Core positioning and vision
The Sentient Foundation is a non-profit organization focused on open-source general artificial intelligence (OpenAGI). Its core mission is to build a decentralized, community-owned AGI economic system that ensures AGI is open, transparent, and collaboratively built and shared by a global community, directly challenging the closed models of giants like OpenAI. The project aims to address the core pain points in the current AI field, such as unclear model ownership, unfair value distribution, and centralized risks, by proposing the OML (Open + Monetizable + Loyal) framework, emphasizing that open-source models can be profitable, controllable, and aligned with community values.
I. Technical architecture and core innovations
1. Layered technical system
- Open Intelligent Network (GRID): underlying infrastructure that connects models, agents, computing power, data, and developers, abstracting global distributed resources into schedulable computing units. It implements value mapping through a closed loop of 'execution-validation-incentive'.
- ROMA (Recursive Open Source Meta-Intelligent Agent) framework: a disruptive multi-agent system that automatically recursively decomposes complex tasks into parallel subtasks, with parent agents dispatching execution and aggregating results, adaptable to medium- to long-term multi-step tasks, incorporating financial analysis, deep research, and other professional agents.
- Model fingerprint recognition: injecting specific query-response pairs to generate model identity fingerprints, achieving traceability, behavior verification, and anti-counterfeiting, solving the problem of open-source model replication.
- On-chain training records: the entire training process and contribution data are verified on-chain, enhancing collaboration transparency and the basis for model assetization.
2. Differentiated technological advantages
Technical characteristics, value embodiment, application scenarios
Decentralized collaboration eliminates single points of failure, reduces computing costs, and enhances model robustness for large-scale distributed training and multi-institutional joint R&D.
OML framework ensures model loyalty, prevents AI misconduct, and protects user interests in financial services, medical diagnosis, and safety-critical systems.
The ROMA recursive architecture enhances the efficiency of solving complex tasks and lowers the development threshold for investment research, legal consulting, and industrial design.
On-chain assetization realizes quantitative and liquid model value, incentivizing developers to contribute to the AI model trading market and intellectual property protection.
II. Token economics (Tokenomics)
Core data
- Total supply: 34,359,738,368 tokens (2³⁵), fixed supply with no inflation.
- Circulating supply: 7.24B SENT (21.07%), current market cap approximately **$255M** (ranked #98)
- Distribution mechanism (high health):
- 44% community incentives and airdrops: directly empowering users and expanding the community base.
- 19.55% ecological R&D: continuous technological iteration to ensure long-term competitiveness of the project.
- 22% team and advisor: long-term lock-up, phased release to avoid short-term selling pressure.
- 12.45% investors: Pantera led a $87 million investment, with top institutions like Founders Fund participating and strict lock-up mechanisms.
- 2% public sale: reducing fundraising impact on the market.
Core functions of the token
1. Payment medium: used for model calls, computing power leasing, data purchasing, and other ecological transactions.
2. Governance certificates: votes determine AGI development direction, fund allocation, and technical roadmap.
3. Incentive tools: reward model contributors, computing power providers, and community participants.
4. Value storage: capturing ecological growth value, increasing in value as network effects expand.
III. Financing and partnerships
1. Top-tier financing background
- In 2024, secured $87 million in seed round financing, led by Pantera Capital and Founders Fund, with participation from top institutions like Sequoia Capital and a16z, providing ample funding and industry credibility for the project.
- In January 2026, a new strategic investment from Franklin Templeton is planned to collaborate on promoting high-risk AI applications in the financial sector, bringing open-source inference into institutional production processes, marking recognition of project value by traditional financial giants.
2. Key partners
Partners, cooperation fields, strategic value
Polygon infrastructure deployment reduces gas costs, improves transaction speed, and is compatible with the Ethereum ecosystem.
Franklin Templeton financial AI applications verify commercial feasibility and explore the institutional customer market.
EigenLayer re-staking and security enhance network security and improve decentralization.
Major exchanges providing liquidity support include Binance, Coinbase, Upbit, and Bybit, forming a global liquidity network.
