IQHub provides expert AI governance solutions to help organizations operate AI safely and in full regulatory compliance.
2 Weeks
Rapidly assess your organization's AI risk level and design a concrete action roadmap to ensure both regulatory compliance and operational stability.
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8-12 Weeks
Build a comprehensive framework from AI governance strategy development to control design, operational process definition, and standard documentation.
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4-6 Weeks
Implement an integrated risk management system to continuously monitor and respond to anomaly detection, bias, drift, and policy violations in AI systems.
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3-4 Weeks
Transform audits from events into continuous control capabilities. Minimize regulatory and reputational risks through mock audit-based pre-verification.
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2-4 Weeks
Systematically strengthen your organization's risk identification, control design, and audit response capabilities through AI RMF-based role-specific training and workshops.
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Monthly Retainer
Implement an audit-ready continuous compliance operating model by systematizing AI RMF-based periodic reviews, internal control assessments, and evidence management processes.
Learn MoreWe go beyond meeting FSS AI evaluation criteria and FSC audit requirements — we design a structurally verifiable AI governance framework built for supervisory scrutiny. By integrating model risk management, explainability, data controls, and internal audit evidence into a unified architecture, we deliver a regulatory-grade AI operating model aligned with board-level risk accountability.
We redesign medical AI compliance not as a checklist exercise, but as a governance structure directly linked to your organization's clinical accountability framework. By integrating clinical risk management, data integrity assurance, algorithmic bias controls, and traceable decision records, we build a responsibility-driven AI operating architecture that meets regulatory standards while keeping patient safety at the center.
We redefine the safety, quality, and reliability demands of industrial AI environments as a risk-based operating model — not just a technical implementation. We design a control architecture that governs production data flows, predictive maintenance models, and automated control systems end-to-end, with continuous validation built in through real-time performance monitoring, quality verification, model drift detection, and operational anomaly response.
We treat customer data protection and AI ethics not as compliance checkboxes, but as core business imperatives that sustain brand trust. By unifying privacy protection, bias and discrimination management, and decision transparency into a single governance structure, we design an AI framework that operates within real business controls. We also align audit readiness and executive accountability to build a responsibility-driven AI operating model that goes beyond regulatory compliance to continuously earn customer trust.
AI governance is a management operating model that structurally controls organizational risk. IQHub designs regulatory-grade AI governance architecture with supervisory agency evaluation standards built in.
Cross-map global and domestic AI regulatory frameworks and internalize supervisory agency evaluation perspectives to systematize proactive regulatory alignment and risk interpretation capabilities.
Transform policies into executable control structures and build an evidence-centric integrated control architecture capable of audit response.
Operate AI governance as a continuous compliance model, establishing a risk management process that enables ongoing review and improvement.
