Sahara AI: Building the "Decentralized Ethereum" in the AI Field

1. Project Introduction

1. Project Basic Information

Sahara AI is a full-stack, native AI decentralized blockchain platform. Its core vision is to break the current artificial intelligence landscape dominated by a few large tech companies and to build an open AI collaborative economy driven by a global community that contributes verifiable and fairly distributed benefits.

The fundamental mission of the project is to provide transparent attribution, complete ownership control, and efficient on-chain monetization channels for AI assets (including datasets, models, and agents) through blockchain technology. Essentially, Sahara AI is committed to becoming the "Ethereum of the AI field," providing secure and trustworthy underlying infrastructure for the next generation of decentralized AI applications, ultimately returning ownership and value of data and AI innovations to every creator and contributor.

2. Project Development History

• Early 2023: The project officially started, initially envisioned to create exclusive "knowledge agents" for experts in different fields. Subsequently, the direction was adjusted to focus on the core element of "data", utilizing Web3 incentive mechanisms to begin building an ecosystem.

• Mid 2023: Completed a $6 million seed round financing led by Polychain Capital.

• 2024: Collaborate with major companies such as Microsoft and Amazon to secure relevant orders.

• August 2024: Secured $43 million in Series A funding led by Pantera, Binance Labs, and Polychain Capital.

• June 26, 2025: AI Agent Builder and AI Marketplace officially enter the public testing phase.

3. Core Issues and Solutions

Sahara AI has proposed a blockchain-based systematic solution to address the key pain points faced by the current centralized AI industry, such as data islands, ambiguous model ownership, high innovation costs, and unfair value distribution.

• Establish a Decentralization market that allows anyone to register and trade AI assets on-chain.
• Utilize the immutability of blockchain to record each contribution
• Provide standardized development tools, reduce development thresholds, and promote collaborative innovation globally.

4. Core Team Background

• Sean Ren (CEO): Professor of the University of Southern California, MIT TR35 Innovator
• Tyler Zhou (COO): Former Director of Investments at Binance Labs
• Technical Team: Members from Google Brain, Fetch.ai, Ocean Protocol, holding multiple patents in distributed machine learning.

2. Business Model

1. Platform Architecture and Core Technology

Sahara AI adopts a hybrid blockchain architecture optimized for AI application scenarios, including:

• Four-layer structure: application layer, transaction layer, data layer, and execution layer
• Hybrid mode: key metadata is recorded on-chain, while large datasets and AI models are stored off-chain.
• Core Main Chain: Developing its own Layer 1 blockchain Sahara Chain
• Security Certification: Achieved SOC2 enterprise-level security and privacy certification

2. Product Ecosystem

Sahara AI provides full lifecycle tools from data processing, model development to asset trading:

• Data Service Platform (DSP): Crowdsourced Data Annotation Platform
• Sahara Studio: One-stop development kit
• AI Exchange: A bridge connecting data contributors, model developers, and users.
• Secure Execution Environment: Ensure the safe execution of AI tasks

Currently, the platform has attracted over 200,000 global AI trainers, completing more than 3 million data annotation tasks in total.

3. Market Entry and Growth Strategies

Sahara AI adopts a dual-track strategy:

• User Acquisition: Launch "Knowledge Airdrop" program and testnet incentive activities
• Brand and Market: Launched on multiple leading exchanges, appearing in high-exposure channels.
• Ecological Incubation: Establish specialized incubators to support AI startup projects developed based on its ecosystem.

4. $SAHARA Token Economic Model

• Total Supply: 10 billion
• Allocation Plan:
  • Community and Ecosystem Development (64.25%)
  • Core Contributors (15%)
  • Early supporters (19.75%)
  • Liquidity and Market Stability (1%)
• Token generation and listing: Successfully launched on multiple mainstream exchanges in June 2025.

3. Project Prospects

1. Industry Analysis

The decentralized artificial intelligence market is expected to experience explosive growth, from approximately $2.5 billion in 2024 to over $80 billion by 2030, with a compound annual growth rate of over 60%.

2. Competitive Landscape Analysis

Sahara AI's main competitors include Bittensor (TAO), Olas (OLAS), and Ritual. Sahara AI has advantages in full-stack solutions and commercial implementation.

3. Development Plan

Short-term planning (1-2 years):

• Optimize core technology architecture
• Accelerate the official launch and improvement of AI AgentBuilder and AI Marketplace.
• Improve the incentive mechanism of SAHARA token

Mid-term plan (3-5 years):

• Achieve breakthroughs in cross-chain technology
• Build a globally leading Decentralization AI ecosystem
• Increase market promotion efforts to enhance global visibility.

Long-term planning (over 5 years):

• Become a leader in the Decentralization AI field
• Explore new application scenarios and business models for the integration of AI and blockchain.
• Build a highly prosperous and diverse ecosystem.

4. Summary

1. Core Conclusion

• Accurate positioning, grand vision
• Full-stack solutions form a core barrier
• The team has strong capital strength.
• The token economic model is designed reasonably.

2. Valuation and Investment Recommendations

• Valuation analysis: Listed with a fully diluted valuation of approximately $6 billion, which is at a high level.
• Investment advice: cautiously optimistic, buy on dips

3. Outlook

Sahara AI has the potential to become the underlying operating system for the future decentralized intelligent economy, and its success will have a profound impact on the entire industry, accelerating the popularization and democratization of AI technology, and giving rise to new business models and application scenarios.