"Shenpu Intelligence" Closes New Financing Round of Several Hundred Million Yuan, Led by Linear Capital | Linear Portfolio

General-purpose embodied intelligence robotics company Simple AI (深朴智能) recently announced its third funding round within six months, raising several hundred million RMB. This round was led by Linear Capital and Puhua Capital, with continued follow-on investment from existing shareholders.

Simple AI is dedicated to building industry-leading embodied robot companions, using home-like commercial scenarios as its entry point to gradually bring embodied robots into millions of households.

Jun Yang, Partner at Linear Capital, commented: "By entering through home-like scenarios and building a data flywheel through commercial deployment to achieve the goal of robots entering households, Simple AI is taking a sound path that leverages data scaling laws for embodied commercialization. Founder Xiaofei has not only led teams through the complete cycle from R&D to scaled delivery of robotic products, but has also demonstrated exceptional openness and learning ability in our interactions. We look forward to seeing the Simple AI team carve out a strong position amid the industry's intense competition and rapid iteration."

Recently, general-purpose embodied intelligence robotics company Simple AI (深朴智能) announced the completion of its third funding round within six months, raising several hundred million RMB. This round was led by Linear Capital and Puhua Capital, with existing shareholders Juntai Capital, Shunwei Capital, and Baidu Ventures continuing to increase their stakes.

The participation of top-tier institutions and three consecutive rounds of follow-on investment from existing shareholders fully demonstrates capital markets' strong recognition of Simple AI's technical approach and commercialization capabilities. Proceeds from this round will be primarily directed toward R&D for embodied robot brains and physical bodies.

Dr. Xiaofei Li, Founder and CEO of Simple AI, received both his bachelor's and Ph.D. degrees from Tsinghua University, where he studied under autonomous driving pioneer Academician Keqiang Li. He was promoted to senior engineer at age 30. As a top-tier entrepreneur in artificial intelligence, he led the development of an L4 autonomous driving technical architecture and launched robot products with globally leading sales, accumulating full-chain experience from technology R&D to commercial deployment and deeply experiencing the complete ten-year industrial cycle of the autonomous driving industry.

Around this funding round, the company intensively recruited multiple top technical talents, forming a fully staffed composite talent matrix spanning AI, autonomous driving, and robotics.

Among them, Chief Scientist Dr. Jiawei Wang completed his undergraduate studies at the University of Science and Technology of China (USTC) Young Talents Class, and received his Ph.D. through a joint training program between USTC and Microsoft Research Asia. He has deep expertise in large language models, intelligent agents, and reinforcement learning, with over 10,000 Google Scholar citations. He previously served as a core researcher at Microsoft Research Asia, DeepSeek, and ByteDance's Seed team, participating in the development of multiple flagship products and models. Dr. Wang declined top industry offers including Huawei's Genius Youth program, ByteDance Top Seed, Alibaba Star, and Tencent's Qingyun Program to join Simple AI and commit to the embodied intelligence entrepreneurship wave, providing world-class R&D support for the company's core research directions.

Additionally, the team simultaneously brought in multiple top researchers from leading institutions including Tsinghua University, Peking University, and USTC, as well as from major internet companies, jointly pushing forward R&D breakthroughs and commercial deployment in frontier areas such as world models and dexterous manipulation.

Simple AI focuses on the R&D and application of general-purpose embodied intelligent robots, adhering to a "1+2+N" flywheel iteration path: one embodied model architecture, two real-world data pipelines, and N real-world application scenarios. Through the gradual deployment of N real-world scenarios, the company obtains real robot operation closed-loop data to continuously feed back into and iterate its embodied large models.

At the model level, the team has innovatively constructed a hierarchical memory-enhanced intelligent agent architecture, combining self-developed world operation models with end-to-end VLA to significantly enhance robots' capabilities in complex long-horizon task planning, cross-embodiment zero-shot adaptation, and operational generalization and instruction following in non-standard scenarios. This model architecture enabled the company to become the first Chinese embodied intelligence enterprise to place in the global top three at the B-1K Challenge hosted by Professor Fei-Fei Li.

At the data level, the company has self-developed a low-cost, high-precision pure vision UMI + Ego collection system, enabling large-scale, low-cost collection of multi-modal data in real scenarios. Simultaneously, the company has built a comprehensive real robot operation data closed loop, driving autonomous robot evolution through efficient continual learning, forming a dual flywheel of technology and business where robots become "smarter with use and more efficient with delivery."

Based on systematic breakthroughs at the technology level, Simple AI is iterating its physical bodies at a pace of one generation per month, with a new product set for release soon that will feature major upgrades in model algorithms, perception capabilities, and form factor.

Dr. Xiaofei Li, Founder and CEO of Simple AI, stated: "Embodied intelligence is at a critical juncture, transitioning from technology exploration toward scaled application. We remain committed to using real scenarios as our driving force, building efficient data closed loops and model iteration systems to make robots truly become the intelligent foundation of the physical world."

The company has already achieved commercial breakthroughs in multiple real-world scenarios: it has established strategic partnerships with China Tourism Hotel Group and other premium hotel brands to jointly develop hotel scenario embodied service robots; and it is working with Hong Kong Polytechnic University and Hotel ICON to jointly establish embodied intelligence service standards for hotels, tackling fine manipulation challenges in dynamic environments while simultaneously laying out data compliance frameworks for Hong Kong and overseas markets.

Furthermore, the company is collaborating with Shengshu Technology to achieve bidirectional empowerment between the "foundation model layer" and "scenario application layer." Simple AI will provide Shengshu Technology with real-scenario embodied intelligence data, while Shengshu Technology's foundation models will provide Simple AI's robots with a more powerful intelligent foundation, forming the industry's first embodied intelligence "foundation + application" ecological closed loop.

Looking ahead, Simple AI will continue pushing technology iteration and product integration, building full-chain physical world data collection and model training infrastructure, and continuously optimizing embodied intelligence foundation model capabilities. In 2026, the company will complete the transition from pilot customer trials to batch delivery. In 2027, it will launch an overseas version as well as trial versions targeting seed customers in eldercare and home scenarios, steadily advancing toward the ultimate goal of "embodied robots entering homes" and accelerating the transition of embodied intelligence from laboratories into every real-life scenario.

About Simple AI

Simple AI (深朴智能) is an artificial intelligence technology company focused on the R&D of general-purpose embodied intelligent robots. The company is dedicated to building industry-leading embodied robot companions, using home-like commercial scenarios as its entry point to gradually bring embodied robots into millions of households. The company adheres to building a technology closed-loop system centered on "models-data-bodies-scenarios," achieving globally leading positions in embodied large models and real robot operation closed loops.