An AI agent chains tool calls, model calls, and memory reads into a decision. Standard traces record that chain for the operator. Verifiable agent execution binds each step, and the resulting decision, into a Certified Execution Record with a SHA-256 canonical hash and an independent Ed25519 signature. The record is portable, offline-verifiable, and does not require access to the agent runtime.
Side-by-side comparison
| Dimension | Standard agent trace | Verifiable agent execution (NexArt) |
|---|---|---|
| Scope | Individual spans in the operator's observability tool | Full agent run bound to a single certificate hash |
| Tool calls | Recorded as span events | Included in the protected fields covered by the hash |
| Memory and state | Optional, often sampled | Committed via cryptographic commitments |
| Integrity | Trust the tracing pipeline | Any modification breaks the certificate hash |
| Third-party verification | Not supported | Anyone with the public key can verify offline |
| Multi-step decisions | Reconstructed from spans | Bound as one atomic verifiable unit |
| Data exposure | Typically stores raw tool inputs/outputs | Confidential mode stores only SHA-256 commitments |
Frequently asked
How is verifiable agent execution different from an agent trace?
A trace describes the agent's behaviour to the operator. Verifiable agent execution produces cryptographic evidence of the same behaviour that any third party can check without operator access. The trace helps you debug; the CER lets you defend the decision.
Do I need to change my agent framework?
No. NexArt integrates as an SDK call around agent invocations in LangChain, LangGraph, n8n, and custom runtimes. The agent code stays as it is; the certification wraps the execution boundary.
Add verifiable execution to your AI stack
Produce Certified Execution Records anyone can verify without access to your infrastructure.
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