The competition in the realm of enterprise AI is intensifying. Major players like Microsoft are integrating Copilot into their Office suite, while Google is embedding Gemini into Workspace. Meanwhile, OpenAI and Anthropic are directly targeting enterprises, and virtually every SaaS provider is now including an AI assistant in their offerings.
In this dynamic landscape, Glean is focusing on a less visible aspect: establishing itself as the intelligence layer that operates beneath the user interface.
Founded seven years ago with the ambition to become the "Google for enterprise," Glean has evolved into an AI-driven search platform designed to index and navigate a company's suite of SaaS tools, including Slack, Jira, Google Drive, and Salesforce. The company's current direction emphasizes connecting various AI models with enterprise systems rather than just enhancing chatbot capabilities.
"The initial layer we created--a robust search tool--required us to gain deep insights into how people work and their preferences," Jain explained in a recent interview. "This understanding is now essential for developing high-quality AI agents."
While large language models (LLMs) possess significant power, Jain notes they lack specificity. "These AI models do not comprehend the intricacies of your business. They are unaware of your personnel, the nature of your work, or the products you develop. Therefore, it's crucial to integrate the reasoning capabilities of these models with your company's unique context," he stated.
Glean's unique proposition is its ability to map this context and serve as a conduit between AI models and enterprise data.
The Glean Assistant acts as the primary interface for users, utilizing a familiar chat format powered by a blend of leading proprietary and open-source models, all grounded in the organization's internal data. However, Jain emphasizes that the true value lies in the robust infrastructure that supports it.
One of the key advantages is model accessibility. Instead of locking companies into a single LLM provider, Glean functions as an abstraction layer, allowing businesses to seamlessly switch between or combine models as their needs evolve. Jain views competitors like OpenAI and Anthropic not as threats, but as collaborators.
"Our product improves by leveraging the innovations they introduce to the market," he remarked.
Additionally, Glean offers deep integrations with platforms such as Slack, Jira, Salesforce, and Google Drive, effectively mapping information flow and enabling agents to operate within these tools.
Moreover, governance stands out as a crucial element. "It's essential to establish a permissions-aware governance and retrieval layer that delivers the right information while considering who is asking the question, ensuring the information is filtered according to their access rights," Jain explained.
In large organizations, this governance layer can determine whether AI solutions are merely piloted or fully deployed. Jain cautions against the simplistic approach of dumping all internal data into a model and hoping for the best.
Ensuring that models do not produce inaccurate information is also vital. Glean's system validates model outputs against source documents, generates precise citations, and respects existing access rights.
The critical question remains: will this intermediary layer persist as major platforms delve deeper into enterprise solutions? With Microsoft and Google already dominating much of the enterprise workflow landscape, the relevance of a standalone intelligence layer is in question.
Jain argues that enterprises prefer not to be confined to a single model or productivity suite; they seek a neutral infrastructure layer over a vertically integrated assistant.
This vision has attracted investor confidence, as Glean secured $150 million in a Series F round in June 2025, nearly doubling its valuation to $7.2 billion. Unlike many AI startups, Glean operates without the need for exorbitant computational budgets.
"We maintain a robust and rapidly expanding business," Jain concluded.
