Uber and Autobrains announced a landmark strategic collaboration to launch a commercial robotaxi program in Munich, Germany. The landmark venture natively unifies Uber’s global ride-hailing network, Autobrains’ breakthrough agentic autonomous driving intelligence, and the production-ready NVIDIA DRIVE Hyperion™ Level 4 computer architecture to pioneer a highly scalable framework for autonomous urban mobility.
Munich Selected as the First European Testing Ground
The robotaxi system, once receiving all final regulatory clearances, will see Munich as its primary deployment location. Being one of the most advanced cities when it comes to automobile industry and technology, Munich presents the perfect platform for operational trials. It brings together challenging urban streets, high-speed autobahns, and innovative legislation from Germany concerning Level 4 automation, thus creating a reliable basis for further expansion.
Unlike conventional AV projects, which demand extensive customization of the vehicles, prohibitively costly sensory systems, and restrictive computer configurations, the present project employs an approach that is entirely agnostic of the OEMs. Its design makes it deployable to various vehicle types from diverse automobile companies, making the cost of entry significantly lower.
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The Architecture of Agentic Driving Intelligence
At the heart of the partnership is a modular approach to vehicle decision-making. While traditional AV stacks lean heavily on a single, massive, end-to-end neural model to navigate roads, Autobrains’ Agentic AI divides the driving task into an ecosystem of specialized, context-aware AI agents.
How the Agentic Framework Optimizes Autonomous Fleets:
Context-Driven Reasoning: Individual agents focus on distinct driving dimensions, continuously evaluating environmental anomalies and calculating real-time safety maneuvers.
Standard Sensor Compatibility: The software is optimized to run on standard, assembly-line automotive sensor configurations, avoiding custom retrofits.
Compute Efficiency: The modular framework requires significantly less processing power, allowing it to maximize the performance of onboard automotive chips without draining vehicle battery reserves.
This approach creates a turnkey, commercially viable path for global automakers to instantly convert their standard electric or internal combustion vehicles into autonomous robotaxis, gaining immediate access to Uber’s global passenger marketplace and fleet management routing.
“Autonomous driving will not scale by relying on a single model to solve every driving scenario,” said Igal Raichelgauz, CEO and Founder of Autobrains. “It requires systems that can reason, adapt, and make decisions under uncertainty. With Uber and NVIDIA, we are bringing this approach into autonomous ride-hailing – combining Agentic AI with the mobility platform and automotive compute needed to support scalable robotaxi operations across cities, vehicles, and real-world conditions.”
“For automakers and autonomy developers, the challenge is not just building autonomous vehicles – it’s bringing them into a commercial network where they can reliably serve riders at scale,” said Sarfraz Maredia, Global Head of Autonomous Mobility & Delivery at Uber. “This program creates a new path to do that by combining vehicle-agnostic autonomy, leading AI compute, and Uber’s ride-hailing platform.”
“Robotaxi services require high-performance AI compute, a robust autonomous driving architecture and a path to deployment across real vehicle platforms,” said Rishi Dhall, vice president of automotive at NVIDIA. “By combining NVIDIA DRIVE Hyperion with Autobrains’ Agentic AI and Uber’s global mobility network, this collaboration can help accelerate the development of safe, scalable, software-defined autonomous ride-hailing fleets.”
