Companies that use Glean

Source: Analysis of 100 job postings that mention Glean

My analysis reveals that Glean buyers span diverse leadership roles, with no single department dominating. Directors across marketing, strategic planning, and operations represent approximately 15% of hiring, while VPs in sales and IT account for another 8%. The remaining 78% shows extraordinary variety, from analytics directors to HR operations leads, revealing that Glean purchasing decisions cut across nearly every function. These buyers share common priorities around modernization, AI transformation, and knowledge management infrastructure. They're building teams to handle enterprise automation, data governance, and scalable technology platforms.

Day-to-day users are equally diverse. Individual contributors like AI Solutions Engineers, Knowledge Managers, Data Analysts, and IT Operations Specialists actually work with Glean for search, knowledge sharing, and workflow automation. One posting specifically seeks someone to oversee Glean's enterprise insights platform, managing access, integrations, and system updates. Another emphasizes implementing KM guidelines across drive settings and ensuring searchability on AI tools. These hands-on roles focus on making information accessible, standardizing documentation, and optimizing how teams find and use knowledge.

The pain points center on information chaos and lost productivity. Companies describe needing to make knowledge actually usable, glean insights from data, and create deeper more meaningful connections. One posting seeks help with documentation that Coolblue'ers need to do their work, while another mentions using Glean alongside security architecture for connector governance. The recurring theme is transforming scattered knowledge into actionable intelligence that accelerates business outcomes.

Source: Analysis of tech stacks from 402 companies that use Glean

I noticed that companies using Glean are heavily focused on internal operations, developer productivity, and employee enablement. The presence of tools like Golinks (for internal link shortening) and DX (for developer experience) tells me these are fast-growing tech companies obsessed with reducing friction in how their teams work. They're building sophisticated internal infrastructure to help employees navigate complexity and find information quickly.

The pairing of Glean with PagerDuty makes perfect sense because both solve the "too much information, too little time" problem. PagerDuty handles incident response and alerts, while Glean helps engineers search through documentation and past incidents during those critical moments. Similarly, Mindtickle appearing alongside Glean suggests these companies are scaling their sales teams rapidly and need both knowledge management (Glean) and sales enablement (Mindtickle) to get new reps productive faster. The Decagon AI correlation is particularly interesting because it shows these companies are investing in AI-powered customer support externally while also using AI-powered search internally with Glean.

The full stack reveals these are sales-led or hybrid growth companies in scaling mode. They're past the early startup phase and dealing with the chaos that comes from rapid headcount growth. They need tools that help new employees ramp up quickly and help existing employees stay productive despite growing complexity. The presence of both internal productivity tools and sales enablement platforms suggests they're likely Series B to D companies with 200 to 2,000 employees.

Source: Analysis of Linkedin bios of 402 companies that use Glean

I noticed that Glean's customers span an impressive range of industries, but they share a common thread: they're dealing with complex operations and massive amounts of information. These aren't simple businesses. I see healthcare companies managing patient data and clinical workflows, financial services firms processing billions in transactions, retailers coordinating vast supply chains, and technology companies building sophisticated platforms. What strikes me is how many describe themselves as "leading" or "pioneering" in their fields, companies like Fivetran that are "the global leader in data movement" or Notable with its "AI platform for healthcare operations."

Looking at their maturity, I see a mix heavily weighted toward established players. The majority are either publicly traded companies or well-funded growth-stage firms with Series C rounds and beyond. Many have 1,000+ employees, some exceeding 10,000. But there are also younger companies like 7AI and Composio with under people, suggesting Glean appeals across the growth spectrum.