Why We Need an Open Robotic Era
In the next 5-8 years, the number of robots on Earth will exceed 1 billion, marking a turning point from "single machine demonstration" to "social division of labor". Robots will no longer be just mechanical arms on assembly lines, but "colleagues, teachers, and partners" capable of perceiving, understanding, making decisions, and collaborating with humans.
In recent years, robot hardware has grown rapidly like muscles, with more agile hands, steadier gaits, and richer sensors. However, the real bottleneck is not in metal and motors, but in how to give them the mental capacity for sharing and collaboration:
Software from different manufacturers is incompatible, preventing robots from sharing skills and intelligence;
Decision-making logic is locked in closed systems, preventing external verification or optimization;
Centralized control architectures mean limited innovation speed and high trust costs.
This fragmentation makes it difficult to transform AI model progress into replicable productivity: robot single-machine demos are abundant, but lack cross-device migration, verifiable decisions, and standardized collaboration, thus challenging scalability. OpenMind aims to solve this "last mile". Our goal is not to create a robot that dances better, but to provide a unified software foundation and collaboration standard for massive heterogeneous global robots:
Enable robots to understand context and learn from each other;
Allow developers to quickly build applications on an open-source, modular architecture;
Enable safe collaboration and settlement between humans and machines under decentralized rules.
In short, OpenMind is building a universal operating system for robots, enabling them to not only perceive and act, but also safely and scalably collaborate in any environment through decentralized coordination.
Who is Betting on This Path: $20M Funding and Global Lineup
Currently, OpenMind has completed a $20 million (Seed + Series A) funding round, led by Pantera Capital, with an investment lineup covering top global technology and capital forces:
Western technology and capital ecosystem: Ribbit, Coinbase Ventures, DCG, Lightspeed Faction, Anagram, Pi Network Ventures, Topology, Primitive Ventures, and Amber Group, who have long been deeply involved in crypto and AI infrastructure, betting on the underlying paradigm of "intelligent agent economy and machine internet";
Eastern industrial energy: Sequoia China and others deeply rooted in robot supply chain and manufacturing systems, understanding the full difficulty and threshold of "making and scaling a machine".
Meanwhile, OpenMind maintains close communication with traditional capital market participants like KraneShares, jointly exploring pathways to incorporate the long-term value of "robots + intelligent agents" into structured financial products, achieving two-way connectivity between crypto and stocks. In June 2025, when KraneShares launched the global humanoid and embodied intelligence index ETF (KOID), they chose the humanoid robot "Iris" co-customized by OpenMind and RoboStore to ring the opening bell at Nasdaq, the first time a humanoid robot has performed this ceremony in exchange history.
As Nihal Maunder, partner at Pantera Capital, said:
"If we want intelligent machines to run in open environments, we need an open intelligent network. What OpenMind is doing for robots is like Linux for software, Ethereum for blockchain."
Team and Advisors: From Laboratory to Production Line
OpenMind's founder Jan Liphardt is an associate professor at Stanford University and former Berkeley professor, with long-term research in data and distributed systems, deeply rooted in both academic and engineering sides. He advocates promoting open-source reuse, replacing black boxes with auditable and traceable mechanisms, and integrating AI, robotics, and cryptography through interdisciplinary methods.
OpenMind's core team comes from OKX Ventures, Oxford Robotics Institute, Palantir, Databricks, Perplexity and other institutions, covering key areas such as robot control, perception and navigation, multimodal and LLM scheduling, distributed systems, and on-chain protocols. Simultaneously, an advisory team composed of academic and industry experts (such as Stanford Robotics Director Steve Cousins, Oxford Blockchain Center's Bill Roscoe, Imperial College Safety AI Professor Alessio Lomuscio) provides guarantees for robot "safety, compliance, and reliability".
OpenMind's Solution: Two-Layer Architecture, One Order
OpenMind has built a reusable infrastructure that allows robots to collaborate and communicate across devices, manufacturers, and even national boundaries:
Device Side: Provides an AI-native operating system OM1 for physical robots, connecting the entire chain from perception to execution, enabling robots of different forms to understand environments and complete tasks;
Network Side: Builds a decentralized collaboration network FABRIC, providing identity, task allocation, and communication mechanisms to ensure robots can identify each other, assign tasks, and share states during collaboration.
This combination of "operating system + network layer" allows robots not only to act individually but also to coordinate, align processes, and complete complex tasks together in a unified collaboration network.
Extensive Software and Hardware Compatibility: Supports mainstream protocols like ROS2, Cyclone DDS, seamlessly connecting with existing robot middleware. Whether it's Unitree G1 humanoid, Go2 quadruped, Turtlebot, or robotic arms, they can be directly integrated.
FABRIC Integration: OM1 natively supports identity, task coordination, and on-chain payments, enabling robots to not only complete tasks independently but also participate in a global collaborative network.
Currently, OM1 has been deployed in multiple real-world scenarios:
Frenchie (Unitree Go2 Quadruped Robot Dog): Completed complex site tasks at the USS Hornet Defense Technology Exhibition 2024.
