Enterprise search has long been considered one of technology’s dead ends. For decades, even the biggest firms failed to build a product that could make finding information inside companies easy or commercially viable. In 2019, Arvind Jain, a former Google Search engineer and co-founder of Rubrik, decided to attack the problem head-on.
At the time, there was no established market to build into. That didn’t matter to Jain, because the problem was one he had seen repeatedly in his own career. At Google, he worked on making search effortless for billions of people on the web, yet the same company struggled to serve its own employees with the same clarity. At Rubrik, the challenge became existential. As the company scaled, surveys showed that employees felt less effective, not more. The common complaint: they couldn’t find what they needed to do their jobs.
“Productivity was dropping,” Jain recalled. “People were not able to get as much work done as they used to when we were small. They couldn’t find information, and they couldn’t find the right people to help them. They felt stuck.”
That sense of frustration became the impetus for Glean. Jain describes his instinct as natural for a search engineer: if the problem is information discovery, the answer is to build a search product designed for the enterprise. “It was shocking to me that there was no search product for businesses,” he said. “Every company has huge amounts of information, and they need it.”
Jain spoke to AIM Media House in association with The Llama Club about his journey, the recent funding and what the startup ecosystem looks like for him.
Naming Glean and Building Early
The startup was not always called Glean. Jain’s first choice was Scio, Latin for knowledge. While the name fit the mission, it didn’t resonate broadly, and the team pushed for a change. A “naming party” eventually surfaced the word Glean, which quickly became the favorite.
The technology foundation came just as deliberately. Jain and his team began experimenting with transformers in early 2019, long before the term became mainstream with ChatGPT. For him, transformers were a natural fit: they had been developed at Google to move search beyond keywords, into understanding questions and concepts. Applying them to the enterprise was an obvious step.
Those early models, though modest by today’s standards, made a measurable difference. “It was a significant change in search ranking,” Jain explained. “We used them from the beginning, and that actually made us the first enterprise generative AI company in the world.”
Over time, transformers became central not only to ranking but to the entire user experience. “It’s no longer about 50% or 60% better performance. It has fundamentally changed the experience,” Jain argued. Glean, once built to retrieve information, now facilitates conversations. “When people come to Glean, they don’t just search—they interact.”
A Funding Round as a Statement
In 2025, Glean raised $150 million at a $7.2 billion valuation. For Jain, the capital itself was less important than the message it sent. Enterprise buyers are in the middle of AI transformation, he observed, and they want to place bets only on companies that will endure.
“Every enterprise wants to go through an AI transformation, and they want to do it now,” Jain said. “For that, they need partners they can rely on companies they know will last.” The round, backed by some of the world’s most prominent investors, was meant to give those enterprises confidence. “We already had the product and the technology,” he added. “This was about showing we have the power to last.”
Scaling Across Borders
For startup founders building outside the US, Jain’s advice is practical: expand as soon as product-market fit is proven. “If you already have a product working and a couple of customers, there’s no reason to wait,” he advised. Having teams in both the Bay Area and Bangalore has been an advantage for Glean, offering proximity to multiple markets and the ability to support customers around the clock.
But ambition, not geography, is what he sees as decisive. He contrasted the mindset of building to be acquired with building to endure. “If you think you’ll just be bought, you won’t build the sales and business teams you need. Your ambition won’t be large enough. To be big, you have to think big.”
Despite anxiety among graduates about the value of computer science degrees in an AI-saturated world, Jain believes the fundamentals of hiring haven’t changed. Glean still looks for people with ambition, collaboration skills, and strong analytical ability.
One criterion, however, has become non-negotiable: adaptability to AI. “We now check whether people are using AI tools in their work,” Jain said. “They don’t need to understand transformers, but if they’re not using ChatGPT or anything like it, it shows they’re too stuck in their ways. Willingness to change is one of the most important skills.”
Competition and Context
The speed of AI model development raises questions about whether companies like Glean can maintain an edge if foundational model providers keep absorbing functionality. Jain acknowledged the dynamic but framed it as an opportunity. “Whatever product you build, you have to be ready to throw parts of it away as those capabilities become part of the underlying models,” he said. “The good thing is there’s no ceiling in sight. Today, AI is still pretty limited. It hasn’t yet made people even twice as effective, let alone 50 times. That’s where we’re heading.”
Consumer search entrants like Perplexity, which deliver conversational results with real-time context, also draw comparisons. Jain is blunt about the differences. “The problem of search on the web is so different from search in the enterprise. On the web, everything is public. In enterprises, content is secure, governed by permissions. Ranking is different, governance is critical. Those are not problems consumer search has to solve.”
That, he argues, is why Glean maintains a lead. Having worked on consumer search at Google for more than a decade, Jain believes the two markets require fundamentally different approaches. Glean’s head start he counts four to five years over new entrants matters in a space where integration, governance, and trust are paramount.
Jain’s ultimate vision is to change how people interact with work. “We want to build a fully personal work companion, a companion that everybody gets at work, which can eventually do 90% of your work for you,” he said.
That vision will take years of engineering and trust-building, but he is unapologetic about its scale. For him, the focus is less on what competitors might launch and more on staying close to the mission. “History shows that most innovation happens at startups,” he reflected. “New products get built by new companies. If you keep working hard, stay on your mission, and don’t give up, you can win.”
