of infrastructure, connectors, a governance engine, the company’s knowledge graph, and an adaptive AI layer. The infrastructure layer consists of the basic hardware and software required to run Glean, while the connectors layer links Glean to the various enterprise content repositories and applications. The governance engine ensures that all the information stored on Glean is compliant with regulations and company policies. The knowledge graph captures the enterprise’s information in an organized format, allowing Glean Chat to access it more easily. Lastly, the adaptive AI layer is responsible for Glean’s generative AI capabilities.

The adaptive AI layer of Glean

The adaptive AI layer uses information from the knowledge graph and runs it through LLM embeddings for semantic understanding, as well as large language models for generative AI. It is important to note that Glean utilizes a mix of large language models, including OpenAI’s GPT-4 and transformer models from Google such as BERT. The adaptive AI layer is responsible for analyzing queries and providing relevant responses.

Competitors in the industry

Glean Chat faces an uphill task when it comes to carving out a space in the crowded generative AI market, as there are many competitors with similar offerings. Some of the competitors include OpenAI, IBM Watson, Google, and Amazon AWS. OpenAI’s GPT-3 and GPT-4 are among the most advanced language models in the market, and their capabilities are extensive.

Please provide more context to your sentence for me to understand what you’re requesting

Glean Chat will be priced on a per-seat basis and offered as a premium add-on to Glean’s core search product. The company offers enterprise-level pricing for Glean, which means that the price can vary depending on the customer’s needs.

Funds and Customers

Glean has raised about $155 million to date from investors such as Sequoia, Lightspeed, Slack Fund, General Catalyst, and Kleiner Perkins. The company claims that it already has over 100 enterprise customers, including Databricks, Vanta, Plaid, Grammarly, Okta, Samsara, Niantic, Greenhouse, Duolingo, Wealthsimple, and Confluent. With such top enterprise customers, it shows that the product has a promising future.

In conclusion, Glean Chat is an exciting and innovative product designed to provide an efficient and user-friendly conversational search interface. Its generative AI capabilities are impressive, and it stands out from competitors with its source citation feature. The pricing structure is reasonable and flexible, making it accessible to enterprises of all sizes. Glean has a bright future, and it will be interesting to see how it performs in the highly competitive generative AI market.

Explore more

How to Make Money With Lead Generation in 2026

The digital landscape has transformed into a high-stakes battlefield where businesses are no longer searching for simple contact information but are instead hunting for verified, high-intent connections amidst a sea of automated noise. If a professional spent any time online a few years ago, it was impossible to escape the constant claims from influencers that lead generation represented the ultimate

Financial AI Evolution Requires New Network Infrastructure

The silent cost of a single dropped data packet in a multi-day high-frequency AI training cluster can burn through thousands of dollars in a heartbeat, yet most banks are still running on pipes built for the era of static spreadsheets. As the industry moves through 2026, the transition of artificial intelligence from experimental side-projects to the central nervous system of

Is AI Integration Outpacing Governance in Global Finance?

The financial landscape is shifting beneath the surface as sophisticated algorithms now execute complex trades and predict market fluctuations with a speed that human analysts simply cannot match. This rapid evolution has pushed 77% of financial organizations to integrate artificial intelligence into their core operations. However, a jarring discrepancy exists, as only 14% of these firms are operating under a

How Are Cobots and AI Transforming Industrial Automation?

The rhythmic, synchronized movement of robotic arms no longer occurs behind thick plexiglass or steel mesh, as the walls once defining the factory floor have begun to disappear in favor of seamless interaction. This transition represents a $16.7 billion pivot toward collaborative intelligence, where machines are no longer isolated assets but active partners. As the industry moves into a more

BNPL Growth Challenges US Merchants With Fraud and Disputes

The meteoric rise of installment-based spending has fundamentally altered the American retail landscape, yet the very convenience that drives consumer conversion is now triggering a complex crisis of fraud and operational instability for merchants. Retailers today find themselves in a precarious position where providing the most popular payment options often means opening the door to sophisticated financial threats that bypass