Arvind Jain: The Humble Builder Behind Glean And The Future Of AI-Driven Enterprise Search

Forbes

16-05-2025

Arvind Jain, the humble builder
Glean
Seated for coffee at the heart of Wall Street, across from me is a man as humble as he is successful, which is a modern-day paradox in its own right.
Arvind Jain, CEO and co-founder of Glean, is anything but the caricature of an AI executive in 2025 one conjures up.
There's no buzzwords, no bravado, no executive bluster or the egos one is accustomed to seeing from tech founders.
Just a glass of water, a soft-spoken demeanor, and 90 minutes of insights from someone who's helped build a company that just crossed $100 million in annual recurring revenue. No big deal, not least because bigger things are up ahead.
What Jain offers is something very similar to what Glean has on the table: clarity and a sense of purpose.
His path to leading one of the most celebrated companies of the AI revolution doesn't follow a story of blitzscaling or viral hype.
Instead, the story that leads to the coffee shop and the company he has founded, is one of thoughtful preparation, confidence built over decades of acquiring competence, and a single, relentless question: Why not us?
It's hard to overstate just how fast the AI revolution has moved.
In just a handful of months, we've gone from marveling at what essentially was autocomplete-on-steroids to being utterly unphased by models capable of coding, writing, and strategizing better than most humans can.
First we had the LLMs that crawled, and then came the agents that skipped walking and burst on the scene running. These autonomous systems are designed not only to assist but to act, and most recently, retrieval-augmented generation (RAG) systems have unlocked entirely new ways of navigating unstructured data.
Where LLMs cracked open the possibility of generalized knowledge generation, agents introduced the concept of action, and RAGs brought trust and context back into the picture.
We now stand at the beginning of an era defined not just by what AI can say, but by what it can do, what it can retrieve, decide, execute, and improve over time. What was once a productivity enhancement is rapidly becoming a fundamental rethink of how organizations operate.
And yet, amid the velocity, a clear problem persists: most companies can't effectively access their own information. That's not a hardware or a fundamental limitation of AI itself: it's an interface problem. The future of AI lies not in generating more content, but in making existing knowledge actually usable in the content we generate.
For Jain, this is the natural evolution of the human-AI relationship. AI is not replacing humans and our thoughts. Instead, it is an augmentation of our memory, precision, and access to what we already know, intended to make us all the more productive and efficient.
"We've spent decades building information systems that collect and store, and yet, much of what we've squirreled away remains unusable by the systems we depend on daily" he says. "Now we need systems that recall and apply, instantly, contextually, and in a way that feels natural to the way humans think."
This is the great shift of the AI era: not building intelligence for its own sake, but refining the bridge between what's already known and what needs to be acted on.
Although the promise of AI, and RAGs in particular, is real, the momentum with which we are seeing capital, hype, and ambition collide means that the AI field has seen its share of whiplash and pushback as well.
Investment has poured in, and every week another startup emerges promising to 'redefine' workflows. There are platforms that string together LLMs, spurious claims of agentic superiority, and GPT wrappers upon GPT wrappers that are slapped on existing solutions. As with every gold rush comes the noise of the pickaxes, and this one's roaring loud indeed.
Enterprise buyers, already overwhelmed by cloud tools and SaaS sprawl, now face a new problem: how to evaluate AI offerings when the underlying technology is invisible and the stakes are existential. Many are burned by overpromises.
Some are paralyzed by choice.
'I feel for the CIOs,' Jain says. 'Everyone's selling AI, even if what they have to offer doesn't add that much value. It's our job to prove we're different.'
Glean does this by anchoring in outcomes with no razzle-dazzle or hype, much like their CEO.
That clarity has served them well.
'You can't win by being louder,' Jain says. 'You win by being useful.'
Still, getting here wasn't easy as Jain is the first to admit.
In the early days, well before ChatGPT, even as Glean had a working product it found itself having to do double-duty in every sales conversation. First to educate the buyer on what retrieval-augmented generation (RAG) was, and then to explain why their version of it worked better. Many buyers left the sales meetings unimpressed, not least because there was little understanding of what RAGs are, and what they could do.
'In 2022 and 2023, we were still having to teach people what this even was,' Jain recalls. 'We had to start from zero, explaining why enterprise search wasn't enough, why AI needed grounding, why this could be transformative. You were basically selling the vision and the vocabulary.'
But all that changed. Fast.
In the last year, Glean has gone from market explainer to category leader. Inbound interest surged. Companies now come in knowing what they want, with Jain's team ready to serve.
'That's the signal the market has matured,' Jain says.
'We're not introducing people to the idea anymore. They've seen the limitations of LLMs without context. They've seen the chaos that comes from incomplete knowledge. Now they're looking for solutions that work at scale, and we're ready.'
That shift from evangelizing the category to defining it is what sets Glean's current moment apart from many others in the AI field who are either too early or too late to the party.
It's not that the product changed entirely overnight.
It's that the world finally caught up to what they were building. And because they'd been preparing for this wave long before it crested, they were perfectly positioned when it did.
'When the world realizes it has a problem you've been solving for years,' Jain says, 'you get to lead. Not because you shouted the loudest, but because you listened the longest.'
Every company has an origin story.
With Glean it's impossible to separate the company from the journey its founder took to arrive where he is today.
Jain didn't barge onto the scene with the pompous bravado as many others do. Instead, he arrived prepared, shaped by a career spanning decades spent inside some of the most demanding and innovative organizations in tech.
