Story Protocol Rebrands as DATA Foundation to Power AI Training Infrastructure

Palo Alto-based blockchain startup Story Protocol has officially rebranded as DATA Foundation, marking a major strategic shift toward developing infrastructure for artificial intelligence (AI) training data. The company is moving away from its broader intellectual property focus to concentrate on creating transparent, blockchain-powered solutions for AI datasets.

As part of the transition, Kled founder Avi Patel has joined the organization as an advisor and Chief Data Officer. Patel confirmed the company's new direction, explaining that the DATA Foundation will oversee the DATA Network, an on-chain registry designed to verify the origin, licensing status, and user consent history of datasets used to train AI models.

The move comes at a time when AI developers and major technology companies are facing increasing legal challenges over copyright infringement and concerns surrounding the use of unauthorized training data. By leveraging blockchain technology, the DATA Network aims to provide an immutable record of data ownership, licensing agreements, and provenance, helping AI companies demonstrate compliance and transparency.

The rebranding follows Story Protocol's impressive $140 million in venture funding, led by Andreessen Horowitz's a16z crypto. Although Patel confirmed the funding amount, he declined to comment on reports valuing the company at $2.4 billion.

Story Protocol previously attracted attention after delaying a token unlock earlier this year, with co-founder Sy Leestating the blockchain required additional time to increase adoption before releasing tokens.

A key feature of the launch is the integration with Kled AI, an opt-in human data marketplace that has already registered approximately 1.5 billion user-contributed records on the DATA Network. Leadership has also changed, with Andrea Muttoni assuming the role of CEO of the DATA Foundation.

To address growing concerns about AI data transparency, the foundation is introducing Trace, a public audit platform that generates tamper-proof cryptographic receipts for every data contribution. These records include content hashes, licensing information, consent terms, timestamps, and proof of payment without exposing the underlying datasets. According to Patel, the actual data remains securely stored within licensed marketplaces, ensuring privacy while enabling verifiable compliance.

The platform also incorporates Poseidon, an AI data processing system that evaluates and improves the quality of human-generated datasets. Its contributor application, Numo, rewards participants with stablecoin or fiat payments for submitting authenticated data. Rather than paying contributors in advance, compensation is directly linked to completed marketplace transactions.

Looking ahead, the DATA Foundation is prioritizing the development of an advanced fraud detection protocol capable of verifying that submitted datasets are authentic, human-created, and original rather than AI-generated or illegally copied. Patel emphasized that trustworthy, verifiable data will be essential for the future of AI, noting that developers are increasingly unwilling to license datasets that cannot be independently validated.