Iris (Unitree G1 Humanoid Robot): Performed on-site human-robot interaction demonstration at the Coinbase booth at EthDenver 2025, and plans to enter nationwide college courses through RoboStore's educational project.
FABRIC: A Decentralized Human-Machine Collaboration Network
Even with a powerful brain, if robots cannot collaborate safely and trustingly with each other, they can only fight their own battles. In reality, robots from different manufacturers often build their own systems and operate independently, with skills and data unable to be shared; cross-brand and even cross-national collaboration lacks trusted identity and standard rules. Thus, some challenges emerge:
Identity and Location Proof: How can robots prove who they are, where they are, and what they are doing?
Skill and Data Sharing: How to authorize robots to share data and invoke skills?
Defining Control Rights: How to set the frequency, scope of skill usage, and conditions for data transmission?
FABRIC is designed to solve these problems. It is a decentralized human-machine collaboration network built by OpenMind, providing a unified infrastructure for identity, tasks, communication, and settlement for robots and intelligent systems. You can understand it as:
Like GPS, letting robots know where each other are, whether they are close, and whether they are suitable for collaboration;
Like a VPN, allowing robots to connect securely without public IP and complex network settings;
Like a task scheduling system, automatically publishing, receiving, and recording the entire process of task execution.
Core Application Scenarios
FABRIC can now adapt to various practical scenarios, including but not limited to:
Remote Control and Monitoring: Safely control robots from anywhere without a dedicated network.
Robot-as-a-Service Market: Call robots like hailing a taxi to complete cleaning, inspection, delivery, and other tasks.
Crowdsourced Map and Data Collection: Vehicle fleets or robots upload road conditions, obstacles, and environmental changes in real-time to generate shareable high-precision maps.
On-Demand Scanning/Mapping: Temporarily call nearby robots to complete 3D modeling, architectural surveying, or evidence collection in insurance scenarios.
FABRIC allows "who is doing what, where, and what has been completed" to be verified and traced, and also provides clear boundaries for skill invocation and task execution.
In the long run, FABRIC will become the App Store of machine intelligence: skills can be globally authorized, and data generated from invocations will feed back to the model, driving the continuous evolution of the collaborative network.
Web3 is Writing "Openness" into Machine Society
In reality, the robot industry is accelerating centralization, with a few platforms controlling hardware, algorithms, and networks, blocking external innovation. The significance of decentralization is that regardless of who manufactures the robot or which country it operates in, it can collaborate, exchange skills, and settle payments in an open network without relying on a single platform.
OpenMind uses on-chain infrastructure to write collaborative rules, skill access permissions, and reward distribution methods into a public, verifiable, and improvable "network order"
Verifiable Identity: Each robot and operator will register a unique identity on-chain (ERC-7777 standard), with hardware features, responsibility scope, and permission levels transparent and queryable.
Public Task Allocation: Tasks are not dispatched in a closed black box, but published, bid, and matched under public rules; all collaboration processes generate encrypted proofs with time and location, stored on-chain.
Automatic Settlement and Profit Sharing: After task completion, profit sharing, insurance, and deposit release or deduction will be automatically executed, with any participant able to verify the results in real-time.
Free Skill Circulation: New skills can set invocation times, applicable devices, etc., through on-chain contracts, protecting intellectual property while allowing skills to circulate freely globally.
This is a collaborative order that all participants can use, supervise, and improve. For Web3 users, this means the robot economy has anti-monopoly, composable, and verifiable genes from its inception—this is not just a track opportunity, but a chance to engrave "openness" into the foundation of machine society.
Enabling Embodied Intelligence to Break Out of Isolation
Whether patrolling hospital wards, learning new skills at school, or performing inspections and modeling in urban areas, robots are gradually moving beyond "booth demonstrations" to become a stable part of human daily division of labor. They operate 24/7, follow rules, have memory and skills, and can naturally collaborate with humans and other machines.
To truly scale these scenarios, what's needed is not just smarter machines, but a basic order that allows them to trust, interconnect, and collaborate with each other. OpenMind has laid the first "foundation" on this path with OM1 and FABRIC: the former enables robots to truly understand the world and act autonomously, while the latter allows these capabilities to circulate in a global network. Next, the goal is to extend this path to more cities and networks, making machines reliable long-term partners in social networks.
OpenMind's route is clear:
Short-term: Complete the OM1 core function prototype and FABRIC MVP, launch on-chain identity and basic collaboration capabilities;
Mid-term: Deploy OM1 and FABRIC in education, home, and enterprise sectors, connect early nodes, and gather developer communities;
Long-term: Build OM1 and FABRIC into global standards, allowing any machine to join this open robot collaboration network like connecting to the internet, and form a sustainable global machine economy.
In the Web2 era, robots were often locked in closed systems of single manufacturers, with functions and data unable to move across platforms; in the world built by OpenMind, they are equal nodes in an open network: able to freely join, learn, collaborate, and settle, and together with humans, form a trusted and interconnected global machine society. What OpenMind provides is the powerful capability to make this transformation scalable.