His resume reads like a blueprint for building high-performance systems: Microsoft, Akamai, Google to name a few. Mamoon Hamid, partner at Kleiner Perkins and an early investor and longtime observer of Jain's rise, captures it well:
'He's like the king who doesn't want to be king, but who always finds the right way to take the next step,' Hamid says.
'There's a deep humility you see day in, day out. He'll ask more questions even about his own story, always chasing ground truth. It's not an act, it's just how he's built.'
Hamid recalls introducing Jain at a recent event where he had picked Kendrick Lamar's 'Be Humble' as Jain's walk-up song.
'It was a choice made entirely out of respect. Sometimes you almost have to pull the 'don't be so humble' out of him.'
According to Hamid, Jain's personality, eyes down, curiosity forward, expands the very surface area where luck can strike.
'The absence of ego expands the amount of people who want to come talk to you,' Hamid explains.
'It creates many more opportunities than you'd otherwise have, and Jain's first-principles mindset multiplies that effect even more.'
Each stop taught him something essential, whether it's about scale, about speed, or about solving problems that seem impossible until they're not.
Although Jain argues it has been more luck than not, one has to wonder whether pure instinct, or an uncanny ability to join companies at just the right inflection point, had something to do with it.
Whatever the reason, he's shown up when growth was about to go exponential, and he's helped push it further.
Some of his experiences still resonate loud and clear in the very DNA of Glean itself.
Take his time at Google for example, where Larry Page and the executive team once asked him to make the internet faster. For a younger version of Jain, the task seemed confusing at first, as early Google had little leverage over how fast the internet could be outside of its own data centers.
When he came back with a detailed, technically sound plan that optimized Google's internal approaches with a minimal budget to boot, Page responded with 'Great. Now think bigger and spend $10 billion on it.'
Larry hadn't given his approval to the project as much as he dared Jain to think even bigger.
This nudge towards ambition that was exponential instead of incremental jolted the engineer in Jain to a headspace he carries with him today.
'That moment taught me a lot,' Jain says. 'Being told to do more because the vision wasn't grand enough yet shifted something inside me in a way I haven't shaken off to this day. We often aim too low, and curtail our own path to success by doing so, even when we have every right to think big.'
That mindset of stretching your thinking, then stretching it again, shaped how Jain thinks about leadership.
He's not in the mold of a Marc Benioff, whose flamboyance fuels Salesforce's brand. Nor is he a Sam Altman, whose bold public vision has come to represent AI's next frontier. Neither does he rally crowds or set off Twitter storms as an agent provocateur.
He doesn't need to.
His leadership flows from clarity of thought and the ability to build momentum slowly, sustainably, and with deep conviction.
"I'm not the best engineer," he tells me. "I get out of the way so the best ones can do their work. That's something I learned at Google. Create the conditions, then get out of the way."
This humility is disarming.
In an industry increasingly defined by ego, Jain's soft-spoken clarity makes him all the more compelling. There's no cult of personality. There's just a focus on the mission.
He's not chasing the limelight, but he understands the responsibility that comes with leading a category-defining company. "Sometimes the people best suited to lead are the ones who least seek the spotlight," he reflects. "But that's okay. Real leadership doesn't need a stage, which suits introverts like me just fine."
As AIM Research notes, Glean is in a position to establish itself at the pole position, but success is not at all guaranteed.
Ask Jain what separates successful companies from the rest, and he won't start with product or go-to-market strategy.
He'll start with timing, and what you do before it matters.
"You can't control when the world will pay attention," he says. "But you can control whether you're ready."
Mamoon Hamid puts it another way: 'It's not luck in the blind sense. It's expanding your luck surface every day, through humility, relentless learning, and showing up without pretense.'
Hamid sees a parallel in his own life.
'I was voted shyest kid in my high school class, and also most likely to succeed,' he laughs.
'You don't start out trying to lead companies or industries. You focus on what matters to you, and one day you look around and realize: you've become the person others are betting on.'
It's that slow build, daily curiosity compounded over decades, that defines Arvind's path and, increasingly, Glean's trajectory too.
Glean spent years building the foundational stack before the generative AI wave crested. They didn't chase hype. They prepared for the moment. And when it came, they moved.
"Being early is painful, and it's easy to run out of belief," Jain says.
Indeed, the journey of a startup is paved with improbabilities.
The odds are against you statistically, structurally and emotionally, to the point where looking at the three-year survival rates of startups is enough to make you shudder.
To start a company is to embrace a quiet kind of delusion where you have to ignore the probabilities and follow the possibilities instead.
"I knew we had a team I trusted and a problem people hated: enterprise search. That was enough to convince me to get started. That's how you begin," Jain reflects on how the company began in 2019.
The belief that this particular company is the one that will make it isn't naïve optimism.
It's what makes founders unique: the ability to see what could be, not just what is. The path to a company like Glean isn't a straight flight of an arrow. It's a series of hard choices, near misses, and small wins that compound.
"The path to a trillion-dollar company is narrow," Jain says. "You walk it one step at a time. But first, you have to believe you deserve to be on it."
There's a quiet insistence in his voice when he says this.
It's not about ego. It's about conviction about having the right to win. You don't need to know every step. You just need to take the next one.
We finish our drinks. He folds his napkin, stands, and gives me a parting thought: "In this industry, luck and momentum is everything. But a clear sense of direction matters more."
And with that, he steps into the pulse of New York, quietly shaping the AI revolution, one humble conversation at a time.