Islamic Finance Principles Assessment
Riba — Does OMEGA Labs involve interest?
OMEGA Labs shows no evidence of interest-bearing mechanisms in its revenue model or token design. Rewards flow from Bittensor network emissions tied to data contribution quality, not from lending, borrowing, or fixed-rate yield instruments. For Muslim investors, the riba dimension of this project is not a significant concern based on available sources.
Assessment: Moderate Riba
Score: 66.5/100
Our methodology examines 10 criteria to evaluate how well OMEGA Labs avoids interest-based mechanisms.
OMEGA Labs' income stream is emission-based, distributed through the Bittensor protocol to miners and validators contributing multimodal data or verifying task completion via the OMEGA Focus app. No sources describe treasury holdings placed in interest-bearing instruments, nor any fixed guaranteed return structure. Rewards are variable and tied to data/task quality and network emission schedules, not to a lending spread or interest rate. This emissions-based model resembles a productivity/incentive marketplace rather than a riba-generating financial product, though treasury composition itself is not fully disclosed in these sources.
The core business model is a decentralized AI data marketplace layered on Bittensor's subnet architecture, not a lending or borrowing platform. No interest-bearing partnerships, credit facilities, or debt instruments are described anywhere in the available documentation. The protocol's economic logic centers on compensating miners for verified data and validators for assessment work, functioning closer to a piece-rate labor market than a financial intermediary. Absent any lending or interest-based partnership disclosed in these sources, the business model itself does not raise riba concerns for Muslim investors evaluating this project.
Gharar — How much uncertainty does OMEGA Labs involve?
OMEGA Labs carries moderate uncertainty: the team and product are real and traceable, but audit status and full tokenomics remain unverified. Transparency around the codebase reduces gharar, while the absence of a located security audit and incomplete allocation disclosure increases it. On balance, informational uncertainty here is real but not extreme, and investors should treat it as a documented gap rather than a fatal flaw.
Assessment: Moderate Gharar (Material Uncertainty)
Score: 53.3/100
Our methodology examines 15 criteria including team transparency, audit quality, and governance.
The founding team is named and independently verifiable: Parshant Utam (also founder of WOMBO.ai) and Salman Shahid (CTO), both listing OMEGA Labs on public LinkedIn profiles since January 2024, based in Toronto. The project has shipped real products (OMEGA Focus, Ω Muse) and completed an acquisition (Drippi), and maintains an open-source GitHub repository detailing miner/validator architecture. This level of named, traceable leadership and public code materially reduces gharar compared to anonymous-team projects, though governance remains founder-directed with no described token-holder voting mechanism.
No security audit of OMEGA Labs' own smart contracts or subnet code could be located in these sources; audit results retrieved during research pertained to unrelated protocols entirely (Zircuit, MonoX, Solana programs), not OMEGA Labs. This absence of a named, verifiable audit firm for SN24 itself is a genuine gharar concern and should be stated plainly as such. Additionally, a tokenomics/vesting tracker shows only a partial burn metric (~10.09%) with the underlying allocation table incomplete, leaving pre-mine size, vesting schedule, and launch fairness unconfirmed.
Maysir — Does OMEGA Labs involve gambling or speculation?
OMEGA Labs is not designed as a pure speculation vehicle; it is built around a functioning AI data marketplace with a stated productivity mechanism. However, market data showing a market cap of roughly $2.32M against a fully diluted valuation near $14.21M points to significant secondary-market speculative pressure. The underlying protocol utility does not, by itself, eliminate maysir-like trading risk in the open market.
Assessment: Moderate Maysir (High Risk)
Score: 58.5/100
Our methodology examines 11 criteria to determine whether OMEGA Labs is a gambling instrument or a genuine economic tool.
Although categorized here alongside meme coins, OMEGA Labs' own design is not built solely for speculative trading — it operates a documented "Proof of Productivity" model where token rewards correspond to verified data contribution or task completion via the OMEGA Focus app. This distinguishes it from tokens with no stated function beyond price speculation. That said, the wide gap between its reported market cap and fully diluted valuation, combined with thin emission share (0.17% of network), signals that much of its current trading activity may still be driven by speculative positioning rather than proportional utility consumption.
Weighing the two sides: genuine utility exists in the form of an open-source AI dataset marketplace, real shipped products, and a named, accountable team, which meaningfully separates OMEGA Labs from a pure gambling instrument. Against this, low market capitalization relative to fully diluted valuation, unverified audit status, and incomplete tokenomics disclosure create conditions where secondary-market speculation can dominate over productive use. For Muslim investors, this suggests caution focused on trading behavior and valuation risk rather than a condemnation of the protocol's underlying design.
