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January 7, 2026Robotics20 min read

Decentralized Robotics: Landscape and Outlook

Nine protocols building the coordination, positioning, spatial and capital layers for embodied AI, and the risks that come with an early market.

Key Takeaways

  1. Robotics is moving onto open networks, and the sector already has revenue and live deployments: Machine identity, micropayments and shared mapping let robots transact and coordinate without a central operator.
  2. The market around it is large and growing: Global robotics is projected to grow from about $128B in 2025 to about $275B by 2030, and Goldman Sachs puts humanoids alone at $38B within ten years.
  3. Three trends drive the shift: Vision-language-action models speed up real-world tasks, decentralized infrastructure lets machines take part in the economy, and physical robots give the public an easier way in than abstract crypto products.
  4. The report covers nine networks across the stack: They are peaq, GEODNET, BitRobot, CodecFlow, Auki, Neuron, XMAQUINA, Bittensor subnets and OpenMind.
  5. Valuations remain small against the addressable market: That gap is the entry window, and it carries early-stage risk to match.

Executive Summary

Decentralized robotics represents a structural evolution in how machines operate, learn, coordinate, and create economic value. The sector now demonstrates:

  • Real revenue
  • Live industrial deployments
  • Scalable AI research and coordination frameworks
  • Models for democratized investment and ownership
  • Emerging benchmark for embodied AI

This is no longer a speculative concept; it provides product market fit with real world impact.

The sector’s current aggregate valuation remains disconnected from its long-term addressable market, presenting an asymmetric entry window for early positioning.

70% of the world’s GDP is still tied to physical locations and labor.

DeRobotics is the intersection of Artificial Intelligence, robotics, blockchain, and agentic payment protocols (Coinbase’s x402, A2A etc.), represents one of the most important technology themes for 2026.

Venn diagram of three overlapping circles labeled Robotics, AI and Blockchain. The highlighted center where all three intersect is labeled DeRobotics, defining the sector as the convergence of the three fields.

As AI models become more capable, their physical counterparts gain the ability to perceive, navigate, and act autonomously in the real world. Combined with permissionless payments and shared data networks, robots can increasingly operate, transact, and coordinate without centralized control.

Three converging trends drive this transition:

  • Embodied AI advances: Vision‑Language‑Action (VLA) models, multimodal inference, and simulation accelerate real-world task completion.
  • Decentralized infrastructure: Machine identity, micropayments, spatial mapping, and geospatial networks allow robots to participate in the global economy.
  • Retail accessibility: Physical robots (visible, tactile, and demonstrably useful) offer a clearer onboarding path for the public than intangible crypto products.

Mass deployment of physical machines, in the form of embodied AI will be a theme of the next decade with tangible developments anticipated as early as next year.

Global Robotics is projected to grow from ~$128B in 2025 to ~$275B by 2030:

Bar chart of robotics market cap projections in billions of dollars, 2025 versus 2030. Traditional robotics grows from roughly $128B to about $275B; DeRobotics grows from a few billion to roughly $55B, a far steeper relative increase from a small base.

DeRobotics is arguably in its infancy compared to traditional robotics, suggesting a greater level of upside to compensate for the additional early stage risk.

It’s possible that DeRobotics will merge into the broader “multi-trillion-dollar" traditional robotics market as blockchain networks are more deeply integrated into 'Big tech' systems. If we use "DeFi" as an example, it’s clear that traditional finance is adopting crypto payment rails, and as such it’s likely DeFi + Traditional Finance (TradFi) will simply be known as 'Finance' in the medium term future.

So while this report focuses on the emerging decentralized networks, it’s important to view this in the context of robotics more broadly.

This report outlines the DeRobotics sector’s architecture, evaluates leading networks, and provides context for the economic and technical forces shaping this emerging market.

01Market Context and Growth Drivers

Decentralized robotics networks aim to disintermediate centralized control and ownership of robots with token-incentivized, globally distributed systems, enabling:

  1. Autonomous machine-to-machine, and machine-to-human transactions (x402)
  2. Fractional ownership of physical robots and industrial hardware (XMAQUINA)
  3. Shared robotic intelligence through federated AI and decentralized model training ($TAO subnets, Bitrobot)
  4. Open, collaborative infrastructure for mapping, positioning, and control (GEODNET, Auki)

Several companies are emerging as leaders within this crypto segment:

Grid of ten white logos on black under the heading Emerging Leaders, showing the decentralized robotics projects covered in the report, including peaq, Auki, BitRobot, GEODNET, Codec, OpenMind, Virtuals, Bittensor and NRN.

AI, and in turn Physical AI, has evolved at an exponential pace with embodied AI anticipated to move as fluidly as humans in the not-too-distant-future.

