29 September 2026 | News
Image Courtesy: Public Domain : Dr. Ayman Ghoneim and Yu Liang sign the MoU on behalf of AFDE and Robbyant
Robbyant, an embodied AI company within Ant Group, and the Arab Federation for Digital Economy (AFDE) announced the signing of a Memorandum of Understanding (MoU) to advance the deployment, localization and commercialization of embodied AI and robotic solutions in the United Arab Emirates and the wider GCC (Gulf Cooperation Council) and Middle East markets.
The agreement was signed by Dr. Ayman Ghoneim, Assistant Secretary-General of AFDE, and Yu Liang, Head of Commercialization at Robbyant. The partnership establishes a structured mechanism to jointly advance embodied AI adoption across the Middle East, with collaboration spanning five strategic pillars.
AFDE selected Robbyant based on its full-stack technological capabilities native to embodied AI. In July 2026, Robbyant announced the release of the LingBot 2.0 series, a comprehensive model suite comprising LingBot-Depth 2.0, LingBot-Vision, LingBot-VLA 2.0, LingBot-World 2.0, LingBot-Video, and LingBot-VA 2.0. This series forms a complete, embodied-native “universal brain” that powers robotic perception, world simulation, and action. Notably, Robbyant’s LingBot-VLA 2.0 foundation model has achieved pre-training support for 20 distinct robotic embodiments across 17 hardware brands, demonstrating a strong engineering focus on generalization and multi-embodiment compatibility.
The company is also preparing to launch its proprietary cloud-based model toolchain platform, designed to better support model development, evaluation, and deployment for embodied AI applications.
Robbyant’s solutions are already being deployed in real-world commercial scenarios, including pharmacies, logistics facilities, and industrial machine tending. For instance, in collaboration with Guo Da Drugstore, the company has launched a “Smart Pharmacy” robotics solution powered by the LingBot 2.0 models. This deployment has significantly improved operational efficiency, particularly during peak hours and overnight shifts.