inDrive to test robotaxis in Kazakhstan with Pony.ai and Nvidia

A new partnership for robotaxis

The ride-hailing company inDrive has signed a memorandum of understanding to explore bringing autonomous vehicles to its platform. The company plans to begin testing these robotaxis in Kazakhstan starting in the first half of 2027. This initiative represents a growing trend of self-driving technology expanding into regions outside of the United States and China.

To make this happen, inDrive is teaming up with two major technology firms. Chinese autonomous driving company Pony.ai will provide the Gen-7 robotaxis vehicles for the project. Meanwhile, the American chipmaker Nvidia will supply the underlying artificial intelligence technology required to power the cars.

The tests are scheduled to take place in Astana, the capital of Kazakhstan. According to inDrive CTO Yuri Misnik, the initial phase of the project will involve a safety operator inside the vehicle. The ultimate goal for the partnership is to achieve fully driverless rides on the city streets.

The technology behind the fleet

Nvidia will provide the essential computing infrastructure for the robotaxis through its Hyperion platform and Halos safety system. These tools are designed to provide a ready-made foundation of sensors and computing power. By using these existing systems, companies can avoid the high costs of building and integrating every component from scratch.

The company also provides tools to generate synthetic data, which is computer-generated information used to train AI. This allows the systems to practice driving in a wide variety of scenarios before they ever hit a real road. These capabilities are intended to help developers create safer and more reliable autonomous systems.

Nvidia's approach is specifically aimed at making autonomous services more affordable in emerging markets. Ali Kani, Nvidia's vice president of automotive, noted that these cost savings are important for competing in regions where ride-hailing is already relatively cheap. The goal is to ensure that autonomous technology remains accessible to a broader range of users.

Testing in harsh conditions

Kazakhstan has already expressed interest in autonomous transport by announcing plans to launch such services in 2027. The government has introduced specific rules to allow for the testing of autonomous vehicles on certain public roads. This regulatory environment is a key requirement for inDrive as it looks to expand its reach into new territories.

One of the primary reasons for choosing Astana as a test site is the city's challenging weather. The capital faces months of snow and ice during the winter, which creates difficult obstacles for autonomous driving sensors. inDrive founder and CEO Arsen Tomsky stated that the project provides an important opportunity to evaluate technology in these specific conditions.

Success in Astana is expected to provide valuable insights for other regions that face similar weather patterns. If the technology can navigate the harsh Kazakh winters reliably, it could prove its viability for other parts of the world. This serves as a practical proving ground for the durability of the Pony.ai hardware and Nvidia's software.

A global expansion strategy

This project is part of a broader strategy for inDrive to integrate autonomous vehicles into its global network. The company currently operates in more than 1,200 cities across 47 different countries. It has also expanded its business beyond simple ride-hailing into delivery services, intercity transport, and financial products.

The company is pursuing similar deals in other parts of the world to build its autonomous fleet. In December, inDrive signed a separate agreement with Saudi Arabia's AI Driver to explore vehicles powered by the Chinese firm WeRide. That specific project is targeted for a pilot in Riyadh during the first half of 2026.

By working with different partners in different markets, inDrive describes its approach as capital-light by design. This means the company focuses on providing the platform and local expertise while others provide the specialized hardware and AI. This model allows them to scale quickly without having to own and maintain the entire manufacturing chain for the vehicles.