Islamic Finance Principles Assessment
Riba — Does AI Network involve interest?
AI Network's base protocol shows no evidence of interest-based revenue; income derives from AIN paid or reserved for accessing compute and AI services. The main riba-adjacent question concerns staking rewards, where a quoted "~8%" figure sits alongside language framing returns as variable. On balance, the reward structure appears closer to performance-linked network income than to guaranteed interest, but the ambiguity warrants light purification rather than a clean pass.
Assessment: Minor Riba
Score: 85/100
Our methodology examines 10 criteria to evaluate how well AI Network avoids interest-based mechanisms.
AIN's protocol revenue model is utility-based: resource providers earn AIN for supplying GPU capacity, and developers pay or reserve AIN to access AI services on the network. There is no evidence in available sources of the protocol holding interest-bearing instruments, lending out treasury funds at fixed rates, or generating yield from conventional debt markets. Treasury-funded reward pools exist for NFT/AINFT ecosystem incentives, but these appear to be distributions of protocol-native tokens rather than interest income. No riba-based revenue stream at the base-protocol level was identified in the research.
Validator staking documentation cites an "Annual reward rate: ~8% + transaction fees (varies)," which reads as a target rather than a contractually guaranteed fixed return, since it explicitly varies with transaction activity. The newer AIN Staking program, using the liquid staking token sAIN, describes a "projected APY... tied to protocol activity" and "dynamically tracked based on network participation," reinforcing a performance-linked structure. Rewards derive from network fees and staking-app activity rather than from lending AIN at interest. The mixed fixed/variable framing introduces some ambiguity, but the underlying mechanism resembles profit-sharing from network operation more than riba.
Gharar — How much uncertainty does AI Network involve?
AI Network carries moderate uncertainty: the team and codebase are publicly identifiable and open-source, which reduces informational gharar, but the absence of any named third-party audit and some centralization in validator control increase it. Documentation on staking mechanics, unbonding periods, and slashing risk is reasonably detailed. On balance, the uncertainty here is real but bounded, warranting caution rather than outright avoidance.
Assessment: Moderate Gharar (Material Uncertainty)
Score: 58.3/100
Our methodology examines 15 criteria including team transparency, audit quality, and governance.
The project is not anonymous: sources name co-founders Jeongkyu Shin and Minhyun Kim, alongside board contributors Esha Bhandari, Natasha Crampton, and Nick Lippis, and the team has maintained a public presence since 2019. The ain-blockchain codebase is open-source on GitHub, and documentation covers SDKs, validators, and staking mechanics. This level of disclosure is stronger than many anonymous or pseudonymous projects, though detailed founder credentials and track record remain thin in the retrieved material, leaving some residual uncertainty about the team's history.
No named third-party security audit firm or dated audit report for AI Network could be located in the research; CertiK's own Skynet scan states directly, "No 3rd Party Audit." This is a plain audit gap and a legitimate gharar concern that should not be minimized. CertiK's community-trust score of 75.50 and "relatively good" governance rating offer some reassurance, but a moderate automated-scan score is not a substitute for an independent code audit. Staking terms, unbonding periods (7 days), and slashing risks are otherwise clearly documented.
Maysir — Does AI Network involve gambling or speculation?
AI Network is not designed as a speculative or gambling instrument; it is infrastructure for a decentralized AI-compute marketplace with a fixed 700M supply cap. Some speculative trading naturally occurs on secondary markets, as with virtually any listed token, but this behavior sits outside the protocol's own design. The project's core function is productive rather than chance-based.
Assessment: Minor Maysir (Incidental)
Score: 70/100
Our methodology examines 11 criteria to determine whether AI Network is a gambling instrument or a genuine economic tool.
AI Network's utility is concrete: resource providers supply GPU compute and earn AIN, developers pay AIN to deploy AI services, and the token is reserved or deposited to guarantee service contracts. This creates a functional exchange of value tied to real computational work, not a wager on an uncertain binary outcome. Staking further ties rewards to network participation and security provision rather than chance. This productive, service-backed design distinguishes AIN from instruments whose primary function is speculative betting.
Historical trading data shows periods of thin liquidity, with one snapshot recording roughly $10,000 in 24-hour volume, indicating that at times the market has been driven more by speculative positioning than deep organic usage. This is a common feature of many mid-cap Layer-1 tokens and reflects third-party market behavior rather than a flaw in AIN's own design. Genuine compute-marketplace adoption, staking participation, and an active codebase support the case for real utility, even as investors should recognize that secondary-market price action can be speculative and volatile.
The Full 27-Point Screening
1. Legitimacy (4 criteria)
| Criterion | Score | Analysis |
|---|
| Team Transparency | 55/100 | Co-founders and several board members are named in one source, but bios, credentials and verifiable track record are thin. |
| Fraud & Scam Risk | 60/100 | No fraud/rug-pull evidence tied specifically to AI Network was found; unrelated enforcement actions against similarly-named "AI" schemes were discarded as not applicable, so absence of red flags is weak, not confirmed, evidence. |
| Use Case Legitimacy | 75/100 | Whitepaper, GitHub, and exchange descriptions consistently describe a functioning decentralized compute/AI marketplace rather than pure hype. |
| Ethical Practices | 90/100 | The protocol's own design (decentralized cloud/AI compute) is not in a prohibited sector. |
Summary: AI Network has a partially named team and a real, multi-year infrastructure product, with no fraud evidence found in sources specific to this project, though credential depth and audit history are thin.
