Comparison

Protocol-Level Proof vs Inference-Time Guardrails

Guardrails (NVIDIA NeMo Guardrails, Guardrails AI, custom wrappers) filter what models say. Claw EA proves what agents did. These solve different problems and work well together.

Head-to-Head

DimensionClaw EAInference guardrails
Primary functionProof of what happened (receipts + bundles)Prevent harmful outputs (inference-time filtering)
Enforcement pointGateway + tool boundary + policy engineModel input/output layer
Evidence producedSigned receipts, hash-linked event chain, proof bundleBlock/allow decision logs
Offline verifiableYes (Ed25519 + SHA-256)No (requires platform access)
Policy modelDeclarative WPC (signed, immutable, content-addressed)Rule sets and classifiers (mutable)
ScopeFull execution lifecycle (model + tools + side effects)Model I/O only
Tamper evidenceMerkle transparency logApplication logs (mutable)
ComplementaryYes: guardrails can run inside a Claw-receipted pipelineYes: output filtering + proof are orthogonal

Different Layers, Different Questions

Guardrails answer: "Did the model output something harmful?" They operate at the inference layer, filtering or blocking specific patterns in model input and output.

Claw EA answers: "Can you prove what the agent did, where it ran, and under what policy?" It operates at the execution layer, producing cryptographic evidence of the full lifecycle.

An enterprise that deploys guardrails still cannot answer an auditor who asks "prove this agent only accessed approved systems." An enterprise that deploys Claw EA can, because every boundary crossing produces a signed receipt.

Using Them Together

The strongest posture combines both. Run guardrails inside a Claw-receipted pipeline: the guardrail filters harmful outputs, and the receipt chain proves the guardrail was active. A gateway receipt from clawproxy will capture that the model call was mediated, and the tool receipt will capture that the guardrail check ran.

Work Policy Contracts can enforce that guardrail middleware is required for specific models or use cases.

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