
At Airbnb, Swaroop Jagadish helped people find and trust their data. Now the DataHub co-founder and CEO is taking on a more demanding audience: AI agents that need the same institutional knowledge, without a colleague to ask.
Before CNTXT AI, Mohammad Abu Sheikh built places to exchange ideas and tools to make Arabic knowledge easier to reach. His next bet is that AI will travel further when it learns to listen locally.
When Matt Murphy took over Marvell in 2016, its data center business was a small part of the company. His next decade was spent moving toward the infrastructure that AI would eventually need.
An engineer spent three decades inside IBM before taking charge. His bet is that the next chapter of computing will be won in the complicated places where businesses actually work.

He co-founded Snowplow to give companies access to the events behind their analytics. Fourteen years later, Alex Dean is asking what happens when the next customer arrives with an AI agent.

A former fighter pilot built a storage company, handed off the hardware, and followed the data into the cloud. At Silk, Dani Golan is making another turn - toward the information that AI needs to do useful work.

At UCSB, Alexzendor Misra helped build Correkt, an AI search engine that reached 43,000 users. Now the Shofo co-founder and CTO is working on the video data that other AI systems learn from.

Timothy J. Klein built ATTO Technology around a stubborn engineering problem: expensive computers waiting for their data. His career follows the connections, partnerships and practical decisions behind keeping that data moving.

From an early French internet provider to Scality, Jérôme Lecat has spent three decades building the systems behind the screen. His recurring question is who gets to keep control.

Kazuki Ohta built tools that could analyze almost anything. His company found its footing when it chose a narrower job. Now the co-founder of Treasure AI is making another bet on who gets to use the machinery.
From a self-updating address book to the data behind digital advertising, Taoufik El Jamali keeps returning to the same question: what is stopping growth from working? At Journify, the answer lives between a purchase and the platform meant to learn from it.

After years debugging financial systems that processed hundreds of billions of rows a day, Mitch Radhuber left Goldman Sachs to build Corelayer. His wager is simple: the next on-call engineer will need memory, context and the good sense to ask a human.

He built People Data Labs by learning what customers would actually pay for. Now Sean Thorne is back at the beginning, teaching businesses how to serve customers made of software.

The DualBird co-founder saw the coming flood of AI data through a familiar scene: a pot of Bolognese and far too many hungry visitors. His answer drew on years in chip design, a taste for difficult engineering, and a habit of making time for people.
He helped bring behavioral advertising to the early web. Three decades later, Aqfer co-founder Dan Jaye is back in the CTO chair, working on the data problems that clever software keeps leaving behind.

Before Mitch Radhuber and Shipra Jha founded Corelayer, they spent about six years working side by side at Goldman Sachs. Now he is building AI agents to investigate the production problems that used to claim their evenings and weekends.
At Tapad, Nick Jordan had mountains of information and still could not get what his team needed. He founded Narrative to shorten the distance between a useful question and a usable answer.

From LiveRamp to Protege, Travis May keeps finding businesses in the gaps between other businesses. At Shaper Capital, he is trying to turn that habit into a company-building practice.

He learned to make risk systems dependable, led a remote analytics team, then helped put DuckDB in the cloud. Yves Le Maout's career is a study in making ambitious systems feel close at hand.
He spent more than three decades learning what happens beneath the software. Now Hitachi Vantara's CEO is betting that the most important promise in artificial intelligence is not magic, but machinery people can trust.

In 2020, Weyman Cohen was a Duke senior asking for help finding his way into marketing. Today, after a tour through distributed databases and developer tools, he is making the case for a smaller, faster and more conversational data stack at MotherDuck.

Before AI teams worried about feeding GPUs, Bin Fan was making key-value systems waste fewer bytes. His career follows one stubborn question across two technological eras: how do you keep expensive machines from waiting on data?

Before Tom Frana sold cloud services to Washington, he packed parachutes and learned that delivery means nothing unless the customer can use what arrives. At ViON, that lesson became a business model - and a two-year audition became a career measured in decades.
He studied law, mastered the finance function, and kept drifting toward the customer. At MinIO, Mahesh Patel's useful contradiction - the CFO who envies the salesperson - has become the job.
Coralogix nearly ran out of road before its co-founder reversed the usual order of data analysis. Now Ariel Assaraf is applying that survival lesson to a noisier problem: how humans and AI agents understand what software is actually doing.

The Databricks chief began with an awkward commercial problem: his laboratory had given away the engine. What followed was an education in turning open-source trust into a company without betraying the idea that made it matter.
He spent eleven years learning how networks carry information, then a decade learning how companies carry memory. After one exit and one return to startup life, Tony Ren is building for the handoffs that machines still forget.

The Databricks co-founder helped give big data a humane interface. Now he is returning to a problem his adviser once called solved - and finding it wonderfully unfinished.

He started Apache Spark to fix a stubborn research problem. Seventeen years later, Matei Zaharia is still turning computing bottlenecks into open systems that other people can build on.

The Firebolt CMO began as a software engineer, helped Checkmarx grow from below $1 million to more than $85 million in revenue, and learned that technical buyers will forgive a joke long before they forgive fluff.