A widely circulated projection from industry leaders suggests the long‑term production of billions of robots, creating a multi‑trillion‑dollar, possibly quadrillion-dollar, sector. While the exact figures are speculative, the direction of travel is unambiguous: robotics will become as economically significant as smartphones or cloud computing.

1.1 Robotics Growth Dynamics

Sub-segments are expected to expand rapidly:

Robotics segment market sizes in billions, 2025 to 2030: Industrial 48 to 91, Agricultural 18 to 56, Consumer 14 to 29, Humanoid 3 to 15 (fastest, 39% CAGR), Logistics 15 to 36, Military 20 to 33, Healthcare 10 to 15. Total 128 to 275.

The humanoid category has received significant attention recently due to progress in capabilities and commercial feasibility with thousands of units anticipated to be sold to retail in 2026:

Lineup of nine humanoid robot silhouettes with maker and model: Boston Dynamics Atlas, Unitree G1, Figure AI Figure 02, Tesla Optimus, Sanctuary AI Phoenix, Agility Digit, Apptronik Apollo, Fourier GR-1 and 1X Technologies NEO.

Goldman Sachs predicts the Humanoid category alone could hit $38B within the next 10 years.

All of these robots require shared intelligence, simulation, coordination, and environment mapping systems; areas where decentralized approaches may be structurally advantageous.

The macro robotics sector is influenced by several structural forces:

Structural drivers of robotics growth
DriverImpact
Labor shortages and rising wagesIncreases demand for automation across manufacturing, logistics and agriculture
Declining hardware and sensor costsLowers barriers for robot deployment and ownership
Reshoring and sovereign industrial policyEncourages domestic automation infrastructure
Advancements in large-scale AI modelsEnables autonomous decision-making and embodied intelligence

Several national policies and incentives are being rolled out to encourage domestic production in the United States:

  • NVIDIA and AMD entered a revenue-sharing agreement to pay the U.S. government 15% of their revenues from specific chip sales to China (H20 and MI308)
  • Intel received an $8.9B investment from the U.S. government through the issuance of 433 million new shares, giving Washington a 10% equity stake in the company.

1.2 Why Decentralization Matters in Robotics

Traditional robotics architectures rely on centralized controllers and proprietary cloud systems. This model faces several structural limitations:

Limits of centralized robotics and the decentralized alternative
LimitationDecentralized Network Advantage
Single point of failureDistributed control → Fault tolerance
Bottlenecks in scaling robot fleetsHorizontal scalability via peer coordination
Vendor lock-in and closed data ecosystemsOpen, composable systems
High capital requirements for ownershipFractional / tokenized ownership models
Limited incentives to contribute dataTokenized contribution economy

Decentralization is particularly valuable in dynamic environments like drone swarms, warehouse logistics, agricultural automation, and humanoid assistants, where real-time local decision-making and resilience are critical.

Pair this with local tooling and robotics training environments, tailored to your own personal home, or factory, and you have a distributed robotics evolution. The large scale robotics manufacturers are unlikely to have the bandwidth to tailor their Software Developer Kits (SDKs) sufficiently to make a meaningful difference in your own personal physical robot.

This opens up an opportunity for DeRobotics to plug the gap with a machine agnostic set of software tools to monetize.

1.3 Data Shortfalls

The amount of data that AI uses varies dramatically depending on whether you are referring to the training of an AI model or its ongoing operation (inference), as well as the specific application.

One of the leading arguments for the usefulness of Decentralized AI is its data; There isn’t enough high quality data specifically for Robotics.

Robots need many other data types to operate in the real world:

Data types robots need
Data TypeWhat it RepresentsWhy it Matters (for AI/Robotics)
Numerical DataMeasured values (speed, weight, temperature)Used for control, physics, sensing and precise decision-making
Categorical DataLabels and groupings (object type, color, location)Helps systems classify and understand discrete states
Text DataWritten languageEnables reasoning, instructions, translation, chat and search
Image & Video DataVisual information from camerasTrains perception: Object recognition, scene understanding and navigation
Audio DataSound and speechEnables voice commands, conversation, environmental awareness
Time-Series DataSignals evolving over timeCritical for real-time response, prediction and adaptive control

Image and video data is lacking, and certainly where decentralized AI protocols can contribute.

Vader AI has rolled out an initiative that distributes glasses to contributors who collect video data on completing routine tasks.

This enhances the contextual data to train robots on tasks that humans do instinctively, but embodied AI finds challenging.

02Sector Framework: Layers of the DeRobotics Stack

The emerging sector stratifies into several layers:

Five-layer DeRobotics stack with representative projects: Identity and Economic Layer (peaq); Physical Environment Sensing and Positioning (GEODNET); Spatial Mapping and Shared Perception (Auki); Robotic Intelligence and Coordination (NRN, Codec, OpenMind); Capital Formation and Asset Tokenization (Virtuals, Bittensor, BitRobot, XMAQUINA).

