TechnologySoftware Engineering

How SafetyCulture Uses Glean to Halve Search Time and Go AI-First

SafetyCulture is a global operations platform serving 2 million users across 180+ countries, powering over a billion workplace checks each year. After a 50% expansion of its engineering team created knowledge fragmentation across tools and departments, the company deployed Glean’s enterprise AI search and Agent Builder. Engineers cut search time by 50%, employees save 1.5 hours per week on average, and the company has since built a suite of custom AI agents embedded into engineering, HR, and GTM workflows.

Outcomes

50%Reduction in weekly hours spent searching
20 minutesTime saved per engineer per review cycle
90%+Employee recommendation rate for Glean
1.5 hoursWeekly time saved per employee on information search
30–40 minutesTime saved per performance review with AI agent

Tools & Technologies

1G
Glean
Enterprise search platform by Glean connecting company knowledge across SaaS apps using AI.

AI Categories

Challenge

A 50% surge in engineering headcount fragmented SafetyCulture’s internal knowledge across multiple disconnected tools, leaving employees spending up to four hours per week manually searching for information and making it impossible to efficiently onboard new hires or share institutional expertise at scale.

Solution

SafetyCulture deployed Glean’s enterprise AI search platform and Agent Builder, creating a unified knowledge layer connected to all internal data sources that delivers contextual search results and enables any employee to build, test, and share custom AI agents without engineering overhead.

Full Story

SafetyCulture operates one of the world’s most widely used workplace operations platforms, delivering more than a billion checks per year and 85,000 lessons daily to 2 million users in 180+ countries. Its products help frontline teams report issues, capture data, manage risk, and improve continuously. Running a platform at that scale requires its own internal teams to operate with the same precision it promises its customers — which made the company’s internal knowledge problem particularly urgent.

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