Building Glean with Arvind Jain: Scaling Enterprise Search with AI Innovation
Mar 11, 2025
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Arvind Jain, CEO and founder of Glean and a former Google Distinguished Engineer, discusses his journey to revolutionize enterprise search. Frustrated by workplace information retrieval, he created Glean to tackle efficiency issues for large organizations. They explore the role of AI in solving real-world enterprise challenges, the importance of a scalable design, and the balance between customization and broader applicability. Arvind shares insights on using both explicit and implicit data to enhance the platform, highlighting the transformative potential of AI in the workplace.
Arvind Jain founded Glean to address workplace information retrieval challenges, stemming from his personal frustration with inefficient search systems at companies.
Glean's architecture was intentionally designed for scalability to meet the demanding needs of large enterprises and support extensive data growth.
Deep dives
The Origin of Glean
The need for Glean arose from a common challenge faced by many employees: the inability to effectively search for and access information within their own companies. Many employees have experienced the frustration of knowing valuable documents and policies exist but being unable to find them, whether it's about dental benefits or crucial project specifications. Arvind Jain, the CEO and founder of Glean, saw this issue firsthand while working at Rubrik, where rapid company growth led to a noticeable decline in productivity due to poor information retrieval systems. This realization sparked his entrepreneurial journey, leading him to create a platform designed to centralize search capabilities across various knowledge systems, addressing a widespread problem that he discovered was affecting many others as well.
Building for Scalability
From the onset, Glean was built with an emphasis on scalability, with the understanding that enterprise customers, particularly large organizations, have unique and demanding requirements. Arvind and his team designed the platform to handle vast amounts of information and user requests, establishing performance benchmarks early in the development process, such as initially aiming to support 100 million documents. This focus on scalability was driven by the anticipation of serving some of the world's largest companies, which has proven beneficial as Glean has been able to adapt to increasing data demands from clients effectively. The engineering team, leveraging their background from Google, prioritized creating a robust infrastructure that could handle future growth without sacrificing performance.
Validating Product Value
Initially, Glean faced skepticism from potential customers who questioned the necessity and ROI of an enterprise search solution that could be perceived as optional. To overcome this barrier, Arvind encouraged companies to trial Glean for free, allowing them to see the platform's efficacy in action and understand its value through direct experience. Feedback from trials generally indicated that Glean saved users significant time each week, leading to qualitative metrics indicating user satisfaction and productivity improvements. By demonstrating clear benefits and enabling potential clients to experience the value firsthand, Glean has steadily gained traction despite initial hesitations regarding its market relevance.
Balancing Customization and Growth
As Glean continues to grow, the challenge of balancing customization for individual clients while maintaining a cohesive, scalable product becomes increasingly complex. Every enterprise client has unique requirements, making it tempting for startups to adapt their products excessively to meet these specific requests. However, Arvind emphasizes the need for discipline in product development, advocating for a clear vision and roadmap that prioritizes common client needs over one-off customizations. By fostering open communication with customers and gathering insights on their collective needs, Glean aims to create valuable solutions without diluting its core offerings.
In a world where finding information at work is often more of a headache than it should be, Arvind Jain’s innovative solution is transforming the way enterprises manage and access knowledge. In this week’s episode of Building One, Tomer Cohen sits down with Arvind Jain, CEO and founder of Glean, to discuss how the AI-driven platform is reshaping the future of enterprise search.
Prior to founding Glean, Arvind was a Distinguished Engineer at Google, where he honed his deep technical expertise and understanding of search products. Passionate about building products that solve real-world problems, Arvind has been a key advocate for building with scalability in mind from day one.
Tomer and Arvind discuss:
Why Arvind Jain’s personal frustration with information search in the workplace led to the creation of Glean.
Why Glean’s team designed their product with large enterprises in mind from the very beginning.
How Glean uses both explicit and implicit data to measure success and improve its platform.
The challenges of staying true to your product roadmap while meeting the diverse needs of enterprise customers.
Why AI’s greatest potential lies in solving enterprise-level challenges and how Glean is leveraging this technology to improve workplace efficiency.