He keeps following the data - from search algorithms at Google to the warehouse marketers can finally talk to.
Dr. Jason Davis. The PhD is in the LinkedIn handle, too.
The dispatch
In September 2025, a ten-year-old company called Simon Data quietly dropped half its name. It became Simon AI. Jason Davis, the co-founder who runs it, described the moment in the flattest possible terms: agentic AI, he said, is the biggest shift in marketing since the move to SaaS and cloud computing. Coming from a man who spent his twenties proving theorems about machine learning, that is not hype. It is a forecast.
Davis is a data scientist who became a CEO, which is rarer than it sounds. Most founders pick up data along the way. He started there - a PhD in machine learning, data mining and statistics from the University of Texas at Austin, then a stint at Google writing search algorithms. The path from there to a New York martech company runs through one stubborn, unglamorous idea: the hardest problem in marketing is not the model. It is getting the data to the person who needs it.
Simon AI sells that shortest distance. The platform lets a marketer define a goal in plain language, points AI agents at live signals - churn risk, an inventory swing, the weather, a social trend - and fires off adaptive campaigns without a copy of the data ever leaving the company's cloud warehouse. Built natively on Snowflake, it is a customer data platform that answers to the marketer instead of the other way around. One early deployment, with SeatGeek, reported a 70% lift in how well events matched to the right fans.
What makes him worth reading about is not the funding tally, though it is healthy - roughly $117.8 million, including a $54 million Series D led by Macquarie Group in August 2023. It is that he has been circling the same conviction for fifteen years and finally has the tools to act on it.
Agentic AI is changing how marketing gets done, representing the biggest shift since the move to SaaS and cloud computing.JASON DAVIS · ON THE 2025 REBRAND TO SIMON AI
The origin, in reverse
Rewind to 2009. Davis had built Adtuitive, a retail ad-tech startup good enough that Etsy did not just license it - it bought the whole company to run its own advertising. That is the kind of acquisition that tells you something. You do not purchase a team to power your core systems unless the team is the asset.
Then came the part that mattered more than the exit. Davis stayed at Etsy for three years and ran the search and data teams - data science, analytics, the big-data plumbing. He arrived the year the marketplace sold roughly $180 million in goods. He left it humming at a run rate north of a billion dollars. Somewhere in that climb, watching one of the internet's great marketplaces wrestle with its own information, he found the next company.
The frustration was specific and it stuck with him. Data scientists were building models that never became outcomes. Companies were pouring money into infrastructure they could not actually use. The data existed. The marketers who needed it could not reach it. “Data transfer,” he has said, “is a much ignored topic” - a sentence that sounds like nothing until you have watched a quarter of work die in the gap between a warehouse and a campaign.
So in 2015 he started Simon Data with Matt Walker, a friend from the UT Austin PhD trenches, where they had both been buried in machine learning. Two data scientists who decided marketers should not need to file a ticket with engineering to ask their own data a question.
The receipts
Machine learning, data mining and statistics at UT Austin. Meets future co-founder Matt Walker.
Writes search algorithms - learning what data looks like at scale.
His retail ad-tech startup is acquired to power Etsy's advertising.
Leads search, data science and infrastructure as the marketplace passes $1B run rate.
Co-founds the CDP with Matt Walker to put data in the marketer's hands.
Macquarie Group leads; total funding reaches ~$117.8M.
Launches the agentic marketing platform and rebrands AI-first.
The machine
A goal-based workspace where marketers describe what they want in plain language, then reuse Blueprints, AI Fields and AI Moments to launch adaptive campaigns.
Purpose-built systems that detect signals - churn, inventory, weather, social trends - turn raw data into campaign-ready attributes, and orchestrate across channels.
A cloud-native foundation on Snowflake. Zero-ETL personalization on live signals, with enterprise governance - the data never has to leave home.
“Data transfer is a much ignored topic.”
- JASON DAVIS, ON THE GAP BETWEEN WHERE DATA LIVES AND WHERE IT'S NEEDEDQuirks & footnotes
The links