Each layer solves a distinct technical bottleneck and creates interoperability benefits when integrated.

03The Current ‘DeRobotics’ Landscape

The current landscape is nascent, some are only just demonstrating product market fit with revenue. Here is a rundown of the diverse range of protocols showing promise as we enter 2026:

3.1 peaq ($PEAQ)

Layer 1 for the Machine Economy

peaq serves as the economic system and base coordination layer for the machine economy, similar to how Solana/Ethereum serve DeFi, but as blockchain optimized for machines, robots and autonomous agents, enabling universal standards for identity, ownership, time, access control, and payments for devices and robots on the one side, and a purposely designed token economy that enables micro economies to emerge on top of it through its unique economic model and pool structure on the other.

peaq's tokenized robo-farm

The protocol, being developed since 2021, has onboarded more than six million (human and machine) users and 180 million transactions since their 'Token Generation Event' (TGE) last year. With the roll-out of the peaq ‘robotics SDK’, any ROS2 compatible machine can now be onboarded to the machine economy, transact and trade with humans and other machines on peaq, and leverage its universal standards.

A notable deployment this month was a tokenized Robo-Farm in Hong Kong, which boasts:

  • 80% automation across hydroponic tasks
  • ERC-721 “Share” minting model with estimated ~18% annualized yield
  • Demonstrates real revenue and operational utility, not just proof-of-concept
  • Making every consumer of salad grown by the farm a direct participant in the decentralized Machine Economy
  • Introducing a new asset type with $150K TVL (Machine RWA)
  • Bringing web2 liquidity (salad purchases from average Hong Kong citizens) on the peaq chain
  • Soon, the farm itself will use its proceeds to invest and participate in other Machine Economies on the network

The opportunity sold out within 24 hours on DualMint, a machine tokenization platform.

Other opportunities are available to register on the marketplace:

Screenshot of three tokenized real-world asset listings on peaq: AmpDock EV chargers in Hong Kong (20% historical yield), Boring Index Vault onchain (15 to 20%) and AirUp air conditioning units (20%, sold out), each with a Boring Index score.

The PEAQ Token

The PEAQ token launched alongside Mainnet on November 12, 2024. There were a total of 4.2B Genesis tokens at launch, but when factoring in annual inflation of 3.5% ( Net increase of 147M for the first year) with 10.00% annual disinflation until reaching 1.00%. Then five years at 1.0%, after which supply is capped.

PEAQ token unlock schedule over about 45 months. Monthly unlock bars start with roughly 375M PEAQ, run about 75 to 105M, then taper to about 25M. A cumulative line passes 25% near month 8, 50% near month 20 and about 71% by month 44.

Combining this with an increase in activity and commitment to token alignment, then we could see reasonable price performance provided further partnerships are secured and fundamentals are aligned with tokenholder interest through optimal buyback (or similar) models.

Network native pools that are inherent in the peaq economics (Machine onboarding, Machine Incentive Pools among others) will soon be activated to automate a better regulation of supply and demand of the PEAQ token in the network.

Partnerships like the recent Dubai’s VARA framework for regulating onchain robotics and tokenized machines in Dubai, put peaq in a good position for deeper integration within the global emerging technology market, as such a standard is currently absent.

The “Economic Layer for Machines” is a universal concept that becomes easy to grasp.

“peaq is designed to capture a new type of users and a new class of assets to its network - robots, machines, and sensors. The runtime-native functionalities are the backbone for Machines to participate in this economy and create value outside of their closed systems. With the exponential rise of small and medium scale robotics manufacturers globally, and the fragmentation of smart city infrastructure, we are well-positioned to unlock value flows through our network that will significantly increase economic output in the Machine Economy” - Till Wendler, Co-Founder peaq

3.2 GEODNET ($GEOD)

Decentralized GNSS / RTK Positioning

Global Earth Observation Decentralized Network (“GEODNET”) provides centimeter-level accuracy precision positioning.

This is known as real-time kinematic (“RTK”) data through a network of decentralized reference stations as seen across this coverage map:

Screenshot of the GEODNET RTK Network coverage map, showing green station markers densely clustered across the United States, Europe, India and Australia, with thinner coverage in South America, Africa and Asia.

This data can be used for a variety of use cases, including:

  • Autonomous drones
  • Agricultural machinery
  • Mobile robotics
  • Mapping and surveying

Typically we would expect a positive correlation between valuation and fee revenue, particularly given the commitment to align tokenholder interests with the fundamentals of the business via an 80% buyback model.

GEODNET on precision positioning for robotics

GEOD has seen a steady increase to >$7M ARR with compounding quarterly growth:

Combined bar and line chart of GEODNET quarterly revenue and token burn value, Q3 2024 to Q3 2025. Revenue rises steadily from about $390K to about $1.2M; burn value tracks it, rising from about $290K to about $970K.

