In six months, there were five rounds of financing, with a cumulative total of 2 billion RMB. Zhijian Dynamics has become the fastest "unicorn" in the embodied intelligence track.

Recently, Simplexity Robotics officially announced that it had completed five consecutive rounds of financing in less than half a year, with a total financing amount of 2 billion RMB, instantly becoming the youngest unicorn in the industry. Light Source Capital served as the financial advisor for the latest round of financing.

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

Simplexity Robotics, founded in late July 2025, made its first official appearance and announced its financing. Previously, there were almost no relevant news about them in the public channels.

The financing lineup announced by Simplexity Robotics this time is quite luxurious, gathering top - tier financial investment institutions and top - tier strategic investors. These financial investment institutions include: Vision Plus Capital, BlueRun Ventures, Sequoia China, Legend Capital, Zhongke Chuangxing, and Banyan Capital; the strategic investors are Tencent and Alibaba Group.

It is quite rare in this industry for the two major strategic investors, Tencent and Alibaba, to participate in the same round of investment. Meanwhile, according to public information, most of the old shareholders, such as Tencent, Sequoia China, BlueRun Ventures, and Legend Capital, have continuously increased their investment in multiple rounds since the first round.

Five rounds of financing in six months, 2 billion RMB, and continuous investment increases from old shareholders can't help but attract the market's attention. Many investors said that the iteration speed of Simplexity Robotics in the past few months was exciting. Almost every time they met with the team, they were told that a milestone had been achieved, and new goals were set. It can be said that while Simplexity Robotics is responding to the firm support of its shareholders at "lightning speed", it also verifies the dual advantages of its technological product business model and team execution ability.

Technological Barriers and Moats

Simplexity Robotics adheres to full - stack self - research of software and hardware, following the concept of defining the ontology through models and defining hardware through software to build a simple and efficient technological system centered around "Four Os" (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, it realizes the joint modeling, understanding, generation, and prediction of language logic, visual semantics, 3D spatial structure, and robot status. While achieving a model architecture with a higher upper limit, it reduces manual design and has better scaling effects. Currently, Simplexity Robotics has launched:

(1) LaST₀ Base Model: It is the first to integrate the world model's understanding and prediction of the physical world with the fast - slow thinking of VLA, significantly improving the efficient reasoning ability for the dynamics of the physical world and solving the problem of how robots can "think while moving quickly".

(2) ManualVLA Long - Range Task Model: Based on the powerful foundation of LaST₀, ManualVLA solves the problem of how to enable robots to understand complex long - range tasks. It allows the model to automatically generate multi - modal "operation manuals" similar to those used by humans from the target state, perfectly answering the question of how robots can "think clearly before taking action" (this paper has been accepted by CVPR 2026).

(3) TwinRL Real - Machine Reinforcement Learning Framework: Based on the strong generalization and reasoning ability of the basic model, we also consider how to continuously learn/evolve in the physical world and continuously improve the success rate of task execution. TwinRL expands the exploration space of real - machine reinforcement learning with the help of digital twins. In multiple tasks, robots can achieve a 100% success rate in the desktop area in less than 20 minutes, solving the challenge of how to make robots become stronger in the real world.

      It is reported that other model research results of Simplexity Robotics are being released successively.

Adhering to full - stack self - research of software and hardware, defining the ontology through models, adhering to a general ontology, and believing in the scale effect of data, this is exactly Simplexity Robotics' response to how to solve the data closed - loop problem.

It is understood that Simplexity Robotics recently proposed a robot learning paradigm of "Human data is all you need" and has verified that it is applicable to various dexterous operations (including grippers and dexterous hands). In the pre - training stage, a large amount of operation data is efficiently collected through human hands, significantly improving the generalization ability of the model; in the downstream task stage, human demonstrations can quickly collect task data, expand the task exploration space, and improve execution accuracy; in the post - training stage, humans participate in post - training through real - time guidance, enabling robots to achieve efficient online learning and continuous improvement of capabilities.

Meanwhile, by deploying additional computing power on the edge side and using the shadow mode, edge - side training and model testing and verification in user scenarios are realized. Through this paradigm, Simplexity Robotics can effectively improve data universality and reusability, and build an extremely efficient closed - loop system for data collection, training, testing, verification, and deployment.

When it comes to embodied intelligent products, Simplexity Robotics also adheres to extreme simplicity - simple deployment, simple use, and simple maintenance. In the view of Simplexity Robotics, extreme simplicity reflects the focus on user value and thinking more for users. Time is the biggest cost, and users should not pay for complexity. Only by providing value to users can the company be more valuable. Currently, the first - generation self - developed ontology of Simplexity Robotics has been produced in small batches and started PoC verification.

Systematic Combat Capability

The development speed of Simplexity Robotics is in sync with its financing speed. It only took less than 45 days for Simplexity Robotics from the arrival of the first employee to the birth of the first - generation self - developed ontology.

Currently, the company has achieved a strategic layout in Beijing, Shanghai, and Suzhou, established joint laboratories with top universities, set up a global innovation center in Suzhou, continuously promoted model R & D and transformed it into product strength, completed the R & D of two generations of ontologies for both B - end and C - end users, achieved small - batch production of ontologies and fully launched PoC verification. Meanwhile, the company completed five rounds of financing transactions within half a year.

As Jia Peng, the CEO of Simplexity Robotics, said, "Systematization is our difference." The mass production and implementation of embodied intelligent products is a systematic battle, integrating strategy, technology, brand, product, organization, and business. The core team of Simplexity Robotics has experienced the most competitive and cruel market environment, gone through the whole process from survival crisis to breakthrough, and finally completed the full verification from 0 to 1 and then from 1 to scale. They deeply understand the whole - process operation logic from top - level strategy to practical execution, have the extreme systematic combat ability polished by the market, and know well how to efficiently integrate resources, control costs and rhythm, and build a small, refined, simple, and efficient organizational structure to achieve a core decision - making and execution system with a full - link closed - loop.

Commercial Implementation and Future Development

Regarding specific implementation scenarios, Simplexity Robotics follows a progressive iteration path from closed to semi - open and then to fully open scenarios, and first focuses on closed scenarios such as factory workshops, supermarkets, and logistics. The funds raised this time will be fully invested in areas such as training base models, ontology R & D and iteration, data collection, and core algorithm R & D to accelerate the large - scale application of embodied intelligent technology in multiple scenarios.

It will complete the scenario expansion from factories to the manufacturing and service industries, from domestic to overseas markets, continue to focus on technological innovation and industrial cooperation, empower the large - scale implementation of the embodied intelligent industry with technology, and accelerate the large - scale application of embodied intelligent technology in multiple scenarios.

With its leading technological barriers and top - tier team combat ability, Simplexity Robotics has become a new force in the embodied intelligent industry. The company will continue to focus on technological innovation and industrial ecological cooperation, empower the large - scale implementation of the embodied intelligent industry with technological innovation, steadily move towards general embodied intelligence, and help China take a leading position in the global general intelligence and robotics fields.

Simplexity Robotics

Simplexity Robotics is an innovative technology company that starts from real - world scenarios and is committed to creating embodied intelligent products with high user value through a high - ceiling unified model, an efficient data closed - loop, and reliable robot hardware to ultimately empower the future development of humanity.

Simple is Scalable - The core concept of "the highest truth is the simplest" always runs through the technological architecture and product design of Simplexity Robotics. Simplexity Robotics adheres to a simple and scalable methodology to solve complex problems in the field of embodied intelligence.