Bonsai Robotics Introduces New Weeding and Spraying Integrations for Amiga System

If field results correspond with stated objectives, such integrations may support more targeted input application while maintaining operational throughput

By Ambuj Sharma
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Bonsai Robotics Amiga

US agritech startup Bonsai Robotics has introduced four new autonomous solutions on its Amiga platform at World Ag Expo, expanding its capabilities in specialty crop operations. The company said the updates include partnerships with WEED-IT, Carbon Robotics, OnTarget Spray Systems and Interlink Sprayers to support precision spraying and automation functions.

Bonsai Robotics has also stated that its Amiga Max system has been named a recipient of the 2026 Top 10 New Product Award at the event. According to the company, the integrations are intended to help reduce herbicide use, water consumption and operational costs, and the Amiga platform has been trained on data from more than 750,000 acres globally.

Specialty crop growers are under more pressure than ever to do more with fewer people and tighter margins. With these new partnerships, we’re delivering affordable, high-performance autonomy for some of the most labor-intensive, high-value tasks on the farm.
Tyler Niday, Co-Founder and CEO, Bonsai RoboticsTyler Niday, CEO, Bonsai Robotics

Bonsai Intelligence is described by the company as a vision based, AI driven system that relies on real world operational data rather than primarily on GPS inputs. The platform is designed to support planning, tracking and equipment management across machinery from multiple manufacturers through a single interface.

The company has identified spraying and weeding as operational tasks with defined parameters that lend themselves to autonomous deployment. The platform is intended to improve precision and consistency while enabling use across different crop types and equipment configurations.

Platform Integrations and Deployment Strategy

Bonsai Robotics stated that the new partnerships are intended to support operational efficiencies through continuous autonomous operation and electric or hybrid system configurations.

The Amiga Flex has been integrated with the WEED-IT Precision Sprayer, which uses chlorophyll detection technology to enable targeted herbicide application.The Amiga Max has also been paired with the Carbon Robotics LaserWeeder for in-field laser-based weed control demonstrations.

Also read: Claas Invests in Pheno-Inspect for AI-Based Field Analytics Capabilities

In addition, both and Amiga Flex systems are compatible with electrostatic sprayers from OnTarget Spray Systems, designed to reduce water usage and improve daily acreage coverage.The Amiga Max can also be configured with a single row power tube sprayer from Interlink Sprayers, developed for vineyard and trellis-style crop applications.

According to Bonsai Robotics, the system has been trained on data from more than 750,000 acres spanning different continents and crop environments. The company states that its autonomy solutions are built to function in field conditions such as dust, debris and reduced visibility.

Bonsai Robotics added that the expanded Amiga platform is structured to enable phased deployment of autonomous capabilities, allowing growers to scale adoption across crop types and equipment over time.

Autonomy Expands in Specialty Crops

The expansion of autonomous capabilities on the Amiga platform by Bonsai Robotics reflects a broader shift toward modular automation in specialty crop agriculture. Rather than introducing fully integrated, single purpose systems, the approach appears to centre on interoperability with existing spraying and weeding technologies. This could allow growers to adapt automation within established machinery ecosystems instead of replacing equipment entirely.

A vision based autonomy model developed by Bonsai Robotics, which relies more heavily on real world operational data than GPS, may offer advantages in complex field environments, particularly in orchards and vineyards where canopy cover and terrain variability can affect satellite signals. At the same time, performance consistency across diverse geographies and crop types will likely depend on continued data inputs and local calibration.

The emphasis by Bonsai Robotics on herbicide and water reduction aligns with increasing regulatory and cost pressures in specialty crop production. If field results correspond with stated objectives, such integrations may support more targeted input application while maintaining operational throughput.

However, adoption of Bonsai Robotics systems may hinge on capital investment requirements, compatibility with existing workflows and the availability of technical support. Growers could approach autonomy incrementally, weighing potential efficiency gains against operational risk and long term return considerations.

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