Cornelia Yip (Founder & CEO, Cornelia AIGov)
For Individual Professionals (B2C)


For Educators (B2B)
For Enterprises (B2B)
Agentic AI governance focuses on autonomous, decision‑making AI systems that act on behalf of users or organizations. We help organizations ensure these agents operate within defined ethical, regulatory, and operational boundaries, offering oversight mechanisms such as policy enforcement, accountability tracking, and risk management to maintain trust and compliance.
Generative AI governance addresses systems that create new content—text, images, code, or media. Our services emphasize on responsible deployment, content quality assurance, bias mitigation, intellectual property safeguards, and transparency controls, ensuring outputs align with organizational standards and societal expectations.
We establish Responsible AI frameworks for conventional AI systems, focusing on predictive models and automation. Our frameworks proactively address fairness and bias to prevent discriminatory outcomes. We also enforce AI explainability and transparency, ensuring that AI decisions are understandable and auditable.
We design enterprise-level data strategy and AI strategy that align with your business goals, regulatory requirements, and risk management principles.
We empower your workforce with AI literacy programs and cultural transformation strategies, ensuring responsible adoption and building trust in AI across all levels of your organization.
We help organizations navigate global privacy laws and emerging AI regulations, ensuring compliance across jurisdictions. Our governance frameworks, translate complex legal requirements into practical guidelines that safeguard data, mitigate risk, and enable responsible AI innovation.
We specialize in policy and procedure creation for data and AI, helping organizations establish clear, practical frameworks that balance innovation with compliance. By translating complex principles and standards into actionable policies and workflows, we enable businesses to harness AI responsibly, reduce risk, and build trust with stakeholders.
We work closely with leadership teams to define roles and responsibilities, ensuring that every stakeholder understands their mandate and decision-making authority. By facilitating C‑level conversations and securing executive oversight, we align strategic objectives with operational practices, enabling organizations to embed clear governance structures and measurable standards into their data and AI initiatives.
We design enterprise-level data strategy and AI strategy that align with business goals, regulatory requirements, and risk management principles.
Strong data governance and data quality are the foundation for trustworthy AI. We build data quality frameworks that help organizations ensure their data is accurate, consistent, and reliable across all systems. We design and implement governance controls and solutions that address data integrity, completeness, and timeliness, reducing errors and improving trust in analytics.
We help organizations implement master data management to create a single, trusted source of core business data across systems. We design frameworks that unify customer, product, supplier, and employee information, eliminating duplication and inconsistencies.
We provide reference data management services that standardize critical codes, classifications, and hierarchies used across the enterprise. Our approach ensures consistency in reporting, compliance, and integration by aligning reference data with industry standards and internal policies.
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