From lab to mass production: AgiBot and its pace

Company AgiBot was founded in 2023 in Shanghai by Peng Zhihui, a former technologist from Huawei. Within just three years, the company moved from research to serial production. According to data on its official website, in March 2026 it produced its 10,000th mass-produced humanoid robot, and analytical company Omdia ranked it in first place in worldwide humanoid robot deliveries for 2025.

At the AGIBOT Partner Conference 2026, the company declared this year as the beginning of the "deployment phase." This means it's no longer just about whether the robot can walk or pick up objects. The key is how well it can work in real environments, generate data, and improve during operation.

Sharebot: Netflix for robots?

The most striking novelty presented at the conference is the Sharebot platform. It is a global network for robot rental operating on the principle of Robotics-as-a-Service (RaaS). Instead of applicants buying hardware for hundreds of thousands or millions of dollars, they gain access to robots based on operational consumption.

The first wave of Sharebot deployment covers 14 countries, including the USA, United Kingdom, France, and Singapore. In China, AgiBot relies on thousands of local partners, while abroad it cooperates with regional distributors. This model lowers entry barriers for companies that want to try robotization without bearing full capital risk.

An interesting economic aspect is that service prices in overseas markets can be several times higher than in China. This creates margin not only for AgiBot but also for local service ecosystems that take care of the robots.

Seven standardized solutions

AgiBot structured its deployment into seven standardized solutions covering:

• industrial manufacturing,
• logistics and warehousing,
• commercial services,
• specialized operations.

These scenarios are already running in real operations — on production lines, in distribution centers, and commercial spaces. The goal is predictable behavior and repeatable performance, not a one-time technology demo.

Data as the new fuel: AIMA and hive network

Besides hardware, AgiBot is also building on software architecture. It introduced the AIMA (AI Machine Architecture) framework and the so-called hive data network — a network that collects operational data from deployed robots and feeds it back into development. Every deployed robot thus theoretically contributes to improving the entire fleet.

This approach resembles the development of large language models: the greatest value does not lie in an individual device, but in the aggregated data from the entire ecosystem. The more robots work in the field, the better the system learns to handle unexpected situations.

How does AgiBot compete with Western players?

In the field of humanoid robotics, they are not alone. American Figure AI focuses on logistics and manufacturing, Tesla is developing Optimus with the ambition of its own mass production, and Boston Dynamics remains the benchmark for mobility. However, AgiBot is pushing hard on deployment speed and vertical integration: own hardware, own models, own data.

While Western companies often rely on partnerships — for example, Apptronik with Google DeepMind — AgiBot is building a closed loop under one roof. This allows it to iterate faster and offer standardized solutions that are ready for immediate use.

What does this mean for the Czech Republic and Europe?

For Czech and European companies, the arrival of global RaaS platforms brings two messages. The positive one is reduced costs of robotization and the ability to test automation without investing in own hardware. The challenge is then dependence on Chinese supply chains and the question of how upcoming European regulation will deal with them.

The European market for humanoid robotics is still in its infancy. Although AgiBot does not specify a concrete timeline for expansion into the Czech Republic, its presence in France and the United Kingdom suggests that Central European markets are not excluded. For Czech manufacturers and logistics operations, the RaaS model could be an interesting way to compete with countries with a higher degree of automation.

In the context of the EU AI Act and considered rules for physical AI, it will be crucial to watch how European regulation deals with Chinese robots collecting operational data. Companies should think not only about the rental price but also about data localization and security certifications.

Where is physical AI heading?

With its approach, AgiBot shows that humanoid robotics is leaving the era of prototypes and entering the phase of industrial deployment. Renting instead of selling, a global service network, and operational feedback — these are the pillars of a new model that could change factory floors around the world within a few years.

Whether this model will also establish itself in Europe will depend on the speed of local adaptation, regulation, and companies' willingness to experiment with new forms of automation. One thing is certain: Chinese robotics companies are ceasing to be merely a cheap alternative — they are becoming defining players in the global market.