Ethereum targets AI privacy with zkAPI for anonymous API payments

The Ethereum Foundation (EF) has stepped in with a crypto-native solution; their new zkAPI system allows users to settle transactions for AI models and metered APIs under a complete veil of anonymity.

Historically, users were forced to associate their credit card or API keys with every request—a system that has been criticized as vulnerable because it exposed prompt history to infrastructure providers.

However, according to the Ethereum Foundation, that problem is now resolved in the new architecture because the spending authorization is made locally using cryptographic notes. It co-developed the technology alongside the Open Anonymity (OA) Project.

zkAPI technology will separate payments from user identity

In a blog post released Thursday, the Ethereum Foundation acknowledged the deep-seated privacy flaws built into modern tech architecture. Under the current landscape, “your API key points to an account, the account to a payment method, and every prompt you send joins the record attached to both,” it noted.

Nonetheless, it further claimed that, with the help of zkAPI technology, payment is completely decoupled from identity. This process starts with a single standardized transaction in which a user deposits funds as a credit deposit, such as ETH or USDC, into the vault contract on Ethereum. It becomes purely digital money, fully spendable by the user, yet not traceable to their identity or any previous depositing activity.

The authorization process is also conducted entirely on the client side. A zero-knowledge proof is created locally, which proves that the transaction falls under the private note without disclosing the state. More importantly, a single ZK proof can verify both a single transaction and an entire session, according to the EF.

Furthermore, the architecture employs a distinctive serial number, known as a nullifier, to secure the spending process. In the event of any double-spending attempts, the system will simply spot a duplicate nullifier without disclosing any user information.

Moreover, the default APIs from OpenAI and Ollama are also available locally, enabling existing AI applications, editors, and chat clients to access them via localhost.

Speaking on the new system, Ken Liu, a Stanford computer science PhD candidate who works on the Open Anonymity Project, claimed, “It’s like a generalization of OA unlinkable inference that also abstracts payments away.”

zkAPI could reshape privacy for AI services

The development could become particularly relevant as AI applications increasingly rely on paid inference and metered services. Instead of requiring users to maintain accounts with individual AI providers, zkAPI creates a payment layer that can potentially allow applications to pay for usage without exposing the identity behind each request.

This distinction is important because AI interactions can contain highly sensitive information. Prompts may reveal personal details, business strategies, proprietary code, financial information, or other private data.

If API usage can be linked to a persistent account or payment method, infrastructure providers may be able to build detailed records around that activity.

The Ethereum Foundation’s approach attempts to remove that link by making the payment credential independent from the user’s identity. Users can fund a private balance and authorize spending without repeatedly presenting conventional account credentials to the service provider.

The architecture could also make privacy-preserving payments easier to integrate into existing applications. Because zkAPI exposes standard interfaces for services such as OpenAI and Ollama through localhost, developers would not necessarily need to redesign their AI applications from scratch. Instead, the privacy layer can sit between the application and the underlying API service.

However, the technology is still an emerging approach, meaning its broader adoption will depend on developer integration, user demand, infrastructure support, and the system’s performance as transaction volumes increase.

Ethereum is targeting developments in network scale and user experience

The Ethereum Foundation previously announced its 2026 protocol priorities. The engineering roadmap positions the ecosystem’s immediate development on a three-fold approach: network scaling, user experience improvements, and Layer-1 fortifications.

Looking back at all this, Ethereum’s developers have already begun implementing quantum-proof cryptographic algorithms in both the execution and consensus layers, thus laying the foundation for complete quantum resistance by 2029. Besides, the gas limit targeted by the network in 2026 stands at more than 100 million.

In November, Ethereum educator Anthony Sassano reported that hitting 180 million is the year’s ideal goal, though not the very best outcome they could get. In 2025, the Ethereum gas limit was increased to 60 million thanks to the Pectra and Fusaka upgrades.

The month of October is also set to see the implementation of Glamsterdam on the Ethereum blockchain, which is seen as one of the biggest milestones for the network since the Merge in 2022. The upgrade will be implemented in a dual-layer manner, consisting of the “Amsterdam” update for the execution layer and the “Gloas” update for the consensus layer.

In terms of execution, Amsterdam will introduce Parallel Processing, which, as the name suggests, changes the execution layer to perform transactions in parallel rather than sequentially, like going through a single-lane checkout counter at a supermarket.

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