The competition in the enterprise AI sector is intensifying, as major players like Microsoft and Google enhance their offerings. Microsoft has integrated Copilot into its Office suite, while Google is incorporating its Gemini AI into Workspace. OpenAI and Anthropic are now targeting businesses directly, and virtually every SaaS provider has introduced an AI assistant. However, Glean is focusing on a less visible but crucial role: establishing itself as the connective intelligence layer for enterprise systems.
Founded seven years ago with the aim of becoming the "Google for enterprise," Glean specializes in AI-driven search capabilities that index and retrieve information from various SaaS tools, such as Slack, Jira, Google Drive, and Salesforce. The company is pivoting from developing a simple enterprise chatbot toward enhancing integration between AI models and enterprise data systems.
As Glean co-founder Dhaman Jain notes, while large language models (LLMs) wield impressive power, they often lack a deep understanding of an organization’s specific context. "The AI models themselves don’t really understand anything about your business," Jain explained, underscoring the need for these models to be enriched with contextual knowledge from within the company.
The Glean Assistant serves as an initial touchpoint for customers, leveraging a user-friendly chat interface that combines proprietary models like ChatGPT, Gemini, and Claude with the enterprise’s internal data. However, the true value, according to Jain, lies in the system’s underlying capabilities.
Key features of Glean include:
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Model Access: Glean acts as an abstraction layer, enabling businesses to switch between different LLMs as their needs evolve without being tied to a single provider.
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Integrated Connectors: Deep integrations with platforms like Slack, Jira, Salesforce, and Google Drive allow Glean to understand and act upon the flow of information across tools effectively.
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Governance and Permissions: A robust governance layer ensures that data retrieval is permissions-aware, filtering access based on user rights, which is crucial in large organizations.
Jain highlights that this governance layer can significantly influence whether enterprises can effectively scale their AI initiatives. He cautions against merely feeding internal data into a model without a thoughtful approach to organization and access rights. Glean also implements safeguards to prevent AI hallucinations by cross-verifying model outputs against source materials and providing clear citations.
As tech giants like Microsoft and Google deepen their involvement in this space, one pertinent question arises: Can Glean maintain its relevance as a neutral intelligence layer? Jain argues that enterprises prefer flexibility over being locked into a single model or productivity suite, making Glean’s role as a neutral infrastructure provider indispensable.
Investors are aligned with this vision; Glean recently secured $150 million in Series F funding, nearly doubling its valuation to $7.2 billion. Jain affirms that Glean is flourishing without the massive computational expenditures characteristic of frontier AI labs, stating, "We have a very healthy, fast-growing business."
