RightHand Robotics

RightHand Robotics develops autonomous piece-picking systems centered on the RightPick platform. The system uses AI and machine learning to handle SKU-agnostic picking tasks, claiming cycle times as fast as 3 seconds per pick-and-place operation. The core value proposition is data-driven generalization: rather than programming per-SKU grasp strategies, the platform aims to handle the long tail of item shapes, sizes, and materials encountered in real fulfillment environments across e-commerce, electronics, apparel, grocery, and pharmaceutical verticals.

The company has accumulated over a petabyte of operational data from field deployments, which feeds back into its perception and manipulation models. RightPick systems are designed to operate continuously (24/7) and integrate into both new and existing warehouse workflows. Deployment is handled through a partner integrator program, and the company serves customers globally. For engineers, the interesting problems sit at the boundary of vision, grasp planning, and motion control under the constraints of unstructured item variability and tight cycle-time budgets.

Technical work spans the full robotics stack - perception, learning-based manipulation, and system-level integration - within a company focused on machine learning, AI, and data-driven automation. The engineering challenge is less about any single capability and more about making the full pipeline robust enough to handle millions of distinct SKUs in production, sustained over continuous operation, with the accumulated dataset serving as both training fuel and a feedback loop for reliability improvements.