Mbodi AI: Teaching Robots Through Natural Language
In the heart of the global manufacturing industry lies a mounting crisis — a severe shortage of labor and an overwhelming demand for adaptable, efficient automation. Over 70% of factories worldwide report labor shortages. At the same time, current industrial robots struggle to keep pace with constantly shifting production requirements. Traditional systems demand week-long reprogramming cycles by teams of engineers, rendering them too rigid and costly to adapt to frequent changes.
Billions of dollars in high-variation manufacturing tasks remain untouched by automation. The core issue? Robots lack the flexibility and responsiveness of human workers. While automation has revolutionized static, repetitive tasks, it’s left behind a vast category of dynamic operations that require frequent tweaking, nuanced control, and adaptability — a limitation that costs companies productivity, efficiency, and growth.
Mbodi AI was born to close this “automation gap,” empowering robots to become as adaptable as human labor — but without the constraints.
How Does Mbodi AI Make Robots Smarter?
Mbodi AI is building an embodied AI platform — one that fuses the cognitive intelligence of large language models with the physical capabilities of industrial robots. The startup’s vision is bold yet simple: let anyone teach robots new skills using plain natural language and short demonstrations, no engineering expertise or coding required.
At its core, Mbodi’s technology is powered by a combination of:
- Generative AI for interpreting natural language and task intent
- Agent orchestration to dynamically coordinate robotic behavior
- Symbolic reasoning for planning and execution in real-world contexts
Once a user gives a verbal command, Mbodi’s platform interprets the instruction, understands the robot’s surroundings, and orchestrates the necessary actions — all within seconds. The result is a precise, safe robotic behavior that’s production-ready almost immediately.
Even more impressively, learned behaviors can be shared across an entire robotic fleet. If one robot learns how to pack boxes or sort components, that skill can be instantly propagated to others, unlocking unprecedented levels of scale and reuse.
What Makes Mbodi’s Platform Different From Traditional Robotics?
Traditional automation systems are inflexible. Teaching a robot a new task often involves:
- Hiring or contracting specialized engineers
- Spending days or weeks on coding and calibration
- Testing and debugging on-site
- Creating task-specific programs for each machine
Mbodi throws this approach out the window. Instead, it delivers:
- Zero-code programming: Just speak or demonstrate the task.
- Real-time adaptability: Robots learn and re-plan in seconds.
- Fleet-wide knowledge: Learned tasks are shared across systems instantly.
- Hardware-agnostic compatibility: Works across different robot brands and factory environments.
This human-like learning loop allows Mbodi-powered robots to be more than just machines — they become intelligent co-workers capable of collaborating with humans in dynamic, high-mix production environments.
How Is Mbodi AI Being Used in the Real World?
Mbodi isn’t just a prototype or a research project — it’s on track for real-world deployment through a joint commercialization agreement with ABB Robotics, one of the world’s leading industrial robot manufacturers. This partnership was born after Mbodi won ABB’s prestigious global AI Startup Challenge, beating out hundreds of startups.
Together, Mbodi and ABB are preparing to launch the first-of-its-kind embodied AI deployments in industrial settings. These use cases will prove that adaptable, conversational robot training isn’t just futuristic — it’s operational today.
This step marks a critical milestone: bringing AI-powered, human-trainable robots from the lab to the factory floor.
Who Are the Founders Behind Mbodi AI?
Mbodi’s founding duo blends deep technical expertise with a shared mission: to free robots from brittle programming constraints.
- Xavier (Tianhao) Chi: Former tech lead at Google Public DNS (8.8.8.8), one of the internet’s most critical services. With a strong background in electrical and computer engineering from UIUC, Xavier has engineered high-scale infrastructure systems and now applies that rigor to embodied AI.
- Sebastian Peralta: A polymath with backgrounds in electrical engineering, computer science, and physics from UPenn. He also conducted graduate-level research in robotics at the GRASP Lab and previously worked at Google Public DNS. Sebastian brings a multidisciplinary approach to robotics and deep learning.
Their shared insight? Robotics had been held back by outdated programming methods and lacked the intelligence layer necessary to keep up with human-paced work. Mbodi AI is their answer to that problem.
Why Does Embodied AI Matter Now?
We’re entering an age where physical systems — from factory robots to autonomous vehicles — need to operate with the fluidity and contextual understanding of humans. But while AI models have made huge strides in language, vision, and reasoning, robotics has lagged behind due to the difficulty of interfacing these models with the physical world.
Embodied AI bridges this gap. It enables systems to perceive, plan, and act in real-time physical environments — using the same language and cues that humans rely on. With platforms like Mbodi, this intelligence becomes accessible, scalable, and production-ready.
And the timing couldn’t be better: with labor shortages intensifying and global supply chains under strain, manufacturers are desperately seeking more agile automation solutions.
What is Mbodi’s Vision for the Future?
Mbodi envisions a future where robots are as teachable and flexible as software — instantly programmable, endlessly adaptable, and widely accessible. Just as cloud computing democratized access to computation, Mbodi aims to democratize access to physical automation.
In this world, a warehouse manager could teach robots new tasks verbally. A production line could evolve overnight without downtime. Entire factories could reconfigure their robotic workforce on the fly, without engineers, consultants, or code.
This paradigm would unlock a new era of hyper-agile manufacturing, where productivity scales without friction, and small teams can do big things.
What’s Next for Mbodi AI?
With a foundational partnership in place and a robust platform already demonstrating real-world value, Mbodi’s next chapter is focused on scaling deployments, refining use cases, and continuing to blur the line between software agents and physical robots.
From electronics assembly to custom packaging, high-variation tasks that were previously too complex for automation are now well within reach. And as Mbodi’s agents grow smarter, their capacity to handle increasingly nuanced instructions will only improve.
In short, Mbodi isn’t just teaching robots to work — it’s teaching them to think, learn, and collaborate.
Conclusion
Mbodi AI is at the forefront of an industrial revolution, powered by embodied intelligence. By merging natural language, generative AI, and robotic control, they’re building a platform that makes automation smarter, faster, and dramatically more accessible.
In a world where agility is king and labor is scarce, Mbodi’s promise of production-ready robot training in minutes might just redefine the future of work.