Tayo Adesanya spent nearly 12 years working with microchips and AI processors, helping large manufacturers decide which chips to use in their hardware. He launched Lola Vision Systems in 2024 as a bet on where the AI computing market was headed. "Starting Lola Vision Systems was a bet on where the world was headed and what I was seeing," he said.
The company builds software and chips for running AI models on devices. Its core product is software that translates AI models into instructions a specific chip can run, which Adesanya calls a "compiler toolchain." He says manually setting up an AI model on new hardware can take roughly 200 hours just to begin testing. Lola Vision says it has rebuilt that software layer and is also developing its own semiconductor chips. A client provides its code and the AI model it wants to use, whether custom-built or open source, and the software translates both into instructions the client's chip can execute.
"Speed is only part of it," Adesanya said. Faster setup gives aerospace and other mission-critical companies time to "run more accurate models on their own data, at a lower power." He added that for these customers, "accuracy and reliability aren't nice to have. They determine whether a product passes regulatory review and whether it works reliably in the field."
Lola Vision is one of several startups trying to offer an alternative to Nvidia's technology for running AI on devices. Adesanya said many companies start with Nvidia's Jetson line of compact computing modules or with open source AI models, which he claimed often break or run poorly out of the box, leaving teams to spend days or weeks getting them to work.