Grass Depth Analysis: A Bright New Star in the DePIN Field, The Expansion Path of AI Data Bank

Key Points

• How does Grass stand out among numerous DePIN projects?

The core factor is a zero-threshold mining model, users are the cornerstone, and other factors are all leverage.

Grass breaks through the DePIN industry barriers through the "technology + model" dual-wheel drive - utilizing zero-knowledge proofs and Solana Layer2 architecture to ensure data authenticity, addressing the "dirty data" pain points in the AI industry; at the same time, adopting the "bandwidth mining → points incentive" model to convert 2.5 million users into data nodes, forming a supply-side advantage.

With the explosive demand for AI data, the popularity of the Solana ecosystem and the DePIN concept, as well as reasonable operational strategies, it has achieved a leading position in the field of AI data DePIN.

• What key factors need to be considered for the future development of Grass?

Short-term view on technology implementation: Will the decentralized transformation be successfully completed by 2025;

Mid-term Demand Validation: Data procurement scale of AI companies;

Long-term Compliance Game: Data Privacy and Ownership Rules.

The current biggest risk is "Token frenzy masks demand vacuum" - if future growth in AI customer orders cannot be achieved, the perfect business closed loop may degrade from the positive cycle of "data-capital" to a supply-side bubble.

1. Industry Background

When the democratization of DePIN's computing power meets the data dilemma of AI, a quiet movement for data equality has quietly emerged.

DePIN integrates global idle resources ( computing power, storage, bandwidth ) through token economics to build a distributed infrastructure network; at the same time, the AI industry faces a structural shortage of data, with monopolies, privacy controversies, and silo barriers among giants, resulting in 80% of data value being unreleased.

The future AI competition is essentially a dual game of data acquisition efficiency and ethical compliance, and DePIN provides the optimal technical solution.

The disruptive nature of Grass lies in the realization of the fusion of these two.

1.1 DePIN: A Global Paradigm for Restructuring Infrastructure

Definition and Core Logic

In recent years, with the maturity of blockchain technology and the rise of the Web3 concept, various industries are exploring decentralized transformation paths. DePIN is precisely the embodiment of this trend in the infrastructure field. DePIN( stands for Decentralized Physical Infrastructure Networks, which is a decentralized physical infrastructure network ) that integrates globally dispersed physical resources ( such as computing power, storage, bandwidth, and energy through blockchain technology, creating a new economic model.

The core logic lies in: driving community contributions of idle resources through token incentives to build a decentralized infrastructure network, replacing the high-cost, low-efficiency model of traditional centralized service providers.

Industry Drivers

Compared to the centralized model, the decentralized transformation of physical infrastructure has greater advantages in terms of cost structure, governance model, network resilience, and ecological scalability.

Subfields and Typical Cases

According to Messari's definition, DePIN encompasses physical infrastructure ) such as wireless networks, energy networks ( and digital resource networks ) such as storage, computing (, achieving supply-demand matching and incentive mechanisms through blockchain technology.

• Physical Infrastructure: Represented by the Helium) decentralized wireless network(, a globally covered communication network is built through community deployment of hotspot devices;

• Digital Resource Network: Includes Filecoin) decentralized storage(, Aethir) distributed computing(, etc., forming a shared economy model by integrating idle resources.

Market Potential

According to Messari data, as of 2024, the number of global DePIN devices has exceeded 13 million, with a market size of $50 billion, but the penetration rate is less than 0.1%. It is expected to grow 100-1000 times in the next decade.

In 2024, the total market value of the DePIN track will reach 50 billion USD, covering more than 350 projects, with an annual growth rate exceeding 35%.

Its core driving force lies in the improvement of resource efficiency ), such as the utilization of idle bandwidth ( and the explosive demand ), such as AI's demand for computing power and data (, creating a bilateral effect.

Of course, the scalability, data privacy, and security verification of decentralized networks remain key challenges for DePIN development.

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) 1.2 AI Data Demand: Explosive Growth and Structural Contradictions

"Data is the new oil ###Data is the new oil("

The acquisition and processing of AI data is the core driving force behind the development of artificial intelligence, especially when training large language models ) such as GPT ( and generative neural networks ) like MidJourney (.

The performance and effectiveness of AI models largely depend on the quality and quantity of the training data. High-quality, diverse, and geographically representative data is crucial for the performance of AI models.

Data Demand Scale and Characteristics

• Magnitude Leap: Taking GPT-4 as an example, training requires over 45TB of text data, while the iteration speed of generative AI demands real-time updates and diversification of data;

• Cost Ratio: The cost of data collection, cleaning, and labeling in AI development accounts for over 40% of the total budget, becoming a core bottleneck for commercialization;

• Scenario Differentiation: Autonomous driving requires high-precision sensor data, medical AI relies on privacy-compliant case databases, and social AI depends on user behavior data.

Traditional Data Supply Pain Points

• Data Barriers: Core enterprises/subjects and other giants control extensive data sources, creating high entry barriers and unfair pricing for small and medium developers;

• Data Silos: Data is often dispersed among different institutions and enterprises, facing numerous obstacles to sharing and circulation, resulting in insufficient utilization of data resources.

• Data Privacy: Data collection often involves privacy and copyright disputes, such as the Reddit API charging incident that sparked protests from developers;

• Inefficient circulation: Data silos and lack of standardization lead to duplicate collection, with global data utilization rate below 20%;

• Value Chain Disruption: Individual contributors who create data are unable to benefit from the subsequent use of that data.

