In the rapidly advancing world of autonomous vehicles, a crucial aspect often overlooked is tire health. Korean startup BANF is changing that with its innovative hardware and software solution, which monitors tire pressure, temperature, tread wear, wheel alignment, and lug nut stability. The system, which uses machine learning to analyze data, provides insights not only on tire health but also on cargo load measurement and road surface conditions.

BANF's technology is particularly significant in the context of autonomous trucks, which aim to operate 24/7, putting immense stress on tires. The startup's solution can help reduce fuel consumption and tire maintenance costs by up to $4,500 per truck annually. With a growing presence in Korea, China, and the US, BANF is poised to make a significant impact in the industry.

The company's triaxis sensor, mounted to the inner liner of the tire, measures motion and forces along three axes, providing a comprehensive picture of tire health. The sensor data is transmitted to a smart profiler, which acts as a transmitter, receiver, and charger, facilitating real-time monitoring and analysis.

BANF has already collaborated with major industry players, including Volvo Group, Hyundai Motor Group, and DHL, and is working with US tire manufacturers to commercialize its technology. With a $5 million pre-Series A funding round last year and a $12 million Series A round in the pipeline, BANF is gearing up for a potential IPO on Korea's stock exchange in 2027, followed by a US Nasdaq listing.