Ai Legal, Regulatory and Compliance

With only 35% of companies having established Ai governance frameworks, organisations face significant risks from unmanaged Ai deployment. We develop enterprise-grade legal and organisational governance structures that enable innovation while ensuring regulatory compliance, ethical standards, and risk mitigation.

  • Risk Classification Assessment
  • Compliance Gap Analysis
  • Implementation Roadmaps
  • Technical Documentation
  • Quality Management Systems
  • Post-market Monitoring
  • Conformity Assessment Preparation
  • Biometric systems compliance (Article 5 prohibitions and requirements)
  • General-purpose AI model compliance (Chapter V requirements)
  • Testing in real-world conditions compliance (Articles 57-61)
  • Data governance and quality requirements (Article 10)
  • Transparency obligations (Article 13)
  • AI system disclosure requirements
  • User information requirements
  • Documentation of AI capabilities and limitations
  • Establishing quality management systems required under Article 17
  • Preparing technical documentation per Annex IV requirements
  • Developing required logging mechanisms and record-keeping systems
  • Creating EU declarations of conformity
  • Supporting registration in the EU database for high-risk AI systems
  • Guidance through conformity assessment procedures
  • Support with notified body interactions
  • CE marking compliance
  • Technical documentation assessments
  • Quality management system assessments
  • Setting up serious incident reporting systems
  • Developing incident investigation procedures
  • Creating corrective action protocols
  • Establishing communication channels with authorities
  • Incident documentation and tracking
  • Designing organizational structures for AI oversight
  • Establishing human oversight measures
  • Developing risk management systems
  • Creating post-market monitoring systems

Setting up incident reporting procedures

  • Model Risk Management
  • Deployment Guidelines
  • Content Moderation Frameworks
  • Output Validation Protocols
  • Prompt Engineering Standards
  • Usage Policies and Controls
  • Copyright and IP Management
  • Implementing right to explanation systems
  • Setting up complaint handling mechanisms
  • Creating remediation protocols
  • Establishing appeal processes for algorithmic decisions
  • Worker/employee information requirements
  • Algorithmic Bias and Discrimination
  • GDPR, CCPA, POPI, etc.
  • Data privacy assessments and compliance
  • Cybersecurity risk mitigation
  • Data breach response and reporting
  • Consumer privacy regulations