AI×Crypto Intersection: In-depth Analysis of Five Major AI Layer1 Projects

Author: Biteye core contributor Louis

Editor: Biteye core contributor Denise

With the rapid development of AI technology, traditional blockchain architecture can no longer meet the high-performance computing and complex data processing requirements of AI applications. This has led to the rise of Layer 1 blockchain platforms optimized for AI, which are diverse in terms of technical architecture, application scenarios and business models.

This study provides an in-depth analysis of five leading AI Layer1s: Bittensor, Vana, Kite AI, Nillion, and Sahara.

01. Bittensor: Decentralized AI Network Infrastructure

As an early explorer in the field of blockchain AI, Bittensor is committed to building an open decentralized artificial intelligence collaboration network.

Its goal is to break down the centralized barriers in traditional AI research and development, allowing more participants to contribute and benefit together.

Unlike traditional centralized AI systems (such as companies like OpenAI), Bittensor has created an open peer-to-peer ecosystem where participants can receive corresponding rewards based on their contributions to the network.

Bittensor's technical architecture adopts a two-layer structure design:

• Root network (main network): responsible for the coordination, verification and issuance management of the entire system, and is the hub for the allocation of network resources.
• Subnet Ecosystem: Each subnet is like an independent AI laboratory, developing professional solutions for specific AI application scenarios and proving its value in market competition.

This design allows Bittensor to balance the stability of the overall network with the professionalism in various fields, providing a flexible infrastructure for the development of decentralized AI.

Ecological Development Progress

• The number of subnets has expanded from 32 in the early stage to more than 64, covering a variety of AI application scenarios such as text generation, trading signals, and data annotation.
• The number of active users has reached 140,000, doubling from the previous year
• The total market value of the subnet exceeds 100 million US dollars, and the daily transaction volume remains at around 45 million US dollars
• Institutional participation has increased significantly. The well-known fund Grayscale has included TAO in its decentralized AI fund, with the weight adjusted to 29.55%.

These data show that Bittensor is gaining recognition from more and more market participants, and its ecosystem is entering a healthy development track.

The dTAO (dynamic TAO) system upgrade recently completed by Bittensor is an important innovation in its economic model. The core of this upgrade is to optimize the allocation mechanism of the TAO token, from a resource allocation method that relies on the subjective judgment of the validator to a more market-oriented allocation mechanism, so that resources can flow more accurately to those truly competitive subnets.

The original economic model of Bittensor exposed several key problems in actual operation:

1. The evaluation mechanism lacks objectivity: As the number of subnets increases, it becomes difficult for validators to comprehensively and objectively evaluate the actual value of each subnet, and the allocation efficiency gradually decreases.

2. Imbalanced power structure: Many validators are also subnet operators. This overlapping role can easily lead to conflicts of interest. Validators may favor the subnets they participate in, or even engage in private transactions.

3. Participation barriers: It is difficult for ordinary TAO holders to directly influence the network’s resource allocation decisions, and power is overly concentrated in the hands of a few validators.

To address these issues, the dTAO upgrade introduces a dynamic resource allocation system based on market mechanisms.

This system transforms each subnet into an independent economic unit, driving resource allocation through actual user demand. Its core innovation is the subnet token (Alpha token) mechanism:

• How it works: Users can obtain Alpha tokens issued by each subnet by staking TAO. These tokens represent the user’s support for a specific subnet.
• Resource allocation logic: The market price of the Alpha token becomes a signal to measure the intensity of subnet demand. Initially, the price of the alpha token is the same, and there is only 1 TAO and 1 alpha token in each pool. As the liquidity of the two tokens in the subnet is added, the price of the alpha token will also change accordingly. The emission of TAO is distributed in proportion to the price of the subnet token in all tokens. The subnet with a higher price will receive more TAO allocation, thereby achieving automatic optimization of resource allocation.

This mechanism significantly improves the efficiency and fairness of resource allocation, makes the value of TAO tokens more stable, and provides more ways for ordinary users to participate in network governance.

