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, ensuring that AGI is open, transparent, and collaboratively built and shared by the global community, directly challenging the model of closed giants like OpenAI. The project aims to address the core pain points of unclear model ownership, unfair value distribution, and centralized risks in the current AI field, proposing the OML (Open + Monetizable + Loyal) framework, emphasizing that open-source models can be profitable, controllable, and aligned with community values.
1. Technical architecture and core innovations
1. Layered technical system
- Open Intelligent Network (GRID): Underlying infrastructure connecting models, agents, computing power, data, and developers, abstracting global distributed resources into schedulable computing units, achieving value mapping through a closed loop of 'execute-validate-incentivize'
- ROMA (Recursive Open Source Meta-Agent) framework: Disruptive multi-agent system that automatically recursively decomposes complex tasks into parallel sub-tasks, with a parent agent assigning execution and summarizing results, adaptable to medium to long-term multi-step tasks, with built-in financial analysis and in-depth research professional agents
- Model fingerprint recognition: Injecting specific queries—responses 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 training process and contribution data are fully certified on-chain, enhancing collaboration transparency and the foundation for assetization of models
2. Differentiated technical advantages
Technical characteristics, value reflection, application scenarios
Decentralized collaboration eliminates single points of failure, reduces computing costs, and enhances model robustness through large-scale distributed training and joint research and development among multiple institutions
OML framework ensures model loyalty, prevents AI from causing harm, and protects user interests in financial services, medical diagnostics, and safety-critical systems
ROMA recursive architecture enhances the efficiency of solving complex tasks and lowers development barriers for investment research, legal consulting, and industrial design
On-chain assetization realizing model value quantification and circulation, incentivizing developers' contributions to AI model trading markets, and intellectual property protection
2. Token economics
Core data
- Total supply: 34,359,738,368 units (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, expanding the community base
- 19.55% ecological research and development: Continuous technical iteration to ensure the project's long-term competitiveness
- 22% team and advisors: Long-term lock-up, released in phases to avoid short-term selling pressure
- 12.45% investors: Pantera led $87 million, with top institutions like Founders Fund participating, with strict lock-up mechanisms
- 2% public sale: Reducing the fundraising impact on the market
Core functions of the token
1. Payment medium: Used for model invocation, computing power leasing, data purchases, and other ecological transactions
2. Governance certificate: Voting to determine the direction of AGI development, fund allocation, and technical roadmap
3. Incentive tools: Rewarding model contributors, computing power providers, and community participants
4. Value storage: Capturing the value of ecological growth, appreciating with the expansion of network effects
3. Financing and partners
1. Top-tier financing background
- In 2024, $87 million seed round financing was obtained, led by Pantera Capital and Founders Fund, with participation from top institutions including Sequoia Capital and a16z, providing ample funds and industry credibility for the project
- In January 2026, additional strategic investment from Franklin Templeton is planned to advance high-risk AI applications in the financial sector, introducing open-source reasoning into institutional-level production processes, marking traditional financial giants' recognition of the project's value
2. Key partners
Partners, collaboration areas, strategic value
Polygon infrastructure deployment reduces gas costs, increases transaction speed, and is compatible with the Ethereum ecosystem
Franklin Templeton Financial AI applications validate commercial feasibility and expand the institutional client market
EigenLayer re-staking and security enhance network security and decentralization
Major exchanges support liquidity: Binance, Coinbase, Upbit, Bybit are listed, and a global liquidity network is taking shape
3. Community and ecological progress
- The Binance trading competition is 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, establishing a large user base
- Launching the Dobby vertical domain model (focusing on cryptocurrency and Web3), SERA-Crypto research agent (providing precise insights within 30 seconds) and other ecological applications
4. 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 soared from $0.022 to $0.036, 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 surging
- Covering four major exchanges, a global liquidity network is taking shape, with the Korean market becoming a new growth engine
2. Growth drivers
- The AI sector is on an overall rebound, with companies like OpenAI releasing major products, driving up the sector's heat
- Upbit's listing brought high liquidity to the Korean market, combined with the Binance trading competition, doubling trading volume
- Franklin Templeton's strategic investment enhances the project's credibility, attracting institutional funding attention
- The community scale continues to expand, ecological applications gradually land, increasing the actual demand for token usage
5. Risk factor assessment
1. Technical risks
- The difficulty of AGI research and development is extremely high, the project is still in its early stages, and the effectiveness of the ROMA framework and OML model implementation remains to be verified
- Decentralized collaboration faces challenges of efficiency and consistency, which may affect the speed and quality of model training
- On-chain training and storage costs are relatively high, requiring optimization of technology to lower barriers
2. Market risks
- Short-term price surge (cumulative 227% since TGE), RSI reaches 78.36 (overbought), profit-taking pressure is rising
- The AI token market is highly volatile, significantly influenced by the macro environment and industry policies
- Intense competition, facing dual competition from decentralized AI projects like Bittensor, SingularityNET, and giants like OpenAI
3. Business risks
- The commercialization path is unclear, lacking stable income sources, reliant on financing and token appreciation to maintain operations
- The non-profit organization model may limit resource acquisition and market expansion speed
- High regulatory uncertainty, significant AGI field policy risks, which may affect the project's compliance
6. Fundamental scoring and investment outlook
Comprehensive score: 7.8/10
- Advantages: Top-tier financing + innovative technology + healthy token economy + strong community; the integration of AI and Web3 shows great prospects, and the collaboration with Franklin Templeton opens up the institutional market
- Disadvantages: Early stage + unclear commercialization + short-term overbought, time needed to verify technological implementation and ecosystem expansion capability
Medium to long-term outlook
- If the technological implementation goes smoothly, the ROMA framework and OML model are expected to become the standard for decentralized AGI, driving continuous growth in SENT value
- Applications in the financial sector (in collaboration with Franklin Templeton) may become the first commercialization breakthrough, validating the model's practicality and profitability
- As the AI sector continues to heat up, the recognition of the OpenAGI concept is increasing, and the project is expected to attract more developers and users, forming a positive cycle
7. Core conclusions and recommendations
Core judgment
SENT has a solid fundamental basis, backed by top-tier capital, innovative technical architecture, and a healthy token economy. Long-term value depends on the progress of technological implementation and ecosystem expansion. In the short term, due to Upbit's listing and the hype around AI, the price has surged dramatically, showing clear overbought signals and increasing adjustment 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 recommendations
1. Short-term (1-4 weeks): Mainly observe, wait for a pullback to the $0.030-$0.032 range before considering entry, set stop loss at $0.028
2. Medium-term (1-3 months): Focus on technological progress (ROMA framework optimization, model training results) and the situation of commercial cooperation, building positions in batches
3. Long-term (6 months+): If the project achieves key technological breakthroughs and ecosystem expansion, target price $0.05-$0.06, corresponding to TGE price 4-5 times
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