Chip Ganassi Racing partners with OpenAI to optimize IndyCar setups

Chip Ganassi Racing partners with OpenAI to optimize IndyCar setups

The IndyCar powerhouse is feeding sensor data from its cars into OpenAI's models to sharpen setups, strategy, and pit work

Racing used to be a sport of gut feel, grease, and a guy with a clipboard. Chip Ganassi Racing would now like to add a large language model to that list.

The IndyCar team and OpenAI announced a research collaboration on February 28, 2025. Both sides described it as the first partnership of its kind for either organization. The goal is to turn an enormous stream of race data into faster, smarter decisions, both on track and off it.

A billion data points and a very busy pit wall

Every IndyCar run by the team carries more than 200 sensors. Together, they produce nearly one billion data points per hour.

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The collaboration targets several areas at once. These include car setups, race strategy, pit stop performance, and even front-office operations.

By 2026, the relationship had grown beyond the lab. OpenAI became a primary sponsor on the No. 10 car for select races driven by Alex Palou. Those included events in Long Beach and Washington, D.C.

Palou’s results during this stretch have done the partnership no harm. His run included multiple championships and the 2025 Indianapolis 500.

How a tech giant ended up at the racetrack

The partnership traces back to a single connection. OpenAI researcher Joyce Ruffell first got to know the team at a Women in Motorsports event. She went on to play a central role in building the collaboration.

The other key names are familiar. OpenAI CEO Sam Altman and team owner Chip Ganassi are both tied to the effort. Ganassi’s operation brings serious pedigree, with 17 championships in its history.

The collaboration has also become content. A documentary series titled “R&D” follows the project and shows how the technology is being used.

Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our Editorial Policy.
Chip Ganassi Racing partners with OpenAI to optimize IndyCar setups
Chip Ganassi Racing partners with OpenAI to optimize IndyCar setups

The IndyCar powerhouse is feeding sensor data from its cars into OpenAI's models to sharpen setups, strategy, and pit work

Racing used to be a sport of gut feel, grease, and a guy with a clipboard. Chip Ganassi Racing would now like to add a large language model to that list.

The IndyCar team and OpenAI announced a research collaboration on February 28, 2025. Both sides described it as the first partnership of its kind for either organization. The goal is to turn an enormous stream of race data into faster, smarter decisions, both on track and off it.

A billion data points and a very busy pit wall

Every IndyCar run by the team carries more than 200 sensors. Together, they produce nearly one billion data points per hour.

Advertisement

The collaboration targets several areas at once. These include car setups, race strategy, pit stop performance, and even front-office operations.

By 2026, the relationship had grown beyond the lab. OpenAI became a primary sponsor on the No. 10 car for select races driven by Alex Palou. Those included events in Long Beach and Washington, D.C.

Palou’s results during this stretch have done the partnership no harm. His run included multiple championships and the 2025 Indianapolis 500.

How a tech giant ended up at the racetrack

The partnership traces back to a single connection. OpenAI researcher Joyce Ruffell first got to know the team at a Women in Motorsports event. She went on to play a central role in building the collaboration.

The other key names are familiar. OpenAI CEO Sam Altman and team owner Chip Ganassi are both tied to the effort. Ganassi’s operation brings serious pedigree, with 17 championships in its history.

The collaboration has also become content. A documentary series titled “R&D” follows the project and shows how the technology is being used.

Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our Editorial Policy.