AI Guardrails for Web3 Agents
Pre-action validation of LLM/agent outputs against Web3 regulatory corpus
POST /v1/guardrail/validateThe Problem
The EU AI Act high-risk obligations go live 2026-08-02. Web3 AI agents — autonomous DeFi bots, AI-initiated on-chain transactions, LLM-driven governance proposals — fall under Annex III §5 (financial services classification). Article 9 requires documented risk-management systems. Article 14 requires human oversight for high-risk systems. Penalty: €35M or 7% global turnover.
The Solution
SL-2 validates every LLM/agent output against the Web3 regulatory corpus before execution. Three check modes: validate (semantic compliance gate), output-scan (LLM response review), and cross-model verify (Truth Loop L0-L9 for borderline cases). Produces Article 9-compliant audit artifacts.
How It Works
Agent sends proposed action + LLM output to /v1/guardrail/validate
Semantic gate checks against Web3 regulatory corpus (SEC, CFTC, EU AI Act, MiCA)
Borderline verdicts escalate to Truth Loop cross-model verification (L0-L9)
Returns ALLOW / BLOCK / ESCALATE with Article 9 audit artifact
Audit log exportable for EU AI Act Article 12 record-keeping obligation
Who Uses It
Why Not Chainalysis / Elliptic / Generic Tools?
Galileo and Bedrock Guardrails do generic AI safety — no Web3 vertical fluency, no jurisdiction awareness, no EAS attestation. SL-2 speaks MiCA and Article 9 natively.
Ready to deploy SL-2?
Book a 30-minute technical demo. We'll walk through the API, discuss your compliance requirements, and scope an integration.
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