The Path to Breakthrough for DePIN

• Distributed Data Collection: Collecting public data ) through a node network, such as social media and public databases (, reduces the cost of data collection and improves the efficiency and scale of data collection;

• Enhance data quality and diversity: Through the DePIN incentive mechanism, more participants can be attracted to contribute data, thereby improving the quality and diversity of data and enhancing the generalization ability of AI models.

• Decentralized Cleaning and Annotation: Community collaboration completes data preprocessing, combined with zero-knowledge proof )ZK( to ensure data authenticity;

• Tokenized Incentive Loop: Data contributors receive token rewards, while demanders purchase structured datasets with tokens, creating a direct match between supply and demand.

The Grass project is located at the intersection of DePIN and the AI data industry, innovatively applying the DePIN concept to the field of AI data collection, establishing a decentralized data scraping network aimed at providing a more economical, efficient, and reliable data source for AI model training.

In the following chapters, we will conduct a deep analysis of the specific mechanisms, technical features, application scenarios, and future development prospects of the Grass project.

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2. Basic Information of the Project

The rapid expansion of Grass is inseparable from its extremely low participation threshold. It allows every user to become a 'miner' of AI data, exchanging idle bandwidth for future dividends.

Grass builds a decentralized data crawling network through the DePIN architecture, providing cost-effective and diverse data sources for AI training. Users only need to install the client to contribute bandwidth and receive token rewards - attracting over 2.5 million nodes in one year, with a more than 5-fold increase in token price within the first 10 days of launch, validating its business logic.

The project has received backing from top-tier capital such as Polychain and Hack VC, relying on the high-performance Solana chain to achieve data rights confirmation and circulation.

The current team's anonymity is still under debate, and the progress of decentralized data processing needs to be followed up.

) 2.1 Scope of Business

Grass is a DePIN project that collects and verifies internet data through the unused bandwidth of user devices, specifically supporting the development of artificial intelligence ###AI(.

Its core is to allow companies to use users' internet connections through the residential proxy network ), to access and scrape internet data from different geographical locations, which is very useful for AI model training that requires diverse and geographically representative data.

• Problems Solved: Traditional web scraping is typically performed by centralized systems, which are inefficient and prone to errors or biases. Grass aims to provide reliable, verified internet data through a decentralized approach, and the data provided by decentralized users naturally possesses characteristics of diversity, multi-regional distribution, and real-time availability.

• Vision and Mission: Grass's vision is to create a decentralized internet data layer where data is collected, verified, and structured in a trust-minimized manner. Its mission is to empower users to contribute to the data layer and incentivize participation through a reward mechanism.

• User Participation Method: Users can get started in just three steps: visit the Grass official website, install the extension/client, connect, and start earning Grass Points. This contribution of bandwidth to earn rewards provides ordinary users with an opportunity to share in the AI growth dividends.

In summary, the key features and advantages of Grass are: low cost of data retrieval in a decentralized network, richer diversity of data; users earn rewards by contributing bandwidth, realizing the return of data value; using blockchain technology to verify data, ensuring the transparency and reliability of the data.

( 2.2 Development History

Concept Phase: In mid-2022, the project was proposed by Wynd Labs.

Development Stage: Product construction began in early 2023, marking the project's entry into the actual development stage.

Seed Round Financing: In 2023, Grass completed a $3.5 million seed round financing, led by Polychain Capital and Tribe Capital, totaling $4.5 million ) including a pre-seed round led by No Limit Holdings ###.

User Testing: At the end of 2023, launch a Chrome browser extension and start user testing to attract early users to participate.

Milestone: In April 2024, the project announced that it has surpassed 2 million connected node devices and is growing rapidly. According to DePIN Scan data, as of March 2025, its active users have exceeded 2.5 million.

First Airdrop: The first airdrop will be announced on October 21, 2024, distributing 100 million GRASS tokens, 10% of the total supply, as a reward for early users.

Listed Exchanges: Launched on a certain trading platform and other exchanges on October 28, 2024, the price increased steadily from $0.6 to $3.89 in 10 days, roughly a 5-fold increase.

Current Status: The project continues to expand, and the second phase of user mining incentives is underway; plans to launch Android and iPhone mobile applications to increase network scale and user engagement.

( 2.3 Team Situation

According to Rootdata, Grass was developed by Wynd Labs, founded by Andrej Radonjic, who is the CEO of Wynd Labs and holds a Master's degree in Mathematics and Statistics from York University and a Bachelor's degree in Engineering Physics from McMaster University.

The team members are all from Wynd Labs, focusing on blockchain and AI technology development, and have experience in relevant fields. However, specific member information has not been widely disclosed, with only Radonjic's identity being revealed.

According to Tracxn, Wynd Labs was founded in 2022, and its core product is Grass.

) 2.4 Financing and Key Partners

Investors and Support

Seed Round: Completed a $3.5 million seed round financing in 2023, led by Polychain Capital and Tribe Capital. According to Rootdata, the total financing after the seed round reached $4.5 million, including the pre-seed round led by No Limit Holdings.

Series A Financing: Completed Series A financing in September 2024, led by HackVC with participation from Polychain, Delphi, Lattice, and Brevan Howard, with the amount undisclosed.

Investor Support: HackVC, Polychain, Delphi, Lattice, and Brevan Howard are all relatively well-known investors in the industry.