Artificial Intelligence Demands Feeding, Web3 Data is Chaotic! The Imperative Importance of an AI-Compatible Data Infrastructure

In the rapidly evolving world of AI and Web3, the importance of a robust, AI-ready data layer has become increasingly apparent. Architecture, it seems, is destiny in these multi-chain, real-time, adversarial markets. Teams that stand up such a data layer will have a significant advantage, as they can enable autonomous market-making, governance copilots, cross-chain portfolio policies, data markets for models, and safety layers.

The decentralized finance (DeFi) sector is moving towards intent-based designs, with Uniswap Labs and Across proposing ERC-7683 as a shared rail for this pattern. This shift towards intent-based designs is a step towards creating a more efficient and user-friendly DeFi landscape.

However, the road to success is not without its pitfalls. Several AI×Web3 products have faced challenges, with some closing, being shelved, or effectively ceasing operation. Examples include Planet Mojo's "WWA" platform, Brian (AI → onchain transaction builder), TradeAI / Stakx, and BitAI.

The need for an AI-ready data layer that is programmable, verifiable, real-time, and cross-chain is clear. Such a layer should include features like ingestion and normalization, streaming and snapshots, mirrors with provenance, on-stream compute, finality-aware freshness API, intent hooks, safety and audit, and more.

The fusion of AI and crypto is seen as complementary, with AI bringing generative capability and autonomy, and crypto bringing ownership, provenance, and open markets for compute and data. However, analysts expect a high cancellation rate for "agentic AI" projects over the next couple of years due to costs, unclear value, and risk controls.

AI agents in Web3 are often faced with a chaotic data pantry, a challenge that is further compounded by the unique RPC behavior, logs, event schemas, reorg patterns, and finality assumptions of each chain. This necessitates the development of bespoke indexers for each chain.

Regulators and watchdogs flag "AI trading" claims as high-risk, underscoring the need for careful oversight and compliance in this space. Vitalik Buterin, co-founder of Ethereum, emphasizes the importance of careful incentive design and the significance of data quality and safety in the crypto×AI landscape.

Nasim Akthar, CTO at Igris.bot, and Dhawal Shah, Founder and CEO at HeyElsa, are among those working on solutions to these challenges. Akthar emphasizes the need for a neutral layer that normalizes and verifies data in real-time for AI agents in Web3, while Shah is building an agentic layer with cross-chain liquidity, data endpoints, and real-time RAG to turn fragmented chaos into reliable autonomous execution.

Worldcoin, a notable player in the crypto space, faced regulatory compliance issues in Indonesia, with their operations temporarily suspended in May 2025. This serves as a reminder that even in the decentralized world of Web3, regulatory compliance is crucial.

In conclusion, the intersection of AI and Web3 presents a complex landscape with numerous challenges, but also immense opportunities. As we navigate this frontier, it is crucial to prioritize accuracy, relevance, and impartiality, focusing on the development of robust, AI-ready data layers, and ensuring compliance with regulations.

Artificial Intelligence Demands Feeding, Web3 Data is Chaotic! The Imperative Importance of an AI-Compatible Data Infrastructure