The most active subnets include:

• Subnet 4 Targon: Focuses on AI reasoning services for text generation, featuring fast response and low cost
• Subnet 64 Chutes: Provides various LLM APIs to enable developers to build and deploy AI applications on the Bittensor network
• Subnet 8 PTN: Focusing on the financial field, it encourages miners to generate accurate trading signals through a reward mechanism, covering a variety of financial markets such as foreign exchange and cryptocurrency
• Subnet 52 Dojo: Doing data annotation, encouraging users to earn tokens through data annotation. Enter Yzi Labs and announced an investment in its parent company Tensorplex.

02. Vana: Data sovereignty and value reconstruction platform

The Vana project focuses on solving a core problem in today's digital economy: the ownership and value distribution of personal data. In the current Internet ecosystem, user data is mostly monopolized and controlled by large technology companies, while the users who actually create this data rarely benefit from it. Vana's innovation lies in establishing an ecosystem where users truly own and control their own data, while being able to obtain economic returns from it.

As an EVM-compatible Layer 1 blockchain network, Vana’s technical architecture consists of five core components:

1. Data Liquidity Layer: This is the core of the Vana network, which enables the incentive, aggregation and verification of data assets through data liquidity pools (DLP). Each DLP is a smart contract specifically used to aggregate a specific type of data asset, such as social media data, browsing history, etc.
2. Data Portability Layer: Ensures that user data can be easily transferred between different applications and AI models, enhancing the flexibility of data use.
3. Universal Connectome: Tracks real-time data flows across the entire ecosystem, forming a data ecosystem map to ensure system transparency.
4. Non-custodial data storage: An important innovation of Vana is its unique way of data management. The user's original data will not be on the chain, but the user will choose the storage location by himself, such as a cloud server or a personal device, which ensures that the user has full control over his own data.
5. Application ecosystem: Based on data, Vana has built an open application ecosystem where developers can use the data accumulated by DLP to build various innovative applications, including AI applications, and data contributors can receive dividend rewards from these applications.

This design enables Vana to create a fairer data value distribution mechanism while protecting user data privacy, providing an important data foundation for the development of decentralized AI.

Latest Developments

Vana's financing and cooperation expansion continue to advance:

• In February 2025, YZi Labs announced a strategic investment in Vana, and Binance founder CZ joined as an advisor.
• In terms of ecosystem construction, Vana has built data projects covering multiple fields from social media data to financial forecasting data, including: Finquarium (financial forecasting data), GPT Data DAO (ChatGPT chat data), Reddit Data DAO (Reddit user data), Volara (Twitter data), Flirtual (dating data), etc.
• Recently, Vana organized a hackathon during Eth Denver, offering a prize pool of up to $50,000 to encourage developers to build DataDAO and AI applications based on Vana data, further expanding its ecosystem.

These developments indicate that Vana is actively building a complete ecosystem around data ownership and value realization, and its development momentum deserves attention.

03. Kite AI: Technological breakthrough of AI native public chain

Kite AI is a native Layer 1 blockchain project focused on the AI field, built on the Avalanche framework. It is committed to solving the various challenges faced by traditional blockchains when dealing with AI assets, especially how to achieve transparent ownership and incentives for AI data, models, and intelligent contributions. Kite AI proposes four core technological innovations:

1.PoAI consensus mechanism: Proof of Attributed Intelligence is a consensus mechanism pioneered by Kite AI. Through a verifiable contribution record system on the chain, it accurately tracks the value contribution of data, models, and AI agents. The project has designed a dynamic reward pool mechanism to distribute income according to the contribution ratio, effectively solving the problems of "data black box" and "model plagiarism" in the traditional AI economy.

2. Combinable AI subnets: Kite AI adopts a modular architecture to support developers to build industry-specific AI collaborative ecosystems on demand. For example, in the medical subnet, patient data can be encrypted and authorized to pharmaceutical companies for AI model development. The benefits are distributed to data subjects, model developers, and subnet maintainers in a certain proportion, creating a win-win ecological environment for all parties.

