In the Wake of His Wife’s Death, Adtech Founder Finds New Energy in Austin

Gabe Lozano reimagined his product, rebranded the company and is now opening a new office on East 6th Street.

Written by Jeff Rumage
Published on Apr. 19, 2022
In the Wake of His Wife’s Death, Adtech Founder Finds New Energy in Austin
After his wife’s death in 2020, Decide CEO Gabe Lozano went on a road trip that brought him to La Luz Trail in Albuquerque. He eventually landed in Austin, where he opened a second office for his adtech startup Decide. | Photo: Gabe Lozano
Decide CEO and co-founder Gabe Lozano. | Photo: Gabe Lozano

After the death of his wife Rachel in February of 2020, Gabe Lozano took a couple of months to regroup until one day in July he decided to leave St. Louis with the hope of finding “the energy to participate again,” he said.

More than five months, 15,000 miles and 25 cities later, Lozano said he found that renewed sense of energy within the first couple hours of setting foot in Austin. Now, his adtech company is opening an office here.

“It is really hard to describe, other than I felt energetic,” he told Built In.

The next day, he bought a laptop and a keyboard and got to work. With a renewed sense of creativity and some new perspective, Lozano began to rethink the possibilities of his online advertising company.

Lozano founded Lockerdome in 2008 as a sports-oriented social media platform, but it evolved into an online advertising company that uses data to determine where it should embed its clients’ interactive advertisements. Lockerdome rebranded to Decide in February.

With a new name and a new vision, the remote company is now launching its first office space outside of St. Louis. The 18,000-square-foot St. Louis office is currently used by half of the company’s employees.

Decide will soon launch its Austin hub in a two-story, 4,000-square-foot building at 1408 E. 6th St. Seven of the company’s 80 employees now live in Austin, and Lozano said that number may rise in the near future. 

Although the company is remote, Lozano said he would like a place for people to get together for social events and technical meetups on the first floor, where there is a bar, kitchen and “hangout space.” The second floor is reserved for people who want a productive space.

Lozano said he wants to create an environment that people will “opt in to,” similar to the way many remote professionals have opted to move to Austin.

Decide.co recently opened an Austin office.
Decide will soon open a two-story office at 1408 E. 6th St. | Photo: Decide

“People have asked me if the Austin office is about accessing talent, but that’s not really why we have an office here,” he said. “I want people to feel what it’s like to be in a small city that is surging.”

Lately, Lozano has been thinking about ways that machines could help people make more-informed decisions. This inspired him and his team to improve upon their AI models by crowdsourcing from multiple AI models.

“Instead of a couple of people in the company building our AI models, we wanted to create a platform where a lot of people can contribute models that compete against each other at the same time,” he said. “Now we have our full applied [machine learning] team that is working on this product collectively.”

Lozano’s team can now build, train, test and deploy a new AI model in a few minutes, although more novel models may take days. By crowdsourcing from multiple models, Lozano said the technology is able to make smarter decisions.

“It is difficult to build end-to-end AI models that work in the real world without human oversight,” he said. “But when you crowdsource a bunch of different models and make them compatible with human knowledge, then the collective system begins to work really well.”

Lozano and his crew have since built what they called the Decision Marketplace, which is used to run a large portion of its ad platform. In the future, Lozano said he hopes to explore the potential of crowdsourced AI decision-making technology in other industries.

“Having a machine navigate the last mile from a predictive knowledge state to a real-world decision — that’s something that we’re very interested in, in any capacity,” he said.

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