6 Monate, 5 Runden von Finanzierungen, insgesamt 2 Milliarden Yuan. Zhijian Dynamics wird das schnellste "Einhorn" im Bereich der Embodied Intelligence.

Recently, Simplexity Robotics announced that it has completed five consecutive financing rounds in less than half a year, with the total financing volume reaching 2 billion yuan. As a result, it has suddenly become the youngest unicorn in the sector. Light Capital served as the financial advisor for the latest financing round.

Five Rounds in Half a Year, First Official Announcement, All - Star Investor Matrix, Creation of the Most Competitive Financing Landscape

Simplexity Robotics, founded in July 2025, has carried out its first official presentation and announced the financing. Previously, there were almost no public news about it.

The financing list disclosed by Simplexity Robotics is impressive. It includes top - tier financing institutions and top - tier strategic investors. These financing institutions include: Vision Plus Capital, BlueRun Ventures, Sequoia Capital China, Legend Capital, CAS Star, Banyan Capital; the strategic investors are Tencent and Alibaba Group.

The simultaneous participation of Tencent and Alibaba as strategic investors in the same round is very rare in this sector. Meanwhile, public information shows that most old shareholders such as Tencent, Sequoia Capital China, BlueRun Ventures, Legend Capital have invested additional funds in several consecutive rounds since the first investment.

Five financing rounds in six months, 2 billion yuan, and the continuous investment of old shareholders in multiple rounds can't help but attract the market's attention. Many investors directly state that the iteration speed shown by Simplexity Robotics in recent months is exciting. Almost every time they meet with the team, they are informed that a milestone has been reached and new goals are set. It can be said that Simplexity Robotics has appropriately reciprocated the strong support of shareholders with "lightning speed" and at the same time confirmed the dual advantages of technological products, business models, and team capabilities.

Technological Barriers and Protective Walls

Simplexity Robotics focuses on the independent development of full - stack software and hardware and follows the approach of defining the device through the model and defining the hardware through the software to create a simple and efficient technology concept centered around the "four ones" (one model, on device, one body, one hour).

Simplexity Robotics has created an integrated model of the world model and VLA. Through a unified Transformer architecture, it enables the combined modeling, understanding, and prediction of language logic, visual semantics, 3D spatial structure, and robot state. This achieves a model architecture with a higher upper limit, while reducing manual design and achieving a better scaling effect. Currently, Simplexity Robotics has already presented the following models:

(1 ) LaST₀ Basic Model: For the first time, it combines the understanding and prediction of the physical world through the world model with the fast and slow thinking of VLA, which significantly improves the efficient inference ability for the dynamics of the physical world and solves the problem of how a robot can "think while moving".

(2) ManualVLA Long - Term Task Model: Based on the powerful LaST₀ basic model, ManualVLA solves the problem of how a robot can understand complex long - term tasks. The model can automatically generate multimodal "operating instructions" like those of a human from a target state, thus answering the question of how a robot can "think before acting" (this article was accepted by CVPR 2026).

(3) TwinRL Real - Robot Reinforcement Learning Framework: Based on the strong generalization and inference ability of the basic model, it also considers how to continuously learn and develop in the physical space to increase the success rate of task execution. TwinRL expands the exploration space of real - robot reinforcement learning using digital twin technology. For multiple tasks, the robot can achieve a 100% success rate on the table surface in less than 20 minutes, which solves the challenge of how to make a robot stronger in the real world.

      It is known that more model research results of Simplexity Robotics will be published soon.

The independent development of full - stack software and hardware, the definition of the device through the model, the adherence to a general device, and the belief in the scale effects of data are exactly Simplexity Robotics' answer to the question of how to solve the problem of the data closed - loop.

It is known that Simplexity Robotics recently proposed a robot learning paradigm called "Human data is all you need", which has proven suitable for various fine manipulations (including grippers and fine hands). In the pre - training phase, a large amount of manipulation data is collected through the efficient data collection of human hands, which significantly improves the generalization ability of the model. In the downstream task phase, human demonstration can quickly collect task data, expand the task exploration space, and improve the execution accuracy. In the post - training phase, humans can participate in post - training through real - time consultation, so that the robot can achieve efficient online learning ability and continuous performance improvement.

At the same time, additional computing power is provided on the end - device side, and the end - device training and test verification of the model in the user scenario are realized through the shadow mode. Through this paradigm, Simplexity Robotics can effectively improve data universality and reusability and create an extremely efficient closed - loop system for data collection, training, test verification, and deployment.

In terms of embodied intelligence products, Simplexity Robotics also focuses on extreme simplicity - simple deployment, simple operation, and simple maintenance. From Simplexity Robotics' perspective, extreme simplicity reflects user values as the center and thinks for the users. Time is the biggest cost factor, and users should not pay for complexity. Only by providing value to users can the company have more value. Currently, the first generation of Simplexity Robotics' self - developed device is in small - scale production, and PoC verification has begun.

Systematic Operational Capability

The development speed of Simplexity Robotics is in sync with the financing speed. It took Simplexity Robotics less than 45 days from hiring the first employee to the emergence of the first self - developed device.

Currently, the company has made a strategic layout in Beijing, Shanghai, and Suzhou, jointly established a joint laboratory with top universities, built a global innovation center in Suzhou, continued model research and transformed it into productivity, developed two generations of devices for the B and C segments, put the devices into small - scale production, and fully started PoC verification. At the same time, the company has completed five financing rounds in half a year.

As Jia Peng, the CEO of Simplexity Robotics, said, "Systematization is our differentiation." The mass production and application of embodied intelligence products is a systematic battle that integrates strategy, technology, brand, product, organization, and business. Simplexity Robotics' core team has experienced the most competitive and brutal market environments, gone through the entire process from survival to getting out of crisis, and finally completed the full verification from 0 to 1 and then from 1 to scaling. They profoundly understand the operational logic of the entire process from the top - level strategy to practical implementation, have extremely systematic operational capabilities that have been repeatedly shaped by the market, and know how to efficiently integrate resources, control costs and rhythm, and create a small, refined, simple, and efficient organizational structure to realize a core decision - making and execution system for the entire process.

Commercial Implementation and Future Development

Regarding specific application scenarios, Simplexity Robotics follows a step - by - step iteration path from closed to semi - open and then to fully open scenarios, and first focuses on closed scenarios such as factory halls, supermarkets, and logistics centers. The funds collected here will be fully invested in the fields of basic model training, device development and iteration, data collection, and core algorithm research to accelerate the mass application of embodied intelligence technology in various scenarios.

The scenarios will be expanded from factories to the manufacturing and service industries, from China to overseas. Technological innovation and industrial cooperation will be continuously promoted to enable the mass production and application of the embodied intelligence industry through technology and accelerate the mass application of embodied intelligence technology in various scenarios.

Thanks to its leading technological barriers and top - tier team capabilities, Simplexity Robotics has already become a rising force in the embodied intelligence sector. The company will continue to work on technological innovation and industrial cohesion to enable the mass production and application of the embodied intelligence industry through technological innovation and gradually approach general embodied intelligence to bring China to a leading position in the global general intelligence and robotics industry.

Simplexity Robotics

Simplexity Robotics is an innovative technology company that starts from real scenarios and aims to create high - value - added embodied intelligence products through a high - performance all - in - one model, an efficient data closed - loop, and reliable robot hardware and ultimately promote the future development of humanity.

Simple is Scalable - The core concept of "Simplicity is Scalability" runs through the technology architecture and product design of Simplexity Robotics. Simplexity Robotics focuses on a simple and scalable methodology to solve complex problems in the field of embodied intelligence.