There’s been a short term negative correlation between valuation and revenue, driven largely by the adverse macro movement in the broader crypto market following the cascading liquidation events on October 10:

Dual-axis chart of GEODNET daily revenue versus FDV, November 2024 to November 2025, source DefiLlama. Daily revenue mostly holds $8K to $15K with spikes to $40K, while FDV falls from a peak near $360M to roughly $110M to $160M.

We anticipate this to shift as robotics becomes more entrenched in society and enters mass production to completely revamp the existing human workforce, creating a strong appetite for geospatial positioning data.

According to a report by A16z, Decentralized Physical Infrastructure Networks (“DePIN”) is set to grow to a multi trillion dollar industry in its own right, of which GEODNET is highlighted in second spot behind Helium:

“The World Economic Forum projects the DePIN category will grow to $3.5T by 2028.”

a16z crypto chart of weekly DePIN fees, 2023 to 2025, stacked by Helium, GEODNET, Akash, Hivemapper, Livepeer and Dimo. Fees climb from near zero to above $500K weekly, led by Helium, which reports 111,906 hotspots and 1.41M daily users.

Fundamentally GEODNET has strong global network coverage; 20,000+ satellite miner stations across 150+ countries.

GEODNET's product traction caught the attention of Multicoin Capital, who purchased $8mm of the token in February 2025. Speaking on the Supercycle Podcast, Multicoin General Partner Shayon Sengupta shares the story of first meeting Mike:

Multicoin on investing in GEODNET

GEODNET is one of the few proven revenue-generating DePIN projects with real enterprise customers. Its resource network growth directly increases service reliability, forming a strong flywheel for tokenholders, assuming its buyback model and demand for its data continues.

“$GEOD isn’t a hype machine, it’s a utility engine. Every new drone, robot, tractor, and rover tapping into the GEODNET RTK network creates real demand, real revenue, and real burn.” - Mike Horton, Project Creator, GEODNET

For more information, we suggest readers listen to CEO Mike's talk at the 2025 Multicoin Summit:

Mike Horton on physical AI, Multicoin Summit 2025

3.3 BitRobot (Pre-TGE)

The World’s Open Robotics Lab

BitRobot is a modular network of robotic subnets, each generating valuable resources, to accelerate Embodied AI and robotics innovation.

It was co-developed by Michael Cho (FrodoBots Lab cofounder), Jonathan Victor (former Filecoin Ecosystem Lead), and Juan Benet (creator of Filecoin and IPFS). The project is currently tokenless, but intends to launch a network token to incentivize resource co-ordination for progressing robotics training using a network of subnets. Here's a video on Frodobot's Earthrover:

FrodoBots EarthRover Mini+

Subnet Structure

A BitRobot Subnet is a focused cluster of contributors and resources working together to create value for the BitRobot Network.

BitRobot network flow diagram. Resource supply from human labor, embodied robots and external service providers feeds subnets 1 to N. Demand from embodied AI agents, AI labs, startups, consumers and governments contributes to a reward network, which distributes rewards back to the subnets.

Subnets vary in what they do: some focus on hardware procurement, others build new datasets (teleoperation, video, and simulation) or train new models. So far, five subnets have been publicly announced out of 14 live or in development. In addition, over 25 additional teams are in the pipeline. The five publicly announced subnets are:

Table of five BitRobot subnets with descriptions and key metrics: ET Fugi sidewalk robot navigation data; Earth Rover navigation challenge; Robotics Origami dexterity challenge; Robotics IKEA furniture assembly challenge; SeeSaw by Virtuals crowdsourcing first-person video to train humanoids.

Virtual's subnet 5 ("SeeSaw") has been subtly integrated into its Agent Commerce Protocol ("ACP"):

This year, we’ve been quietly placing serious bets on robotics as a core pillar of Virtuals Protocol, from SeeSaw surpassing half a million recorded tasks to early-stage ACP integrations with robots and capital formation rails for embodied agents.

The incentive structure for subnet emissions will be established based on a governance framework that includes the Senate and an AI entity “Gandalf AI”:

BitRobot governance diagram. Token rewards flow to a Senate of senators and to Gandalf AI, weighted by delegation. Senators and Gandalf AI then allocate rewards to subnets SN01 onward, weighted by their respective evaluations.

The BitRobot Senate is composed of nominated representatives of the Embodied AI research communities, with the aim of resources flowing toward the subnets creating the highest value.

What’s BitRobot Aiming to Solve?

Unlike language and vision AI, robotics is still held back by closed ecosystems, fragmented tools, and limited real-world testing; leaving most progress locked inside a few large labs. Here's CEO Michael on our Supercycle Podcast, discussing the founding story for Bitrobot:

BitRobot on its founding story

BitRobot addresses this by incentivizing global contributors to collect data (video, teleoperation, and simulation), train models, and test policies; forming the foundation for general-purpose physical AI.

