Governance, Security & Audit

Five Governance Dimensions

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        <h3 class="text-h3 font-bold text-gosign-dark">1. Audit Trail & Traceability</h3>
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          Every AI agent decision generates a complete decision record: input (document, query, data point), model and model version, professional assessment and confidence score, applied rule with rule version, decision path (autonomous or Human-in-the-Loop), result and timestamp.
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          The audit trail is immutable, exportable, and machine-readable. Auditors can trace every agent decision from input to outcome.
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        <h3 class="text-h3 font-bold text-gosign-dark">2. <a href="/en/decision-layer/" class="hover:text-gosign-accent transition-colors">Decision Layer</a></h3>
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          The <a href="/en/decision-layer/" class="text-gosign-accent-text hover:underline">Decision Layer</a> is the architectural layer between AI agent and target system. It makes every LLM decision transparent, auditable, and traceable. The agent analyzes, understands, and evaluates. The Decision Layer documents the decision path and controls routing:
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          <strong class="text-gosign-dark">Autonomous decision:</strong> Where the model can decide securely and in compliance with rules.
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          <strong class="text-gosign-dark">Human-in-the-Loop:</strong> Where bias risk, discrimination potential, or co-determination issues exist - architecturally enforced, not optional.
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          Every human override is documented. Every rule version is assigned. Every decision is reproducible.
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        <h3 class="text-h3 font-bold text-gosign-dark">3. Cert-Ready by Design</h3>
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          Controls are first-class data objects in the system - not documents in a folder. Every control has: technical implementation (RLS policy, trigger, API check), automatic evidence generator, evidence history with timestamp, status, version, auditor view with drill-down to the concrete implementation.
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          The system proves itself. Auditors see the live status in the Auditor Portal.
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          <a href="/en/governance/cert-ready/" class="text-gosign-accent-text font-semibold hover:text-gosign-accent-hover">Cert-Ready by Design &rarr;</a>
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        <h3 class="text-h3 font-bold text-gosign-dark">4. Employee Oversight & Co-determination</h3>
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          AI agents in enterprise environments require oversight by employee representation bodies. Built for the most demanding standard globally - German co-determination law - the Gosign architecture addresses this as a design principle: governance frameworks (collective agreements, works agreements, or company policies) as explicit constraints in the Decision Layer. Employee representatives can trace what the agent does, why, and when a human intervenes. Templates, logging, role concepts, and audit trail are part of the architecture.
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          <a href="/en/governance/co-determination/" class="text-gosign-accent-text font-semibold hover:text-gosign-accent-hover">Employee Oversight & Co-determination &rarr;</a>
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        <h3 class="text-h3 font-bold text-gosign-dark">5. EU AI Act</h3>
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          The Gosign architecture addresses the central requirements of the EU AI Act as a design principle: Transparency (Art. 13) - Decision Layer documents every decision path. Human oversight (Art. 14) - Human-in-the-Loop architecturally enforced. Record-keeping (Art. 12) - complete audit trail with timestamps, input hashes, model versions. Risk management (Art. 9) - Governance layer with bias monitoring, confidence tracking, anomaly detection.
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          <a href="/en/governance/eu-ai-act/" class="text-gosign-accent-text font-semibold hover:text-gosign-accent-hover">EU AI Act Readiness &rarr;</a>
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