How Glean built a $bn AI product

👋 Hey, this is Ben with a 🔒 subscriber-only issue🔒 of Ben’s Bites Pro. A weekly newsletter covering how businesses are using AI.

If you’re not a subscriber, here’s what you missed recently:

• How to get your team to use AI; insights from Stripe and more

• How IgniteTech is using AI to change its business

• Analysing Intercom’s AI strategy

Today we’re looking at Glean, an AI-powered search and knowledge discovery solution for enterprises.

Glean has successfully established itself as a leader in the AI space. It’s valued at over $1BN (hello, unicorn status) and is backed by the likes of Kleiner Perkins, Lightspeed and Sequoia. Its client roster includes Databricks, Duolingo, and Grammarly, to name a few.

The company is revolutionising how modern teams locate internal information. By providing a centralised repository of a company’s information, workers can swiftly find any document, information or person they need to do their work.

Thanks to Arvind Jain for his time for this post.

Humble beginnings

Like many of today’s successful tech companies, Glean was born out of real challenges experienced at work. Arvind Jain is Glean’s co-founder and CEO. He was struggling with knowledge search and discovery at his previous startup, Rubrik, when he landed on the idea for Glean.

Jain tried to find a ready-made solution for Rubrik. But the requirements proved a challenge: it needed to integrate with over 300 applications used by Rubrik’s employees, and work well enough that the adoption rate would be high.

To Jain’s surprise and frustration, no such solution existed. And this seemed to be an industry-wide issue. Enterprise companies everywhere were struggling. They has lots of information in lots of different places, without the means for employees to locate it.

When you can’t find it, build it.

Jain had identified a gap in the market. He saw the opportunity to create the solution companies needed, and decided to go build it. He hired someone to take over his R&D responsibilities at Rubrik and got to work on incubating the idea that would later become Glean.

Solving a common problem

Information retrieval is a common use-case. According to McKinsey, a survey revealed that over a quarter of a typical knowledge worker’s time is spent searching for information. Another found that only 16 percent of content is posted where other workers can access it.

The problems here are obvious. Companies want their workers to spend time doing the things that make the business most successful. Not wasting time finding stuff.

But the reason few solutions exist is because it's a hard problem to solve. Firstly, every enterprise is different, with its own unique set of information, apps, tech stack and people to solve for. Secondly, it’s only in the last decade that the support for APIs has become available across most apps. Before that, trying to integrate with say, a messaging app, was difficult to the point of being impossible.

Now, thanks to the rapidly changing technological environment and progression in AI, a solution like Glean is possible. And judging by the company’s success, it’s a solution that’s been eagerly awaited.

The Google standard

Glean’s founding team all worked at Google previously. There, they had the luxury of using Moma—a custom intranet that indexes everything used inside Google.

Subscribe to Premium to read the rest.