Dataset Valuation

Inflectiv introduces a dynamic dataset valuation framework, ensuring datasets retain long-term financial value.

• Scarcity & uniqueness – AI models prefer exclusive datasets, leading to higher pricing for rare, high-quality datasets.

• Continuous monetization – Datasets can be licensed and resold multiple times, ensuring long-term earnings for contributors.

• Trust index scoring – AI algorithms score datasets based on integrity, compliance, and usability, influencing their market demand.

• Dataset utility in AI model training – High-utility datasets are more valuable, especially those optimized for NLP, computer vision, and predictive AI.

Dataset tokens & liquidity pools

Tokenized AI datasets operate within a DeFi-enabled liquidity framework, ensuring immediate tradeability, staking rewards, and a deflationary model for utility tokens.

Impact: As more datasets enter the marketplace, more utility tokens are locked or burned, increasing scarcity and long-term value appreciation. Token pairing: ensuring AI data liquidity

Every dataset token is paired with utility tokens in a liquidity pool, ensuring:

• Instant tradeability for dataset tokens.

• Dynamic pricing based on supply & demand.

• Scarcity-driven value appreciation for utility tokens.

Liquidity incentives

• Contributors earn passive income from trading fees & licensing revenues.

• Validators receive rewards for ensuring data compliance and quality.

• Dataset token stakers earn yield rewards, incentivizing long-term liquidity provisioning.

Deflationary mechanics

• Liquidity pool locks – utility tokens tokens used for dataset tokenization are locked permanently, reducing circulating supply.

• Premium feature fees burned – AI dataset compression, validation, and preprocessing services burn utility tokens, creating deflationary pressure.

• Dataset yield pools – Staking dataset tokens generates passive income, further reducing $IAI liquidity from open circulation.