Built as a Solana protocol, each subnet operates as an open research mission where people, robots, and compute coordinate to advance embodied AI.

To accelerate progress, the BitRobot Foundation has launched a $5M Grand Challenges Fund, initially supporting the Earth Rovers (navigation), Robotic Origami (dexterity), and Robotic IKEA Assembly (manipulation) subnets.

White the protocol is in its early stages, it’s clear they’ve got a wealth of expertise and are incentivizing network contributors to solve real world robotics problems with established partners - incentivizing global contributors to collect a breadth of multi-modal data will be the solution to creating a foundation for general purpose AI, including Robotics.

3.4 CodecFlow ($CODEC)

AI Execution and Inference Marketplace for Robots

CodecFlow ($CODEC) acts as the operational layer for embodied AI, bridging:

CodecFlow architecture diagram. Human demonstrations, synthetic data and multimodal inputs feed the CodecFlow platform (Optr SDK, machine layer, Fabric), linked to a VLA model, cloud training, simulation and an operator agent, executing in digital and physical environments on a decentralized blockchain network.

The CODEC SDK provides robots with access to vision-language-action models via decentralized compute nodes. To date Codec has served 2.8M+ inference calls, across 450+ models and 1,200+ compute suppliers.

$CODEC token: Fair launched through Pump Fun on Solana.

Its spike in volume on September 15 is attributable to its coverage, and traction, around VLA (Vision Language Action) models which provides Operators the ability to see, understand, and act in digital environments:

Dual-axis chart of CODEC price versus daily volume over 90 days, mid-August to mid-November 2025. Price peaks near $0.042 in mid-September then falls to about $0.016, while daily volume jumps from about 1M to 4 to 8M after mid-September.

A comparative traditional AI entity would be Hugging Face, which builds open-source tools and platforms that make it easy for developers and companies to create, share, and deploy machine-learning models.

Revenue: Income can be generated from:

  • Marketplace Fees: Revenue from Operator publishing/licensing
  • Compute Rentals: $CODEC earnings for node operators contributing hardware
  • Premium Access: Token staking for reduced fees, priority deployment
  • Transaction Fees: Platform cuts from compute usage and task brokerage

One of the largest opportunities to monetize DeRobotics projects is through an auction model between the traditional robotics workforce and tasks needing completion:

Flow diagram of a robotics labor marketplace: a traditional robotics workforce submits bids to an auction platform, which assigns tasks, and completed tasks route back to the workforce.

Projects that offer these brokerage services, or build the software that enables these two counterparties to transact, could earn reasonable fee revenue as activity ramps up.

CODEC offers a central hub for robotics companies to source tasks. It recently integrated Chainlink Runtime Environment (CRE) to build an autonomous delivery agent, MechaShip, with dynamic quotes.

It supports x402 micropayments by agents to access its central hub and is live on peaq’s MachineDEX (Decentralized Exchange on Mainnet).

If CODEC is able to onboard big name partners and align interests between the fundamentals of a lucrative auction system model and tokenholders, then this would bolster the protocol’s long term prospects for success.

“Software ate the digital world, embodied AI is about to eat the physical one. This future cannot be built in silos. CodecFlow is constructing the decentralized infrastructure from simulation to hardware that enables intelligent Operators to learn, act, and cooperate openly.” - Moyai, CodecFlow CEO

3.5 Auki ($AUKI)

Decentralized Shared Spatial Computing

Auki uses its proprietary ‘Posemesh’ technology to create a shared 3D map of the world that robots and Augmented Reality (“AR”) devices can reference. This is dubbed the “Real World Web”.

Auki has rolled out devices using its XR tech “Cactus AI” within several Swedish supermarket stores for trials, and experimental mapping of surroundings, providing spatial awareness for embodied AI to operate. It already has active pilots with Toyota Material Handling, COOP Visby, and more with 2,300+ nodes in operation:

Grid of twelve partner and event logos for Auki, including MTR, AWE, Sino Group, Stora Coop, Fresh Plus, Hong Kong Fintech Week, WOW Summit, Handelskongress Deutschland, Tai O Heritage Hotel, Mars and Toyota Material Handling.

Current robotics partnerships include:

Shared spatial context enables multi-robot collaboration, object permanence, and navigation without centralized data servers. Here's Auki CEO Nils on our Supercycle Podcast, discussing the market opportunity of robotics:

Auki Labs on the robotics outlook

Auki's core ‘Posemesh’ Technology

This is Auki’s “moat” and provides the business with a tangible advantage in sustaining a lead in the decentralized spatial market segment.

