Glean’s Strategic Shift: Building the Backbone of Enterprise AI Integration
In the rapidly evolving landscape of enterprise artificial intelligence (AI), major players like Microsoft and Google are embedding AI assistants directly into their productivity suites, such as Copilot in Office and Gemini in Workspace. Simultaneously, AI pioneers like OpenAI and Anthropic are offering their models directly to businesses, while numerous Software as a Service (SaaS) providers are introducing their own AI-driven tools. Amidst this competitive frenzy, Glean is charting a distinct course by focusing on the foundational infrastructure that connects these AI models to enterprise systems.
Glean’s Evolution: From Search to Integration
Founded seven years ago, Glean initially aimed to revolutionize enterprise search by creating an AI-powered tool capable of indexing and retrieving information across a company’s suite of applications, including platforms like Slack, Jira, Google Drive, and Salesforce. This endeavor required a deep understanding of organizational workflows and employee preferences. Over time, Glean recognized that the true value lay not just in search capabilities but in serving as the intermediary layer that seamlessly integrates various AI models with enterprise data.
Arvind Jain, Glean’s CEO, highlighted this strategic pivot during a recent discussion at Web Summit Qatar. He emphasized that while large language models (LLMs) possess significant generative and reasoning capabilities, they lack intrinsic knowledge about specific business contexts. These models do not inherently understand organizational structures, employee roles, or the nature of the products and services a company offers. Therefore, there’s a critical need to bridge the gap between the generic capabilities of LLMs and the unique contexts of individual enterprises.
The Role of Glean Assistant
Glean’s solution to this challenge is the Glean Assistant, a chat interface that serves as the entry point for users. This assistant is powered by a combination of leading proprietary models, such as ChatGPT, Gemini, and Claude, as well as open-source models. What sets Glean Assistant apart is its grounding in the company’s internal data, ensuring that the AI interactions are contextually relevant and accurate.
However, the true strength of Glean lies beneath this interface. The company has developed a robust infrastructure that offers several key advantages:
1. Model Agnosticism: Glean provides enterprises with the flexibility to choose and switch between different LLM providers as their capabilities evolve. This approach prevents vendor lock-in and allows businesses to leverage the best available AI technologies without being tied to a single provider. Jain views companies like OpenAI, Anthropic, and Google not as competitors but as partners whose innovations enhance Glean’s offerings.
2. Deep Integration with Enterprise Systems: Glean has developed connectors that integrate seamlessly with various enterprise platforms, including Slack, Jira, Salesforce, and Google Drive. These integrations enable the AI agents to understand and act within the specific workflows and data structures of each organization, facilitating more effective and efficient operations.
3. Comprehensive Governance and Security: Recognizing the importance of data security and compliance, Glean has implemented a permissions-aware governance layer. This system ensures that information is retrieved and presented based on the user’s access rights, maintaining strict adherence to existing security protocols. Additionally, Glean’s infrastructure is designed to verify AI-generated outputs against source documents, providing line-by-line citations and minimizing the risk of inaccuracies or hallucinations that can occur with AI models.
Navigating the Competitive Landscape
As tech giants like Microsoft and Google continue to expand their AI capabilities and integrate them more deeply into their productivity tools, questions arise about the viability of independent intelligence layers like Glean’s. If these major platforms can access internal systems with the same permissions and context awareness, the necessity of a standalone integration layer might be challenged.
Jain argues that enterprises prefer to avoid being locked into a single model or productivity suite. By offering a neutral infrastructure layer, Glean provides businesses with the flexibility to adapt and evolve their AI strategies without being constrained by the limitations of a vertically integrated assistant.
Financial Growth and Market Position
Glean’s strategic approach has resonated with investors. In June 2025, the company secured a $150 million Series F funding round led by Wellington Management, nearly doubling its valuation to $7.2 billion. This substantial investment underscores the confidence in Glean’s vision and its potential to play a pivotal role in the enterprise AI ecosystem.
Unlike frontier AI labs that require massive computational resources, Glean’s focus on integration and infrastructure allows it to operate with a more efficient cost structure. This efficiency, combined with its strategic positioning, positions Glean as a key player in the ongoing evolution of enterprise AI.
Conclusion
As the enterprise AI landscape continues to evolve, the competition to own the interface is intensifying. However, Glean’s focus on building the underlying intelligence layer offers a compelling alternative. By providing flexible model access, deep system integrations, and robust governance, Glean enables enterprises to harness the full potential of AI while maintaining control over their data and workflows. In a market dominated by tech giants, Glean’s approach offers a path to AI integration that prioritizes adaptability, security, and enterprise-specific context.
