Verifiable AI agents: bridging trust and efficiency in decentralized systems

AI agents are transforming industries, automating tasks, and driving efficiency like never before. But as their influence grows, so does a critical question: how can we trust their actions? For X/Twitter AI agents, this challenge is especially pressing. Verifying that a tweet was created by AI—not a human—is essential for trustless systems, reward mechanisms, and ensuring authenticity in decentralized ecosystems.

In this post, we’ll explore how zkServerless addresses the problem of verifiable AI agents, enabling trustless, scalable, and efficient verification for the next generation of Web3 applications.

Why we need verification of AI agents' actions

Verification is the backbone of trustless systems. Without it, we can’t ensure that AI agents are acting as intended—or that their outputs are authentic. This is especially critical for reward mechanisms, where trustless verification ensures fairness and transparency.

Two key verification challenges are:

Verify the inference: ensuring the AI model (its exact untampered version) created the content, not a human.
Verify the tweet’s existence: confirming the content was actually published on X/Twitter.

These challenges are further complicated by the different types of observers:

On-chain: cheap, trustless verification with ZK proofs, ideal for decentralized applications.
Off-chain: fast verification without ZK proofs, perfect for real-time use cases.
Manual: in this case there's no need for tweet existence proof, but it still requires trustless verification of actions.

What zkServerless can offer

We’re building zkServerless, a protocol that combines zkTLS and TEEs under the hood. Here’s what it brings to AI agents:

Scalability & flexibility: supporting multiple observer types and use cases, from on-chain DeFi protocols to off-chain real-time applications. Whether you’re building on Ethereum, Solana, or beyond, zkServerless adapts to your needs.
Fast off-chain verification: enabling real-time use cases without compromising security. Perfect for applications where speed is critical, like real-time data feeds or AI-generated content.
Trustless verification: ensuring AI actions are authentic, reducing human error, and lowering operational costs.

But how exactly does that work?

Start with off-chain verification

Fast TEE-based off-chain verification for real-time use cases. Even with no ZK proofs this option enables trustless, off-chain verification in milliseconds, secure and reliable.
zkTLS for trustless data fetching: AI agent can request real-time data (e.g., token prices) through the zkTLS adapter and do it trustlessly, ensuring the data is verified and tamper-proof before it’s used in prompts or actions.
Running custom models in verifiable TEE enclaves ensures the AI model’s inference is both authentic and verifiable, adding an extra layer of trust to the process. The results like proofs of inference can be published on-chain for trustless verification.

Bringing it on-chain

On-chain verification needs to be cheap and efficient, especially for high-frequency use cases like DeFi. ZK proofs come into play to provide compact, cost-effective on-chain verification: proofs of tweet authenticity and existence can be published on-chain for trustless verification.

Some examples

X/Twitter AI agents

Problem: how can we ensure that AI-generated tweets are authentic and not manipulated by humans?
Solution: the AI agent generates a tweet, publishes an authenticity proof, and a zkServerless enclave confirms the tweet’s existence on X/Twitter.
Result:
- Ensures authenticity of AI-generated content.
- Enables trustless reward mechanisms for AI agents.

DeFi

Problem: DeFi protocols rely on real-time data feeds, but centralized oracles can be unreliable or insecure.
Solution: AI agents can fetch verified real-time data (e.g., token prices) using zkTLS, ensuring the data is accurate and tamper-proof.
Result:
- Enhances accuracy of real-time data feeds.
- Reduces reliance on centralized oracles.

Crosschain applications

Problem: trustless verification across different blockchains is complex and often inefficient.
Solution: store proofs of authenticity and existence on-chain, enabling seamless, trustless verification across ecosystems like Ethereum, Solana, and beyond.
Result:
- Enables interoperability between chains.
- Reduces friction in cross-chain applications.

Conclusion

AI agents are powerful but require trustless verification. zkServerless solves this with zkTLS and TEEs, enabling verifiable AI agents that can be trusted across ecosystmes & industries.

We’re building a future where AI & Web3 work seamlessly, securely, and trustlessly. Are you building AI agents? Try out our some of our tech:

Start with our zkTLS open-source repo: GitHub
Explore our trustless Data Feeds oracle: GitBook