2. Project Operations (9 criteria)
| Criterion | Score | Analysis |
|---|
| Core Protocol Business | 90/100 | Core business is GPU/compute resource marketplace for AI, not gambling, interest-lending, or other prohibited activity. |
| Transaction Fees | 50/100 | Validators earn transaction fees alongside a stated reward rate, but no burn or clear anti-extraction fee design for the base protocol is documented. |
| Treasury Assets | 45/100 (low evidence) | A DAO treasury is mentioned for reward pools, but its composition (e.g., whether it holds interest-bearing instruments) is not disclosed in these sources. |
| Revenue Model | 65/100 | Revenue comes from compute-access fees rather than interest, but the full revenue model is not fully detailed. |
| Transparency | 80/100 | Codebase is open-source on GitHub and documentation/whitepaper are publicly available. |
| Governance | 45/100 | A DAO governance structure is described, but a third-party scan flags single-owner/creator address control and only moderate governance strength. |
| Launch Fairness | 40/100 (low evidence) | Launch fairness details (pre-mine, initial sale structure) specific to AI Network could not be established from these sources. |
| Token Distribution | 40/100 (low evidence) | Total supply (700M) is known, but the breakdown of initial distribution among team, investors, and public is not documented in reliable AI Network-specific sources. |
| Speculation/Utility Ratio | 70/100 | The token has clear stated uses (compute access, staking, governance) beyond speculation. |
Summary: The protocol is an open-source, DAO-governed decentralized AI-compute marketplace on its own PoS blockchain bridged to Ethereum, but centralization flags and undisclosed launch/distribution details limit full transparency.
3. Financial Health (4 criteria)
| Criterion | Score | Analysis |
|---|
| Protocol Revenue | 65/100 | Revenue described as compute-access fees, with no indication of interest-based income, but detail is limited. |
| Financial Status | 55/100 | AIN has multi-year exchange listings but at least one data point shows very thin trading volume, indicating limited market depth. |
| Interest Assessment | 80/100 | No lending/borrowing feature is described as native to the AI Network base protocol in these sources. |
| Audit Quality | 15/100 | A dedicated security-scan source explicitly states no third-party audit exists for AI Network. |
Summary: Revenue comes from compute-access fees and staking rather than interest-based lending, but the project lacks any documented third-party security audit and has shown periods of thin trading liquidity.
4. Token Economics (5 criteria)
| Criterion | Score | Analysis |
|---|
| Token Purpose | 75/100 | AIN functions as a utility token for compute access, staking and governance rather than as a speculative meme token. |
| Governance Rights | 60/100 | DAO and staking-linked governance influence over AI Agents is described, though the depth of holder control is unclear. |
| Rewards Distribution | 70/100 | Staking rewards are described as tied to protocol activity/participation rather than a purely fixed guarantee. |
| Speculation Controls | 40/100 (low evidence) | No specific anti-speculation mechanisms (burns, holding limits, etc.) for AI Network are documented in these sources. |
| Asset Backing | 65/100 | Token value is tied to network utility and a fixed supply cap rather than to interest-bearing reserves, but detail is limited. |
Summary: AIN is a utility token for compute access, staking and governance with a fixed supply cap, though anti-speculation design and detailed distribution mechanics are not documented.
5. Staking Mechanism (5 criteria)
| Criterion | Score | Analysis |
|---|
| Mechanism Type | 70/100 | Native staking is documented with unbonding periods, node requirements, and a liquid staking token (sAIN); appears non-custodial via self-run/delegated validators, though beta whitelisting introduces some centralization. |
| Islamic Contract Classification | 40/100 | Validator documentation quotes a stated "~8%" annual reward rate alongside variable framing elsewhere, leaving the underlying contract structure (fixed-return vs. genuine profit/activity-sharing) unresolved. |
| Rewards Structure | 55/100 | Sources present staking rewards as both a quoted base rate and as activity-dependent/variable, so the reward mechanism is not cleanly one or the other. |
| Documentation | 75/100 | Staking documentation covers unbonding periods, slashing risk, hardware requirements and reward sourcing in reasonable detail. |
| Shariah Alignment | 45/100 | The mixed fixed/variable reward framing leaves a core classification question about the staking contract unresolved. |
Summary: A native staking mechanism exists with documented unbonding, slashing and a newer liquid-staking option, but its reward structure mixes fixed-rate and activity-based framing, leaving the Islamic contract classification unresolved.
Overall Assessment: AI Network appears to be a genuine, if only partially transparent and unaudited, AI-compute infrastructure project whose staking design carries an unresolved fixed-vs-variable reward question that should be clarified before a definitive Shariah ruling.
Written by ThanvirFounder, Ex Director S&P Global Energy
Reviewed by Imam Omar SiddiqiShariah Scholar