Glean positions itself as the intelligence layer for enterprise AI

Seven years ago, Glean set out as an enterprise search tool. Today, the company is shifting its strategy to become the “intelligence layer”—the infrastructure connecting artificial intelligence models to internal company data—and an abstraction layer that sits between enterprise data and various large language models (LLMs). This positioning is designed to help companies avoid vendor lock-in. According to Glean’s CEO, Arvind Jain, enterprises do not want to be locked into a single model or productivity suite. Jain noted that the search product Glean initially built required a deep understanding of how people work and their preferences, which is now becoming foundational for building high-quality agents.

The company, which raised $150 million in Series F funding in June 2025 at a valuation of nearly $7.2 billion, argues that its value lies in how it connects generic models with company-specific context. Speaking on a podcast recorded last week, Jain noted that AI models do not inherently understand a company’s specific business, people, or products. To address this, Glean’s product architecture relies on three core pillars:

• Model access: Glean acts as an abstraction layer, allowing enterprises to switch between or combine different models.
• Connectors: The system integrates with internal systems to map how information flows across them.
• Governance: A permissions-aware retrieval layer that filters information based on user access rights.

Jain, who is the CEO of Glean, explained the necessity of this setup: “You need to build a permissions-aware governance layer and retrieval layer that is able to bring the right information, but knowing who’s asking that question so that it filters the information based on their access rights.”

Rather than competing directly with platform giants like Microsoft and Google, Glean positions itself as a partner. This approach allows enterprises to leverage innovation from model providers like OpenAI and Anthropic without committing to a single ecosystem. Jain stated that Glean’s product improves because it can leverage the innovation these model providers make in the market. He also noted that the company has a healthy, fast-growing business.

Why it matters

Glean’s strategy highlights a growing enterprise demand for neutral infrastructure that allows companies to leverage multiple AI models without being locked into a single vendor’s ecosystem.