Amazon acquires robotics startup Rivr

Amazon has acquired Rivr, an autonomous robotics startup based in Zurich, in a transaction that highlights the e-commerce giant’s focus on doorstep delivery. The financial terms of the acquisition deal were not disclosed. Marko Bjelonic, the co-founder and CEO of Rivr, announced the transaction on LinkedIn, following an initial report of the deal by the publication The Information. According to Bjelonic, the acquisition will “accelerate our vision of building General Physical AI through doorstep delivery, bringing robotics and AI closer to real-world deployment at scale.” In practical terms, the acquisition is intended to leverage Amazon’s resources to deploy Rivr’s robotics technology to more doorsteps.

Prior to the acquisition, Rivr had already attracted financial backing from entities associated with Amazon. The startup’s funding history includes:

• Seed round: Rivr closed a $22.2 million seed round in 2024.
• Total funding: The startup raised a total of $25 million.
• Last valuation: Rivr was valued at $100 million during its last private valuation.

The Amazon Industrial Innovation Fund and Bezos Expeditions participated as investors in the startup’s funding rounds.

Rivr is known for developing a specialized stair-climbing delivery robot. Bjelonic, who once described the four-legged wheeled robot as a “dog on roller skates,” had previously sought to test the technology in real-world environments. To do so, the startup launched a pilot program in Austin with Veho, a package delivery company. At the time of the pilot, Bjelonic stated that he hoped to learn from the partnership and eventually scale the company’s fleet to 100 bots by 2026. However, it remains unclear if the startup ever reached the milestone of 100 bots before the acquisition took place. TechCrunch reached out to Rivr for comment regarding the acquisition.

Why it matters

The acquisition signals Amazon’s continued push into autonomous last-mile logistics, leveraging Rivr’s specialized robotics to bridge the gap between AI research and real-world deployment.