Podcast Summary: Building Glean with Arvind Jain: Scaling Enterprise Search with AI Innovation
Building One is a captivating podcast series hosted by Tomer Cohen, LinkedIn’s Chief Product Officer. In the episode titled "Building Glean with Arvind Jain: Scaling Enterprise Search with AI Innovation," released on March 11, 2025, Tomer engages in an insightful conversation with Arvind Jain, the CEO and founder of Glean. This episode delves deep into the challenges of enterprise search, the entrepreneurial journey behind Glean, and the transformative role of AI in enhancing workplace productivity.
1. Introduction to Glean and Arvind Jain
Tomer Cohen opens the discussion by introducing Arvind Jain, highlighting his extensive background in search technology and his entrepreneurial ventures, including co-founding Rubrik, a cybersecurity company. Arvind’s journey to founding Glean stems from a pervasive problem in enterprises: the difficulty employees face in accessing and retrieving internal knowledge efficiently.
[00:38] Tomer Cohen: "If you worked at a company long enough, you've definitely felt this pain. You wanted to find information that you knew existed but couldn't locate."
2. Identifying the Core Problem
Arvind Jain emphasizes that innovation is rooted in problem-solving. His motivation to build Glean was driven by a personal pain point experienced during his tenure at Rubrik. As the company scaled rapidly, productivity metrics plateaued despite increasing the engineering team size, signaling inefficiencies in knowledge management.
[04:17] Arvind Jain: "When you talk with entrepreneurs about what they're building, usually there's something very specific that they feel they know really intimately."
Arvind observed that as companies grow, the dispersion of knowledge across numerous SaaS systems hinders productivity. Attempts to procure existing enterprise search solutions fell short, revealing a market gap that Glean aimed to fill.
3. The Entrepreneurial Journey and Market Validation
Tomer Cohen shares his own entrepreneurial aspirations and how working at Google shifted his focus towards building impactful products rather than starting ventures from scratch. This perspective resonates with Arvind, who underscores the rarity of solving such a fundamental problem that is common across enterprises yet underserved by existing solutions.
[09:25] Tomer Cohen: "I have this firm belief. I don't think competition matters. What's more difficult is that can you actually go and build a good product?"
4. Building for Scalability from the Outset
From inception, Glean was designed to cater to large enterprises, ensuring scalability was a foundational element. Arvind explains that the engineering team, many of whom hailed from Google, ingrained scalability into the product’s DNA.
[11:51] Tomer Cohen: "Any system that you build, make sure that you are keeping that scale requirements in mind."
Glean’s architecture was initially targeted to handle 100 million documents, accommodating the vast knowledge bases of global enterprises. This foresight allowed the platform to seamlessly scale, although real-world applications occasionally necessitated architectural adjustments.
5. Balancing Customization with Scalability
A significant challenge highlighted in the conversation is balancing the need for customization with the imperative of scalability. Enterprises often have unique requirements, but accommodating every custom request can jeopardize the product’s scalability.
[27:15] Tomer Cohen: "Every customer is going to take you in different direction and it's very hard to actually say no to them because you need that revenue."
Arvind and Tomer discuss strategies to maintain this balance, such as prioritizing features based on common customer needs and implementing platform flexibility that allows for some level of customization without fragmenting the core product.
6. Measuring Success: Beyond Traditional Metrics
Glean employs a blend of explicit and implicit metrics to gauge product success. While traditional metrics like successful searches and user engagement are tracked, Glean places a higher emphasis on qualitative feedback and specific use-case outcomes.
[19:07] Tomer Cohen: "We look at all these metrics that you mentioned. Like, we want to make sure that the product is actually working well."
For instance, a telecom company using Glean saw a 42% reduction in case resolution time among 60,000 customer care agents, translating into substantial cost savings and enhanced productivity.
7. Leveraging AI and Large Language Models (LLMs)
Glean was an early adopter of AI and LLMs, integrating these technologies to enhance search capabilities. Arvind reflects on the evolution of search from simple keyword-based queries to sophisticated AI-driven responses that can synthesize information from multiple sources.
[29:50] Tomer Cohen: "We had the same vision from day one that we'll build this product. People will come and ask questions, we'll surface the links to the right resources, but whenever we can, we will actually try to answer the questions."
This proactive integration of AI positioned Glean ahead of competitors, allowing the platform to offer advanced features like semantic search and answer extraction, which have become increasingly essential in modern enterprise environments.
8. Future Outlook: AI-Driven Productivity
Looking ahead, Arvind anticipates that AI will revolutionize workplace productivity by automating routine tasks and enabling AI assistants to handle complex queries. Glean aims to remain at the forefront of this transformation by continually enhancing its AI capabilities to serve as a personal assistant for every worker in every company.
[35:45] Tomer Cohen: "We are going to see it. The question is like, how are you going to get there as a company?"
9. Key Takeaways and Insights
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Problem-Driven Innovation: Arvind’s deep understanding of the enterprise search problem fueled Glean’s success, underscoring the importance of addressing genuine pain points.
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Scalability by Design: Building with scalability in mind from the outset enabled Glean to cater to large enterprises effectively, differentiating it from competitors.
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Balancing Customization and Core Product Integrity: Maintaining a balance between meeting unique customer needs and preserving the scalability and integrity of the core product is crucial.
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AI as a Catalyst for Productivity: Integrating AI and LLMs early allowed Glean to offer advanced search capabilities, positioning the company advantageously in the evolving tech landscape.
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Measuring Impact Through Real-World Outcomes: Demonstrating tangible productivity gains, such as reduced case resolution times, is essential for proving ROI to enterprise clients.
Notable Quotes
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Arvind Jain: "Innovation ultimately is solving problems." [00:06]
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Tomer Cohen: "I don't think competition matters. What's more difficult is that can you actually go and build a good product?" [09:25]
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Arvind Jain: "Every customer is going to take you in different direction and it's very hard to actually say no to them because you need that revenue." [27:15]
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Tomer Cohen: "We had the same vision from day one that we'll build this product. People will come and ask questions, we'll surface the links to the right resources, but whenever we can, we will actually try to answer the questions." [29:50]
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Tomer Cohen: "If you have a good product, if it's also a real need, then ultimately they will come and pay for it." [17:42]
Conclusion
The episode featuring Arvind Jain offers a comprehensive exploration of the challenges and triumphs in building a scalable enterprise search solution. Glean’s journey underscores the significance of addressing real-world problems with innovative solutions, leveraging AI to enhance functionality, and maintaining a delicate balance between customization and scalability. For entrepreneurs and product leaders, Arvind’s insights provide valuable lessons on the importance of deep market understanding, strategic product design, and the impactful integration of emerging technologies.
This summary is intended for individuals seeking to understand the key themes and insights from the Building One podcast episode featuring Arvind Jain of Glean. For a more detailed exploration, listening to the full episode is recommended.
