Mergers & Acquisitions

FarmX Acquires Amos Power to Expand AI-Powered Autonomous Farming Platform

FarmX announced the acquisition of Amos Power, a company specializing in fully electric autonomous tractor technology, alongside new funding to accelerate the global rollout of its AI-powered farming platform.
Image provided by FarmX.

Key Takeaways

  • FarmX acquired Amos Power, a developer of fully electric autonomous tractor technology.
  • The acquisition supports FarmX’s strategy to build a vertically integrated AI-driven agriculture platform.
  • FarmX also secured additional funding to accelerate global deployment and manufacturing.
  • The combined platform integrates AI, machine learning, computer vision, autonomy, and electric machinery.
  • Integrated production deployments are expected to begin following a unified roadmap in 2026.

FarmX Strengthens AI Agriculture Platform With Amos Power Acquisition

FarmX announced the acquisition of Amos Power, a company specializing in fully electric autonomous tractor technology, alongside new funding to accelerate the global rollout of its AI-powered farming platform. The move advances FarmX’s strategy to deliver a vertically integrated, data-driven agriculture system that combines artificial intelligence, machine learning, autonomy, and electric farm equipment.

By integrating Amos Power’s electric tractor platform with FarmX’s computer vision, machine learning, and autonomy stack, FarmX aims to create an end-to-end AI agriculture platform capable of continuous operation. The combined system is designed to learn from every field activity and improve performance over time through real-time perception, sensor fusion, and crop-level analytics.

“In a world being reshaped by AI, we are building a truly data-driven AI agriculture platform,” said Tushar Dave, Chief Executive Officer of FarmX. “By combining electric autonomous machinery with FarmX’s AI, machine learning, and vision-based intelligence, we are creating systems that don’t just automate tasks, but learn from the farm, adapt to changing conditions, and continuously optimize how food is produced.”


FarmX Expands Autonomous Capabilities Beyond GPS-Based Systems

The company stated that its AI-driven perception technology enables reliable autonomous navigation, obstacle detection, row following, and task execution across a wide range of agricultural environments. These include orchards, vineyards, row crops, indoor operations, and other settings where GPS signals may be unreliable or unavailable.

For existing Amos Power customers, the integration is expected to significantly expand autonomous functionality beyond traditional GPS-dependent workflows. The system continuously generates operational data that can be used to refine models and improve decision-making over time.

According to FarmX, the platform’s ability to operate in GPS-challenged environments is a key differentiator as farms seek greater automation across diverse production systems.


Funding, Manufacturing, and Global Expansion

Alongside the acquisition, FarmX secured additional funding to support platform integration, enhance customer support, and scale manufacturing and deployments worldwide. The company has expanded its international footprint across India, Japan, and Australia, and has established strategic partnerships for high-volume manufacturing.

FarmX stated that its manufacturing strategy enables localized production to meet regional demand while supporting a faster global rollout as adoption increases. The company expects integrated production deployments of the combined FarmX and Amos Power platform to follow a unified development roadmap beginning in 2026.


FarmX Positions for Scalable, Data-Driven Farming Systems

Through the acquisition of Amos Power and continued investment in AI-driven autonomy, FarmX aims to position itself as a provider of scalable, intelligent farming systems that combine electric machinery with adaptive software. The company stated that the integrated platform is designed to support long-term productivity improvements by enabling farms to automate operations while continuously learning from real-world field data.

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