3. Community and ecological progress
- Binance trading competition ongoing (dividing a $50.7 million SENT prize pool), driving a surge in trading volume.
- 44% of tokens have been airdropped to the community, covering over a million users and establishing a large user base.
- Launching the Dobby vertical domain model (focusing on crypto and Web3), SERA-Crypto research agent (providing accurate insights into crypto within 30 seconds), and other ecological applications.
IV. Market performance and listing progress
1. Recent milestones
- January 22: Binance wallet opens for airdrop collection, TGE price approximately $0.0107.
- January 29: Upbit officially listed (17:30 KST), price surged from $0.022 to $0.036, with a 24-hour increase of 40.95%.
- January 30: current price $0.0352, market cap $255.03M, 24h trading volume $529.20M, turnover rate 207.5%, liquidity surges.
- Covers four major exchanges, forming a global liquidity network, with the Korean market becoming a new growth engine.
2. Growth drivers
- The overall recovery of the AI track, with companies like OpenAI concentrating on launching heavyweight products, boosts sector enthusiasm.
- Upbit's listing brings high liquidity to the Korean market, combined with Binance trading competition, doubling the trading volume.
- Franklin Templeton's strategic investment enhances project credibility and attracts institutional capital attention.
- Community scale continues to expand, ecological applications gradually land, enhancing actual demand for tokens.
V. Risk factor assessment
1. Technical risks
- AGI research and development is extremely difficult, the project is still in its early stages, and the effects of the ROMA framework and OML model need to be validated.
- Decentralized collaboration faces challenges of efficiency and consistency, which may affect model training speed and quality.
- On-chain training and storage costs are relatively high, requiring optimization of technology to lower thresholds.
2. Market risks
- Short-term price increase is too large (227% since TGE), RSI reached 78.36 (overbought), profit-taking pressure is rising.
- The AI token market is highly volatile, significantly influenced by macro environments and industry policies.
- Intense competition, facing dual competition from decentralized AI projects like Bittensor and SingularityNET, as well as giants like OpenAI.
3. Business risks
- The commercialization path is unclear, lacking stable income sources, relying on financing and token appreciation to maintain operations.
- Non-profit organizational models may limit resource acquisition and market expansion speed.
- Regulatory uncertainty is high, AGI policy risks are significant, which may affect project compliance.
VI. Fundamental scoring and investment prospects
Comprehensive score: 7.8/10
- Advantages: top-tier financing + innovative technology + healthy token economy + strong community, the AI + Web3 integration track has broad prospects, and the partnership with Franklin Templeton opens up the institutional market.
- Disadvantages: early stage + unclear commercialization + short-term overbought, requiring time to validate technological implementation and ecological expansion capabilities.
Medium to long-term outlook
- If the technology is successfully implemented, the ROMA framework and OML model are expected to become the standards for decentralized AGI, driving continuous growth in SENT value.
- Financial applications (in cooperation with Franklin Templeton) may become the first commercial breakthrough, validating model practicality and profitability.
- As the AI track continues to heat up, the recognition of the OpenAGI concept increases, and the project is expected to attract more developers and users, forming a positive cycle.
VII. Core conclusions and recommendations
Core judgments
SENT has a solid fundamental basis, with top-tier capital endorsement, innovative technical architecture, and a healthy token economy. Long-term value depends on technological implementation progress and ecological expansion speed. In the short term, prices have skyrocketed due to Upbit's listing and the AI hype, with clear overbought signals and rising pullback risks; in the medium to long term, if a decentralized AGI breakthrough can be achieved, it is expected to become a benchmark project in the AI + Web3 field.
Investment advice
1. Short term (1-4 weeks): mainly observe, wait for a pullback to the $0.030-$0.032 range before considering entry, set a stop loss at $0.028.
2. Medium term (1-3 months): focus on technological progress (ROMA framework optimization, model training outcomes) and the status of commercial cooperation, building positions in batches.
3. Long-term (6 months+): if the project achieves key technological breakthroughs and ecological expansion, target price $0.05-$0.06, corresponding to 4-5 times the TGE price.
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