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Santa Clara, California, February 27th, 2025, Chainwire

CARV, the leading AI chain ecosystem for data sovereignty, is making a major leap forward in the decentralized AI movement. Today, they are open-sourcing the D.A.T.A. (Data Authentication, Trust, and Attestation) Framework is designed to provide AI agents verifiable access to on-chain and off-chain data.

The D.A.T.A. Framework is now fully available on GitHub: GitHub Repository

This move marks a significant milestone in CARV’s mission to democratize AI data access, enabling developers worldwide to build, refine, and scale AI agents with trustless, structured, and privacy-preserving data.

The Value of Open Source in AI Development

By open-sourcing D.A.T.A. Framework, CARV is empowering developers to build AI agents that don’t just react—they reason, adapt, and optimize interactions in real-time using on-chain and off-chain data. This marks the first open-source AI agent framework that:

• Brings DeepSeek’s Chain-of-Thought Processing into Web3 – allowing AI agents to perform multi-step logical reasoning before taking actions.
• Enables multi-stage verification of AI decisions – ensuring that AI agents validate their own conclusions before executing transactions.
• Empowers AI agents with economic self awareness – AI agents can now own wallets, execute trades, and participate in tokenized ecosystems autonomously.
• Fosters decentralized knowledge networks – AI agents share insights and learn collectively instead of working in silos.

This is more than a data framework; it serves as the foundation for decentralized intelligence, enabling AI agents to interact, transact, and evolve within an open ecosystem.

Key Features of the Open-Source D.A.T.A. Framework

Capabilities for AI Developers:

• Real-Time On-Chain & Off-Chain Data Access: AI agents can fetch and process wallet transactions, smart contract activities, and even off-chain behavioral insights in real time.
• Cross-Chain Verification & Identity Mapping: With CARV ID, AI agents can categorize users, verify token holdings, and personalize interactions based on decentralized credentials.
• Economic Self-Awareness & Monetization: D.A.T.A. enables AI agents to manage wallets, distribute tokens, and optimize their decision-making based on token-driven intelligence.
• Privacy-Preserving AI Computation with TEE: Ensures secure, verifiable, and private AI execution while preventing unauthorized access to sensitive data.

By making D.A.T.A. 2.0 open-source, CARV is inviting developers, researchers, and enterprises to contribute to the evolution of AI reasoning in Web3, leverage token-driven intelligence to create AI-driven economies and push the boundaries of privacy-preserving AI execution 

This open-source release is not just a step toward decentralization—it’s a call to action for the AI, Web3, and data sovereignty communities to build the next-gen AI models that can think, reason, and interact with digital economies in a truly decentralized way.

Starting Building with D.A.T.A. Framework: GitHub Repo

Users can join the Developer Community: https://discord.com/invite/GdrdpvzHxB 

About CARV

CARV is building an AI chain ecosystem to enable data sovereignty at scale. By empowering AI agents with secure, unified infrastructure, CARV enables intelligent, collaborative operations through its SVM Chain, offering trustless consensus, cryptographic proofs, and verifiable execution. With the D.A.T.A Framework, CARV enriches AI with high-quality, on-chain and off-chain data, allowing agents to learn, evolve, and collaborate dynamically. With over 15M users and 8M CARV IDs, CARV ensures privacy and data control while providing AI agents with powerful, cross-chain insights, creating a secure, innovative ecosystem for both AI and human collaboration.

Supported by $50M in funding from top-tier investors like Tribe Capital, HashKey Capital, and Animoca Brands, and backed by a team of veterans from Coinbase, Google, and Binance, CARV is committed to fostering a decentralized future where data is a valuable, user-owned asset.

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