Research Report｜FLock.io Project Overview & $FLOCK Valuation Analysis

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西格玛学长2025/06/09 03:30

By:西格玛学长

1. Project Overview

FLock is a decentralized privacy-preserving platform for the AI ecosystem, leveraging blockchain and federated learning to address data monopolies and privacy risks in traditional AI systems. The platform pioneered the concept of Federated Learning Blocks (FLocks), enabling collaborative AI model training and optimization without raw data ever leaving the user’s local environment, thereby maximizing data sovereignty.

By integrating on-chain incentives and a privacy-secure architecture, FLock brings together developers, validators, delegators, and model users to co-build its ecosystem. To date, over 176 AI developers, 236 validators, 1,203 delegators, and 700,000 model users have participated, contributing to the training and validation of more than 6,500 AI models.

The core team is led by Jiahao Sun, an Oxford alum and former Director of AI at the Royal Bank of Canada, serving as Founder and CEO. The team also includes Chief AI Scientist Zehua Cheng, CFO Vincent Z. Wang, and Head of Operations Leo Peng, all with solid backgrounds in AI, cryptography, and finance, ensuring strong technical depth and industry execution.

Research Report｜FLock.io Project Overview & $FLOCK Valuation Analysis image 0

Funding-wise, FLock has raised $9 million across two rounds. A $6M seed round was closed in March 2024 with investors such as Faction, DCG, OKX Ventures, Volt Capital, Inception Capital, Hyperithm, Tagus Capital, and Martin Köppelmann. In December 2024, it secured a $3M strategic round led by DCG, Animoca Brands, Fenbushi Capital, GSR, and Gnosis VC, securing top-tier backing for ecosystem growth and R&D.

2. Key Highlights

1. Decentralized AI Architecture with Built-in Privacy

FLock innovatively combines federated learning with blockchain to enable collaborative model training without exposing raw data. Users upload only local model weights or gradients, mitigating risks of data leakage, regulatory violations, and cross-border issues. This approach is especially well-suited for data-sensitive industries like healthcare, finance, and education, offering long-term scalability and practical deployment potential.

2. Full-Stack Incentive Mechanism Enabling Data & Compute Market

The platform uses the $FLOCK token to power an incentive model spanning data contribution, model training, validation, and hosting. Rewards are distributed to training nodes, validators, model users, and delegators, creating a multi-sided network of data × compute × model × governance. With 176 developers, 236 validators, and 1,203 delegators, FLock has supported 6,546 models trained and 575,900+ verifications, showcasing real on-chain activity and incentive effectiveness.

3. DAO Governance for Ecosystem Consensus & Sustainable Evolution

FLock is governed by its community, not a centralized entity. All $FLOCK holders can vote on key protocol parameters (e.g., reward ratios, task weights, model listing standards) and submit proposals for new features or subsystems. Currently, 5.44% of $FLOCK is staked in governance, validating the feasibility of community consensus and paving the way for distributed collaboration at scale.

4. Top-Tier Team and Strategic Backers

Led by Oxford alum Jiahao Sun, the team includes talents from Imperial College London, Meta, Web3 infra startups, and the federated learning space—with full-stack capabilities from research to deployment. With $9M raised from top-tier investors including DCG, Animoca Brands, Fenbushi, OKX Ventures, and Gnosis VC, FLock benefits not only from capital but also strategic support across ecosystem access, model integration, and exchange listings.

3. Valuation Outlook

$FLOCK positions itself as a Web3 data privacy infrastructure for the AI era, combining federated learning and blockchain to build a collaborative and verifiable AI model training network. It incentivizes community participation through data, compute, and algorithm contributions—democratizing AI capabilities while preserving privacy.

FLock represents an AI + DePIN hybrid model that emphasizes data sovereignty and fair incentives. Given the strengthening AI infrastructure narrative, the project is well-aligned for long-term growth with strong thematic focus.

Compared to similar Web3 AI infra projects such as Alchemist AI (no-code AI builder), elizaOS (AI agent OS), and Render (decentralized GPU network)—each with valuations between $100M and $1B— FLock remains significantly undervalued, leaving room for substantial re-rating.

4. Tokenomics

Total Supply: 1,000,000,000 $FLOCK

Token Allocation:

Community: 47.00% (470M)
- TGE Unlock: 10.64% (50M)
- Cliff: 0 months; Vesting: 60 months linear
Team & Advisors: 17.00% (170M)
- TGE Unlock: 0%
- Cliff: 12 months; Vesting: 24 months; Total: 36 months
Ecosystem: 19.70% (197M)
- TGE Unlock: 40% (78.8M)
- Cliff: 0 months; Vesting: 48 months
Investors: 16.30% (163M)
- TGE Unlock: 0%
- Cliff: 12 months; Vesting: 24 months; Total: 36 months

Token Utility:

Task Participation & Contribution Rewards
1. All participants (devs, validators, nodes, delegators) must stake/use $FLOCK to join tasks.
2. Data contribution, training, and validation are rewarded with $FLOCK, establishing a positive feedback loop.
Payment & Usage
1. $FLOCK is used to access hosted models on the AI Marketplace—covering API calls, inference requests, custom model builds, etc.
2. Developers pay $FLOCK for model deployment and access, generating usage-side demand.
Task Bounties & Delegation
1. Task creators can set bounties in $FLOCK to attract high-quality node operators for training/validation.
2. Users can delegate $FLOCK to validators or nodes and share in rewards, improving accessibility and token utilization.
Community Governance
1. Token holders can participate in FLock DAO to propose/vote on protocol upgrades, parameters, new features, etc.
2. $FLOCK holders drive protocol direction, emphasizing governance utility.
Staking & Security
1. Nodes must stake $FLOCK to train/validate models; malicious behavior is punished via slashing.
2. This ensures trust and reliability while rewarding honest contributors.

5. Team & Funding

Team Overview: FLock is founded by Jiahao Sun, Oxford alum and former Director of AI at RBC. Key members include Chief AI Scientist Zehua Cheng, CFO Vincent Z. Wang, Ops Lead Leo Peng, and Chief of Staff Sameeha Rehman—bringing strong AI, blockchain, and global operations experience.

Funding Rounds:

Seed Round (Mar 2024): $6M
- Investors: DCG, OKX Ventures, Faction, Volt Capital, Inception Capital, Hyperithm, Tagus Capital
Strategic Round (Dec 2024): $3M
- Investors: DCG, Animoca Brands, Fenbushi Capital, GSR, Gnosis VC, Bas1s Ventures

6. Risk Factors

Multilateral Incentive Risks: While FLock’s incentive model effectively engages developers, validators, and delegators, it could attract strategic exploitation—e.g., spam models, incentive farming, validation manipulation. If not mitigated, these behaviors may cause negative feedback loops.
Ecosystem Participation Dependence: FLock’s model heavily depends on community-driven training, validation, and governance. Attracting and retaining high-quality node operators is critical. Without sufficient activity, the platform may face both underperformance in model quality and governance inefficacy.

7. Official Links

Website: https://www.flock.io/
Twitter: https://x.com/flock_io
Telegram: https://t.me/flock_io_community

Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.

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