  • Domains: Digital twins with three layers (semantic, topographic, rendering)
  • Collaborative SLAM: Multiple devices merge sensor data via overlapping portals
  • Edge Computing: Reconstruction nodes handle compute-intensive 3D processing
  • Privacy-First: Encrypted clusters with local computation, no global data sharing

Auki Token

The $AUKI utility token on Base is burned by devices to access the Auki network on a metered basis. You burn a fixed amount of dollars worth of AUKI for credits. Recent price action has moved consistently with the broader DeRobotics narrative with an increase in attention in September:

Dual-axis chart of AUKI price versus daily volume over 90 days, September to November 2025. Price climbs from about $0.014 to a peak near $0.039 in mid-September, then declines to about $0.017, with volume spikes up to about 7.5M around the peak.

Auki used a DEX-first launch strategy to build a strong organic community, and will launch on CEX in 2026.

Revenue + Operational Efficiencies

Auki is one of a handful of protocols at the intersection of crypto and robotics that is demonstrating significant traction in the real world:

  • $2M+ annual recurring revenue from spatial solutions
  • 30% reduction in time looking for products and walking distance from staff in trials
  • 15 min/day/employee handover time reductions as part of COOP results
  • 30 min/day productivity gains from spatial awareness
  • 4,000 m²/store mapping completed in < 4 hours vs. days previously

Auki is positioning itself as the decentralized spatial layer for robots and AR, converting real-world environments into a shared, privacy-preserving compute fabric with proven enterprise traction.

3.6 Neuron ($NRN)

Neuron. Global Evaluation Layer for Embodied AI

Neuron (NRN) aims to:

“become the authoritative leader that serves as the global evaluation and reproducibility layer for embodied AI... the LMArena for multimodal (Vision-Language-Action), embodied agents”.

NRN robotics leaderboard of six models. OpenPI by Physical Intelligence ranks first with score 30.42; OpenVLA second at 23.05. Gr00t, SmolVLA, Gemini Robotics-ER 1.5 and Helix are unscored. A radar chart compares the two on score, efficiency, robustness and cross-domain performance.
  • Dr. Nicholas Nadeau, former CTO of 1X, recently joined NRN as a Strategic Advisor. His deep experience in building production-grade, real-world robotic systems will prove invaluable.
  • SAI Platform: NRN launched ‘SAI’ (Chinese word for competition) which aims to become the evaluation standard for robotics across the key dimensions that define general intelligence. Beyond simple task completion, SAI assesses models on Competency (efficiency and score), Robustness (performance under diverse conditions and noise), and Generalization (adaptability across multiple tasks and embodiments).

Multi-Pronged Benchmarking Platform:

  1. Independent Standard: Proprietary assessment framework for objective and rigorous evaluation of leading VLAs
  2. Social Validation: Human-preference scoring of pair-wise VLAs' outputs (actions) to provide crowdsourced feedback loops on policy behavior in diverse, human driven scenarios
  3. Eval for Teleoperation: Extends the pairwise comparison engine to human-teleoperated workflows. This layer generates subjective quality data to benchmark hardware efficacy and operator performance.

Strategy & Incentives: $NRN used a co-ordination and incentive mechanism to aggregate human preference data to improve frontier robotic model performance. Token can also be used to subsidize compute resources necessary to power ongoing research and innovation on the SAI competition platform.

It’ll take time for the public to trust robots, so having human input to how they move and interact in the real world will be imperative for a seamless integration into society. Just because a robot does a task more efficiently than a human, doesn’t mean that it’s the optimal method deployed; that’s where “social validation” comes into play.

Monetization: Establishing a leadership position in robotics eval creates a gravitational pull of attention toward the SAI and NRN brands within the industry and serves as the foundation to roll out high-margin commercial opportunities like: Third-party Auditing & Trust Services, Enterprise Evaluation SaaS.

In an agentic economy, model evaluation and benchmarking will emerge as the new business diagnostic tooling infrastructure. LMArena is proving the financial thesis, raising a $100M seed round at a $600M valuation by monetizing trust and advanced enterprise analytics for LLMs.

Ecosystem: Rumored to be integrating SAI eval platform alongside major robotic simulation ecosystems such as Isaac Sim (NVIDIA) and MuJoCo (Google).

“Robotics is currently stuck in the "demo-ware" and lacks the vital evaluation infrastructure that propelled the LLM revolution. The most valuable unclaimed category is this missing benchmarking standard. We are building the independent evaluation layer the industry desperately needs.” - Wei Xie, Co-Founder and COO, ArenaX Labs

3.7 XMAQUINA ($DEUS)

XMAQUINA. Humanoid Robotics Investment DAO

XMAQUINA, ticker $DEUS, enables anyone to invest in early stage robotics companies. What was only previously possible to large ticket investors like a16z, by holding $DEUS, you can participate in private venture rounds of robotics companies like 1x, Agility etc.