3. AI native execution layer: Kite AI is building an on-chain AI native execution layer that specializes in AI computing tasks such as reasoning, embedding, and fine-tuning/training. Through this layer, users can authorize smart contract wallets to execute reasoning calls and interact with models. This execution layer not only supports blockchain transactions and state changes, but also integrates confidential computing environments (such as trusted execution environments TEE) to ensure data security and privacy protection during the computing process.

4. Decentralized Data Engine: Kite AI ensures that data creators receive fair benefits in AI workflows. The platform has built-in compliance modules that comply with regulations such as GDPR/CCPA, meeting data privacy requirements around the world and reducing compliance costs for developers.

These technological innovations enable Kite AI to create a more fair and transparent value distribution environment for AI developers and data providers, and promote the decentralized development of AI technology.

Development Status

Kite AI launched the incentive testnet on February 6, 2025, which is the first AI native Layer 1 sovereign blockchain testnet. The testnet performed well after it went online:

• Less than 70 hours after the testnet was launched, the number of connected wallets exceeded 100,000. As of now, a total of 1.95 million wallets have joined the incentive testnet V1, of which more than 1 million wallets have interacted with the AI agent, with a total call count of more than 115 million times.

• The project has a strong background and is built by an experienced Silicon Valley team. The co-founders all have deep technical leadership experience in the field of artificial intelligence and have worked for top technology companies such as Uber, Salesforce, and Databricks. The core team members come from industry-leading companies such as Google, BlackRock, Uber, and the NEAR Foundation, and have academic backgrounds from top universities such as MIT and Harvard.
• In terms of capital support, the project has received investments from top institutions such as General Catalyst, Hashed, Hashkey, Samsung Next, and has established technical partnerships with Eigenlayer, Sui, Avalanche, AWS, etc.
• As a member of the Avalanche InfraBUILDL (AI) program, Kite AI plays an active role in promoting the development of the Avalanche artificial intelligence ecosystem. This collaboration aims to make Avalanche the leading blockchain for AI applications.
• As the scale of the global data economy is expected to exceed US$70 billion in 2025, Kite AI is expected to become an important infrastructure for data rights confirmation and monetization, and its development potential is worth looking forward to.

04. Nillion: Frontier Exploration of Privacy Computing

Through its unique "blind computing" technology, Nillion is redefining the way sensitive data is handled, opening up new avenues for future digital privacy protection.

Nillion is a decentralized public network based on an innovative cryptographic primitive called Nil Message Compute (NMC), which allows network nodes to operate in a non-traditional blockchain manner. Founded in November 2021, the project is led by forward-thinking innovators such as Alex Page and Andrew Masanto, with the goal of creating a system that can securely process high-value data without exposing sensitive details.

Nillion’s core advantage lies in its “blind computing” capability – a process that allows data to remain encrypted throughout its lifecycle, including storage, transmission, and processing. Its technical architecture integrates a variety of cutting-edge privacy protection technologies:

• Multi-party computation (MPC): enables multiple nodes to collaborate on computing functions without disclosing their private inputs, achieving joint computing without sharing data.
• Fully Homomorphic Encryption (FHE): allows direct operations on encrypted data, ensuring that the data remains encrypted from beginning to end, providing privacy protection throughout the entire process.
• Zero-knowledge proof (ZKP): provides a way to verify calculations without disclosing any underlying data, enhancing the trustworthiness of the system.
• Nada language: This is a domain-specific language designed for creating secure MPC programs. It simplifies the development process of privacy-preserving applications and reduces the learning curve for developers.

Nillion's network architecture consists of three main layers: the processing layer (responsible for secure computing), the coordination layer (NilChain, managing inter-node communication), and the connection layer (connecting external systems as a gateway). This multi-layer architecture enables Nillion to provide powerful computing power while protecting data privacy, meeting the needs of various privacy-sensitive scenarios.

