News Report Technology
July 08, 2025

Pundi AI Unveils Data Pump To Enable Fair Monetization And Practical Application Of AI Datasets

In Brief

Pundi AI’s new Data Pump feature enables dataset owners to tokenize and fairly monetize AI datasets as tradable on-chain assets, supported by integrated AI tools for transparency and community-driven funding mechanisms.

Pundi AI Unveils Data Pump To Enable Fair Monetization And Practical Application Of AI Datasets

AI data platform, Pundi AI introduced a new feature called Data Pump, aimed at facilitating equitable monetization and practical utility of AI datasets. The feature leverages a concept familiar in the Web3 ecosystem by converting datasets into liquid, tradable on-chain assets governed by community ownership principles.

Data Pump allows individuals or organizations holding dataset copyright NFTs to mint ERC-20 tokens that represent access to their data. These tokens can undergo a community funding phase and subsequently be traded on decentralized exchanges such as PancakeSwap. It is also possible for multiple users to generate separate tokens from the same dataset, reflecting shared ownership rights.

The platform incorporates a structured launch framework that permits dataset holders to establish funding targets, distribute tokens, and involve early contributors. This mirrors the mechanics of fair launches seen in platforms like Virtuals, but applies them specifically to datasets utilized in AI development. Creators may also impose participation conditions, such as requiring contributors to maintain a certain balance of Pundi AI Points before joining a campaign.

Each dataset comes with an integrated AI Agent designed to allow users to query, summarize, and evaluate the dataset’s quality and relevance. Unlike task-executing agents, this system focuses on delivering transparent insights into data utility.

The platform employs a bonding curve model to determine token pricing dynamically throughout crowdfunding and launch. This model is implemented entirely on-chain via automated algorithms, removing the need for manual pricing decisions and providing continuous liquidity alongside real-time price adjustment.

In order to address risks such as Miner Extractable Value (MEV) exploitation and unauthorized liquidity pool creation, Data Pump utilizes separate smart contracts for the crowdfunding and post-launch phases. These safeguards are deployed across blockchain networks like BNB Smart Chain (BSC) to maintain security and protect liquidity contributions.

The feature is designed for accessibility, enabling dataset owners to engage with the system without requiring advanced programming skills or technical infrastructure management. The entire process is handled by Data Pump, allowing contributors to focus on enhancing the quality and value of their data assets.

Understanding Data Pump: Key Features And Functionality

Within the Data Pump framework, contributors and communities are provided with mechanisms to determine how their datasets are monetized, enabling ongoing revenue generation beyond traditional one-time licensing models. The system also supports transparency and validation through an embedded AI Agent, which allows real-time querying and assessment of dataset quality.

For developers and AI practitioners, the platform offers access to datasets that are both verifiable and tied to clear ownership credentials. The inclusion of integrated AI Agents enables users to evaluate and extract relevant insights from the data prior to acquisition, which can contribute to the development of AI models with improved accuracy and reduced instances of hallucination.

The process for utilizing Data Pump involves connecting a supported wallet and confirming ownership of a dataset non-fungible token (NFT). Users can then generate an ERC-20 token, configure crowdfunding parameters, and make the asset available for community engagement. Upon successful completion of the funding phase, the token becomes tradable on decentralized exchanges such as PancakeSwap, where pricing is managed through an on-chain bonding curve. At this stage, the associated AI Agent is activated, transforming the dataset into an interactive, on-chain resource with ongoing utility.

Disclaimer

In line with the Trust Project guidelines, please note that the information provided on this page is not intended to be and should not be interpreted as legal, tax, investment, financial, or any other form of advice. It is important to only invest what you can afford to lose and to seek independent financial advice if you have any doubts. For further information, we suggest referring to the terms and conditions as well as the help and support pages provided by the issuer or advertiser. MetaversePost is committed to accurate, unbiased reporting, but market conditions are subject to change without notice.

About The Author

Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.

More articles
Alisa Davidson
Alisa Davidson

Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.

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