$DEUS currently has a treasury Net Asset Value (NAV) of ~$36M, including Equity stakes in Figure, Apptronik, Agility Robotics, NEURA Robotics and 1X Tech:

XMAQUINA treasury

Share of treasury value by holding.

Stablecoins and cash

  • USDC39%
  • USD0%

Robotics portfolio

  • Apptronik34%
  • 1X13%
  • Agility Robotics6%
  • Figure AI6%

Crypto assets

  • PEAQ2%
Source: XMAQUINA DAO treasury.

Think of this similar to the thesis for gaming DAOs in 2021 - a holder of gaming tokens like YGG and BEAM back in 2021 offered investors index exposure to web3 gaming, XMAQUINA is taking a similar concept to enable retail to participate in early stage robotic investments.

Capital was raised through tranches of sales of its DEUS token, which at the time of writing was scheduled to launch within eight weeks, with the following details:

  • TGE Trigger: Requires DAO governance vote (not automatic timeline)
  • Vesting Structure: 33% unlock at TGE, 67% linear over 12 months
  • Cross-chain: Deployed on Base and peaq via LayerZero

Value Accrual Mechanisms

  • No Management Fees: Zero traditional 2% VC-style annual fees
  • Team Compensation: Via vested token allocation (12.5%) + Foundation (7.5%)
  • Revenue Flow: All profits to DAO treasury for DEUS holder benefits
  • Sustainability: 5% allocation from sub-DAO tokens + machine revenue
  • Buyback Mechanisms: Treasury returns fund DEUS buybacks/rewards
  • Dividend Alternative: Revenue sharing vs. traditional equity distributions
  • Self-Funding: Post-TGE operations funded by returns, not fees

The value in this protocol is in the types of private investments that XMAQUINA is able to make by leveraging its network opportunity access, which is clearly strong based on its existing treasury.

The veDEUS token model enables holders to govern the activity of the DAO. For example, distributing the benefits (capital appreciation or dividends) of these underlying robotics businesses (through buybacks or otherwise).

The DEUS token should track the performance of the underlying robotics businesses it invests in, but there will likely be a deviation from its treasury Net Asset Value (NAV) for several reasons; including market access, liquidity, and/or conversely; impairment indicators.

But the ability to actively trade or gain exposure to otherwise private robotics markets demonstrates the real value of bringing capital markets onchain, particularly the less efficient private markets that typically only permit access to accredited investors.

As regulatory clarity is provided around ownership rights for tokenholders then we could see an “ICO” season as businesses come onchain and investment vehicles, like XMAQUINA, become more globally accepted.

“Access to private equity in deep tech, especially in the AI and humanoid segment, has traditionally been restricted to a small group of institutional investors. XMAQUINA is designed to change that. Through a governed, onchain structure, we’ve built exposure to leading companies in the field, including Figure, 1X Technologies, Agility Robotics, and Apptronik, with a growing pipeline that includes NEURA Robotics and others.

These positions offer $DEUS holders real exposure to a sector that is not only transforming labor, but also reshaping logistics, mobility, manufacturing, and human-machine systems.”
- Mauricio Zolliker, Founding Member of XMAQUINA

In an auction with Virtuals Protocol that opened on January 8, 2026, XMAQUINA raised an additional $3.25M. This brings the total to $10M raised for the DAO to participate in investments.

3.8 Bittensor Subnets ($TAO)

Bittensor. Decentralized Fabric for AI + Robotics

Bittensor ($TAO) is an ecosystem of subnets that are tailored specifically to a variety of real world use cases, a number of which have been identified as world class AI models.

Several subnets are relevant to robotics:

Table of thirteen Bittensor subnets relevant to robotics, with focus and impact, including SN3 Templar pre-training, SN13 Data Universe data scraping, SN17 404-Gen 3D models, SN18 Zeus weather, SN26 Kinitro embodied training, SN44 Score computer vision, SN72 StreetVision and SN124 Swarm drone flight.

Robotics requires massive multi-modal data and continuous fine-tuning. Centralized AI systems struggle to scale across variations in hardware, environment, and policy.

Bittensor provides a market for intelligence, letting robots pay for the skills they need (including edge cases), particularly as payment protocols (like x402) provide the infra for trillions of agentic micropayments.

3.9 OpenMind (Pre-TGE)

Openmind AI: The “Android for Robots”

OpenMind provides the foundational software layer for autonomous robotics through OM1, an open-source AI-native operating system handling perception, memory, planning, and action.

Similar to how Android unified mobile devices, but purpose-built for intelligent machines.

OpenMind OM1 architecture diagram. Sensor inputs (vision, sound, battery, GPS, lidar) become natural language on a data bus, are fused, then feed a fast local action LLM and multi-agent planners at 300 ms, 2 s and 30 s, driving movement, speech, expression and wallet.

