A production-shaped Python example of using Jev as a typed semantic decision layer inside a deterministic expense-policy workflow.
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Updated
Oct 3, 2026 - Python
A production-shaped Python example of using Jev as a typed semantic decision layer inside a deterministic expense-policy workflow.
Panel-driven recursive QA loop: the agent does the legwork, a tribunal of AI judges (Clef, Clef Flash, Jev, Luna, SubQ) makes every judgment call: discovery, risk triage, failure triage, fix review, regression, done.
Enterprise Standalone Platform for Real-Time Technical Case Studies, Architecture Reviews, Decision Gates & Multi-Agent Deliberation.
Conditional failure-chain framework for adversarial robustness in AI systems
Laya control plane for the agentic SOC — serve, shadow evals + 300-gate, GPU power control, loopback→docker-bridge MCP forwarding
Human-governed decision gates and lineage receipts for durable AI collaboration
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