Latest development progress

According to the latest information, the development of the Nillion network is progressing steadily:

• The Nillion mainnet is scheduled to go live in March 2025 (this month). The total number of Nillion tokens is 1 billion, which is expected to be distributed when the mainnet is launched.
• In terms of financing, Nillion completed a $25 million financing led by Hack VC on October 30, 2024. Investors include well-known institutions such as HashKey Capital and Animoca Brands, as well as angel investors from projects such as Arbitrum, Worldcoin and Sei. This round of financing brings Nillion's cumulative financing amount to $45 million, providing sufficient financial support for the long-term development of the project.
• In terms of ecological expansion, Nillion has established integration relationships with multiple mainstream public chains such as NEAR Protocol, Aptos, Arbitrum, Mantle, Sei, etc. Through cooperation with NEAR Protocol, Nillion aims to enhance privacy tools and enable developers to innovate more effectively in the DeFi field.
• In terms of AI ecosystem, Nillion has established cooperation with multiple AI-related projects, including Ritual, Crush AI, Skillful AI, Virtuals Protocol, etc. For example, Virtuals Protocol is the largest multimodal AI proxy protocol at present. By cooperating with Nillion and using its secure computing infrastructure to support private training and reasoning of AI models, it has achieved a perfect combination of AI and privacy.

05. Sahara AI: A platform for building a new economy of AI assets

Project Development

The core concept of Sahara AI is to build a "human-AI collaborative network" that enables ordinary users, developers, and enterprises to participate in the creation, deployment, and monetization of AI assets. Through this collaborative model, Sahara AI hopes to lower the entry barrier for AI and allow every participant to share the dividends of industry growth. The project has successfully obtained a total of US$43 million in financing led by Binance Labs, Polychain Capital, and Pantera Capital.

The platform’s technical architecture consists of three key components:

1. Sahara Blockchain: Providing a foundation for secure, transparent transactions and efficient AI lifecycle management for the ecosystem

2. AI infrastructure: Distributed collaborative training and service capabilities that support advanced algorithms and computing frameworks

3. Sahara AI Marketplace: A decentralized trading center for AI assets

Together, these components form a complete ecosystem that supports the entire process from data collection and annotation to model training, deployment, and monetization.

Latest development progress

The Sahara AI project is in a rapid development stage, and its testnet has gone through several important stages:

• In December 2024, Sahara AI launched the first phase of the Beta version of the data service platform test network, which attracted more than 780,000 users to apply, of which more than 10,000 candidates were qualified to participate in the first batch. In this phase, participants can contribute to the AI ecosystem and receive rewards by completing data collection, optimization and labeling tasks.
• In February 2025, Sahara AI launched the second phase of the testnet, expanding the platform’s contributor base and introducing additional bounty opportunities. This phase further strengthens user participation in shaping the future of decentralized AI.
• The latest development is that Sahara AI announced that it will launch a public testnet called "SIWA" on March 10, 2025. This is considered to be the last major test before the launch of the Sahara AI mainnet and TGE, and may also be the last chance for participants to earn airdrop rewards (called "points").

Sahara AI has released its 2024-2025 roadmap, which includes several key milestones:

• Q4 2024: The data service platform and test network have been launched, and users can receive rewards through data collection and labeling.
• Q1 2025: AI Marketplace is launched, providing development tools and data service extensions, supporting model development, training and deployment, and introducing an early access program.
• Q2 2025: Launch the Sahara Studio tool suite, covering model training, deployment, and workflow management, to further optimize the developer experience.
• Q3 2025: Sahara Chain mainnet is released, providing a secure and transparent on-chain infrastructure for large-scale decentralized AI, while supporting the assetization and trading of data and models.

On March 1, 2025, Sahara AI launched an incubator program to discover and support the world's most promising AI x Web3 innovation projects. The program focuses on two tracks: AI infrastructure and AI applications. Teams with MVP maturity and above are welcome to participate. Successfully selected projects will have the opportunity to fully access the Sahara AI ecosystem and obtain exclusive technical support, market development resources and investment opportunities.

06. Conclusion

AI Layer 1 is at a critical stage of rapid evolution. This emerging track is reconstructing the underlying architecture of AI technology through decentralized infrastructure. From data rights confirmation to computing resource allocation, from model training to application deployment, these platforms are breaking through the limitations of traditional centralized AI systems and building a more open, transparent and efficient technology ecosystem. In the future, this track will continue to promote technological innovation and advance the evolution of artificial intelligence towards a more decentralized and collaborative development direction.