Complementing OM1 is “FABRIC”, a decentralized coordination network that enables robot identity verification, proof-of-location, task coordination, and autonomous stablecoin settlements for machine-to-machine collaboration across diverse hardware platforms.

Economics

With $20M funding raised in August 2025 led by Pantera Capital (Coinbase Ventures, DCG, Ribbit Capital participating), OpenMind remains pre-TGE with no token launched as of December 2025.

The project focuses on building organic developer adoption through its Developer League program ($250K in credits for OM1 contributors), which has attracted over 100 contributors and 10,000+ users building on the platform.

Partnerships

The recent Circle partnership (December 2, 2025) introduces the x402 payment protocol using USDC for autonomous M2M transactions, while the NEAR Protocol integration (December 3, 2025) brings hardware-backed privacy AI services through verifiable Trusted Execution Environments (“TEEs”).

Millions of robots will be produced from a variety of manufacturers in the coming years; having a foundational software layer like OM1, will be imperative for seamless operational performance across the varying stacks.

"AIs, when given full control of highly mobile physical shells, can explore the world, learn, interact, chase squirrels, and help blind people. Let’s make this new world open and durably aligned with humans. This means (1) open software and (2) modular brain architectures that allow humans to inspect, understand, trust, and debug thinking machines." - Jan Liphardt, Founder Openmind

04Strategic Advantages of Decentralized Robotics Networks

The composability between these networks is a core strategic edge.

Table of decentralized advantages by category with example project logos: Economics, fractional ownership and revenue sharing; Data, permissionless contribution; Coordination, robust scaling and local autonomy; Infrastructure, distributed hardware flywheels (Auki, GEODNET); Identity and Transactions, machine wallets (peaq, x402).

Example:

Peaq (payments + identity) + GEODNET (positioning) + Auki (shared mapping) = autonomous, location-aware robotic fleets

Equation-style diagram: peaq payments and identity, plus GEODNET decentralized GNSS positioning, plus Auki shared spatial mapping, equals fully autonomous, location-aware robotic fleets.

Openmind and Codec are prime examples that offer robotics agnostic software developer kits (SDK) that can then be plugged into any traditional robotics hardware, rather than having to have the “Apptronik SDK” or “Figure SDK”, specifically.

05Risk Factors

Sector remains high variance, but risk is distributed across multiple protocol layers.

Risks, impact and signals to watch
Risk TypeImpactMitigation Signals to Watch
TechnicalRobotics hardware progress may lag expectationsMonitor humanoid manufacturing cost curves
AI PerformanceEmbodied intelligence may require larger datasets than expectedScaling of Bittensor robotic subnets
RegulatoryAutonomous systems may face jurisdictional restrictionspeaq’s regulatory MoUs (e.g., Dubai VARA)
Token DesignEconomic leakage if contribution incentives weakenSustained burn, fee and revenue share mechanisms

Much of the DeRobotics will be focused on the software, while traditional robotics entities build out the hardware capabilities. The main reason for this is funding; it costs magnitudes more to develop physical infrastructure, particularly at scale to enable an affordable entry.

06Investment Outlook

6.1 Valuation Asymmetry

Traditional robotics equities are valued in the tens to hundreds of billions, while DeRobotics tokens trade at sub-$1B valuations despite similar market exposure.

The projects covered in this report constitute <$200M (27%) of the overall market capitalization of DeRobotics segment:

Table of covered projects by 2025 market cap and network maturity: peaq about $50M, GEODNET $60M with $7M ARR, Bittensor $2.3B, Codec $20M, Auki $30M, Neuron (NRN) $5M, XMAQUINA pre-TGE at about $30M NAV, BitRobot and OpenMind pre-TGE.

The driver for the comparably low market cap (compared to traditional robotics) is that most of the large robotics companies deal with hardware, which inevitably has a significant amount more initial capital outlay and fundamental value than software, given the tangible materials consumed. Particularly as raw material prices continue to soar.

07Scenario Table

3-5 Year Horizon

Valuation scenarios for the DeRobotics sector over a 3 to 5 year horizon from a $750M spot market cap: bear case $5.2B (7x), base case $38.7B (52x), bull case $55.6B (74x), with an accompanying table of the same figures in millions.

Assumptions:

  • 1-3% early adopters by 2026
  • 10-15% penetration by 2030
  • Commercial Adoption: Warehouse, retail, and agriculture robotics continue 20-30% CAGR seen in industrial automation
  • Government Adoption: National policies continue favoring domestic robotics and semiconductor production, helping subsidize deployments
  • Dataset Growth: Robotics datasets grow 10x between 2025-2030
  • Robotics Market Growth: Move consistently with traditional robotics % CAGR
  • Token Economics: Network fees scale with activity (Token buybacks tied to real revenue create direct value accrual)