The Full 27-Point Screening
1. Legitimacy (4 criteria)
| Criterion | Score | Analysis |
|---|
| Team Transparency | 78/100 | Founders Parshant Utam and Salman Shahid are named, hold public professional profiles, and have verifiable prior track records (e.g., WOMBO.ai) tied directly to OMEGA Labs. |
| Fraud & Scam Risk | 62/100 | No fraud, hack, or rug-pull evidence was found against OMEGA Labs itself in these sources, though this is inferred from absence of adverse reports rather than a positive confirmation; an unrelated entity ("OmegaPro") facing DOJ/SEC fraud charges shares a similar name but no documented connection. |
| Use Case Legitimacy | 78/100 | Sources describe a functioning open-source AI data/AGI marketplace with a live app (OMEGA Focus) and public GitHub repository, indicating genuine utility beyond speculation. |
| Ethical Practices | 85/100 | The protocol's own design is an AI training-data marketplace, a sector with no inherent Shariah prohibition; any downstream misuse of AI models by third parties would not alter this base design assessment. |
Summary: OMEGA Labs has a named, traceable founding team and a public, functioning AI/data project, with no fraud evidence found against it, though it shares a confusingly similar name with an unrelated, DOJ-charged scam entity ("OmegaPro").
2. Project Operations (9 criteria)
| Criterion | Score | Analysis |
|---|
| Core Protocol Business | 82/100 | The base protocol is described consistently as decentralized AI/data infrastructure on Bittensor, not a prohibited sector such as gambling or conventional interest-based finance. |
| Transaction Fees | 55/100 | Sources do not detail how transaction/network fees are burned, retained, or distributed for this specific subnet; a Bittensor emissions-based structure is described generally but fee mechanics are not spelled out. |
| Treasury Assets | 45/100 (low evidence) | No information on treasury composition (e.g., whether it holds interest-bearing instruments) was found in these sources. |
| Revenue Model | 68/100 | The revenue/reward model appears emission- and productivity-based rather than interest-based, inferred from the general description of the marketplace, but no explicit revenue statement is provided. |
| Transparency | 80/100 | The project maintains a public, open-source GitHub repository detailing its architecture and code. |
| Governance | 45/100 | Governance appears concentrated in the identified founding team directing subnet incentive design, typical of Bittensor subnets, but no explicit decentralized governance process for token holders is documented. |
| Launch Fairness | 35/100 (low evidence) | No usable data on launch fairness, insider allocation timing, or pre-mine specifics for this project could be extracted from the sources (the tokenomics/vesting table was incomplete). |
| Token Distribution | 35/100 (low evidence) | The token distribution table referenced could not be read from the retrieved snippet, so allocation breakdown and concentration cannot be established. |
| Speculation/Utility Ratio | 55/100 | Genuine utility use cases (data marketplace, productivity app) exist, but the low ratio of circulating market cap to FDV suggests meaningful future dilution and speculative trading dynamics. |
Summary: The project runs as an open-source Bittensor subnet building an AI training dataset via a productivity-reward app, but fee handling, treasury composition, and full token-distribution details are not established in the available sources.
3. Financial Health (4 criteria)
| Criterion | Score | Analysis |
|---|
| Protocol Revenue | 68/100 | Revenue appears tied to network emissions for productivity/data contribution rather than lending or interest income, inferred from the project description rather than a direct financial statement. |
| Financial Status | 45/100 | Reported market cap ($2.32M) and FDV ($14.21M) figures suggest an early-stage, small-cap project; broader financial stability metrics are not established in these sources. |
| Interest Assessment | 78/100 | The base protocol is described as a data/AI marketplace with no lending, borrowing, or interest mechanism mentioned; this is inferred from the absence of any such feature in the project description. |
| Audit Quality | 15/100 (low evidence) | No security audit of OMEGA Labs' code or subnet contracts could be found in these sources; all audit-related sources retrieved pertain to unrelated projects. |
Summary: The project shows small-cap, early-stage market metrics and an emissions-based (non-lending) revenue model, but no audit of its own code could be located in these sources.
4. Token Economics (5 criteria)
| Criterion | Score | Analysis |
|---|
| Token Purpose | 78/100 | The token operates as a utility/incentive asset for a described AI data marketplace, not as a purely speculative meme asset. |
| Governance Rights | 30/100 (low evidence) | No description of on-chain governance voting rights for token holders was found in these sources. |
| Rewards Distribution | 78/100 | Rewards are explicitly described as variable, tied to data/task quality and a "winner-takes-all plus distributed" emission structure rather than a fixed payout. |
| Speculation Controls | 48/100 | A burn mechanism (~10%) is referenced on a tokenomics tracker, but its design and effectiveness as an anti-speculation control are not explained in the sources. |
| Asset Backing | 58/100 | The token's value is tied to platform utility (AI data/task marketplace access) rather than any interest-bearing instrument, though this is inferred rather than explicitly stated as "backing." |
Summary: The token serves a genuine utility/incentive function tied to data contribution and task completion with variable rewards, though governance rights and anti-speculation mechanics are only partially documented.
5. Staking Mechanism
OMEGA Labs has no native staking mechanism, so these five criteria are not applicable and are excluded from the score entirely rather than counted as zeros.
Overall Assessment: OMEGA Labs presents as a genuine, team-identified AI infrastructure project with real utility rather than a meme coin, but several transparency gaps — audit status, governance rights, treasury detail, and full token distribution — remain unresolved from the available sources.
Scoring note: Meme coin: maysir-capped (C13=55); score already below the cap.
Written by ThanvirFounder, Ex Director S&P Global Energy
Reviewed by Imam Omar SiddiqiShariah Scholar