"Mbodi wants to make training robots easier and quicker with the help of AI agents. The company will be showcasing this tech as one of the Top 20 Startup Battlefield finalists at TechCrunch Disrupt 2025. New York-based Mbodi built a cloud-to-edge system, a hybrid computing system using both cloud and local compute, that is designed to integrate into existing robotic tech stacks. The software relies on a multitude of AI agents that communicate with each other to gather the needed information to help a robot learn a task faster."
"Xavier Chi, co-founder of Mbodi, told TechCrunch that users prompt the software using natural language, and Mbodi breaks down the request into smaller subtasks. Mbodi's cluster of agents essentially divides and conquers the task to gather the needed information to train the robot on the prompt quickly. Once deployed, Mbodi will collect data and learn from its real-world use cases."
""The tricky thing with the physical world, it's infinite possibility," Chi said. "Every time you can invent something completely new, you haven't had any data, that is a problem in the physical world. We always need to have a system where you can orchestrate different models or have anyone correct a robot and tell it to do certain things certain ways.""
Mbodi built a cloud-to-edge hybrid system that integrates with existing robotic tech stacks and relies on a cluster of AI agents that communicate to accelerate robot training. Users prompt the software in natural language and the system decomposes requests into smaller subtasks, allowing agents to divide-and-conquer the information needed to train specific movements or tasks. Deployed systems collect real-world data and continue learning from use cases. The founders identified a shortage of fast, generalizable robot training methods despite advances in AI for physical systems. The platform aims to reduce task-specific training overhead and enable quicker adaptation in real-world scenarios.
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