AJ Rios's Mission to Build Sidecar: The Operating System for Modern Data Teams

The data team has become one of the most important functions in the organization. Better data helps leadership make better decisions, and as developing AI insights has become a priority for many companies, the data team is often principally responsible for turning the organization’s data assets into AI solutions. 

But many data teams, especially smaller ones, are drowning. They’re stuck managing multiple tools and handling ad hoc requests, making it difficult to scale with the organization.

Having spent years as a data engineer himself, AJ Rios felt these pains first hand. He wanted to build a solution that would help data engineers deliver value to the business while also getting their time back. So he teamed up with co-founder James Webb and set out to build Sidecar.

Introducing Sidecar: The Operations System for the Data Team

Sidecar automates operations for data teams, enabling teams of all sizes to maximize their impact and increase efficiency. Offering a suite of tools related to data quality, cataloging, governance, and activation, the platform helps data engineers complete workflows without having to juggle multiple tools or maintain custom tooling. 

Having spent years working on data teams both small and large, AJ experienced how the lack of reliable data operations can make it difficult to support the organization. “Many data teams that I’ve seen, and that I’ve worked on, are under water,” AJ explains. “They’re at risk of burning out, waiting for that next hire. A lot of the reason for that is because they’re context switching all the time.”

By helping reduce tech debt and improve data platform health without having to switch from tool to tool, Sidecar allows data teams to get back to what they do best—supporting leaders to make day to day decisions. 

And data health isn’t just important for data engineers’ sanity, it’s also critical for successful AI outcomes. Sidecar unifies, synthesizes, and structures data before it’s served to LLMs, allowing teams to reduce the amount of context needed to produce quality results. 

By enabling teams to create a more efficient data operating system, Sidecar is helping customers save as much as 25% on data platform costs and onboard new team members 70% faster.

AJ’s Journey to Sidecar

AJ was born in Guam, and grew up immersed in the small, tight-knit community on the island. Though he loved growing up there, he soon became troubled by Guamanians’ patterns of poor health, many of which were due to behavioral patterns driven by the island’s colonial history. 

As he began to make plans for college, AJ aspired to become a doctor and improve public health for his community and beyond. But when he arrived at Stanford for his undergrad, he quickly became inspired by the power of software and the impact it could have on behavioral change. So he decided to take a different path, shifting his focus to engineering and spending six years as a data engineer after graduating. 

“Data was a perfect place to learn to become a founder,” describes AJ. “I could support executives in decision making with data. And I was also building cool stuff while also building infrastructure. Those six years really inspired me to support those data teams because I saw really big problems with the way we operated.” 

As AJ’s career progressed, he stayed in touch with his college roommate and close friend, James Webb, who himself was working as a data scientist at leading tech companies. AJ and James soon began riffing on the aspects of the data process that they were struggling with. Before long, they’d identified the key problems holding data teams back, and set out to build Sidecar to solve them.

Now, just two years later, Sidecar has grown to a team of five and is supporting customers like Ophelia, Skylight, Bark, and Aurora Solar.

AJ’s Advice for Fellow Founders

One of the key factors that has helped the Sidecar team design an effective solution, AJ believes, is being able to draw on years of experience working on data teams themselves. 

“There’s a lot of value in founder market fit,” AJ explains. “I’ve run into these problems and had to solve them before, largely in a manual way. When we go through our product development cycles, we know how we would want it.”

That being said, it’s critical to validate your intuitions with market research and customer discovery, he notes. “You can get caught in a trap, too. Perhaps our experience isn’t representative of the market. So it’s important to do customer discovery as well.”

And as you navigate your founder journey, or even if you aspire to become a founder in the future, AJ emphasizes that you should always prioritize kindness and curiosity. If you meet a ton of people, and are supportive and kind to those people, you’ll be way better off in the future.” 

To learn more about AJ’s journey, you can follow him on LinkedIn and visit sidecardata.com.