Glean and the Rise of AI-Powered Enterprise Search
AI agents are transforming how enterprises find and act on internal knowledge
The average enterprise employee spends nearly 20% of their work week searching for information, according to McKinsey research. That staggering inefficiency has created one of the most compelling use cases for AI agents: *enterprise search that actually works*. Glean, founded in 2019 by former Google engineer Arvind Jain, has emerged as the leading player in this space, building an AI platform that connects to over 100 enterprise applications — from Slack and Confluence to Salesforce and Jira — and lets employees search across all of them with a single natural language query.
Glean's approach goes beyond traditional keyword search. The platform builds a knowledge graph of an organization's people, documents, and relationships, then uses large language models to understand queries in context. Ask "What was the decision on the Q3 pricing strategy?" and Glean surfaces the relevant Slack thread, the Google Doc with the analysis, and the Jira ticket tracking implementation — respecting access permissions throughout. In 2024, the company raised a $200 million Series D round at a $4.6 billion valuation, with investors including Sequoia Capital, Kleiner Perkins, and Lightspeed Venture Partners.
The competitive landscape is intense. Perplexity launched an enterprise product offering AI-powered search with cited sources over internal documents. Microsoft integrated Copilot deeply into its 365 suite, leveraging its dominant position in enterprise productivity. Elastic and Coveo have added AI capabilities to their existing search platforms. But Glean's *connector-first approach* — integrating deeply with the tools companies already use — has given it an edge with large enterprises seeking a vendor-neutral solution.
What makes the enterprise search category particularly important for the AI agent narrative is that it represents one of the first domains where agents create *clear, measurable ROI*. When an engineer can find the relevant design document in seconds instead of minutes, when a salesperson surfaces the right case study without asking three colleagues, the productivity gains compound across an entire organization. Glean reports that its largest customers see measurable reductions in time-to-information, making the business case for AI agents concrete rather than theoretical.