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

Trend Analysis: Australian Payroll Compliance Software

The Australian payroll landscape has fundamentally transitioned from a mundane back-office administrative task into a high-stakes strategic priority where manual calculation errors are no longer considered an acceptable business risk. This shift is driven by a convergence of increasingly stringent “Modern Awards,” complex Single Touch Payroll (STP) Phase 2 mandates, and aggressive regulatory oversight that collectively forces a massive migration

Trend Analysis: Automated Global Payroll Systems

The era of the back-office payroll department buried under mountains of spreadsheets and manual tax tables has officially reached its expiration date. In today’s hyper-connected global economy, businesses are no longer confined by physical borders, yet many remain tethered by the sheer complexity of international labor laws and localized compliance requirements. Automated global payroll systems have emerged as the critical

Trend Analysis: Proactive Safety in Autonomous Robotics

The era of the heavy industrial robot sequestered behind a high-voltage cage is rapidly fading into the history of manufacturing. Today, the factory floor is a landscape of constant motion where autonomous systems navigate the same corridors as human workers with an agility that was once considered science fiction. This transition represents more than a simple upgrade in hardware; it

The 2026 Shift Toward AI-Driven Autonomous Industrial Operations

The convergence of sophisticated artificial intelligence and physical manufacturing has reached a critical tipping point where human intervention is no longer the primary driver of operational success. Modern facilities have moved beyond simple automation, transitioning into integrated ecosystems that function with a degree of independence previously reserved for science fiction. This evolution represents a fundamental shift in how industrial entities

Trend Analysis: Enterprise AI Automation Trends

The integration of sophisticated algorithmic intelligence into the very fabric of corporate infrastructure has moved far beyond the initial hype cycle, solidifying itself as the primary engine for modern competitive advantage in the global economy. Organizations no longer view these technologies as experimental add-ons but rather as foundational requirements that dictate the speed and scale of their operations. This shift