Ethical Impact Assessment
An Ethical Impact Assessment evaluates technologies, especially AI, for risks around fairness, bias, discrimination, and societal harm. It goes beyond compliance, focusing on ethical dimensions such as transparency, inclusivity, and human rights impact.
Conformity Assessment
Conformity Assessments validate that AI and IT systems meet regulatory, technical, and ethical standards. Under the EU AI Act and similar frameworks, high-risk AI systems must undergo conformity checks to ensure safety, accountability, and explainability.
AI Risk Assessment
AI Risk Assessments identify, measure, and mitigate risks that emerge from deploying AI systems. These risks span operational (system failures, scalability), regulatory (non-compliance with AI laws), ethical (bias, discrimination), and reputational (public backlash).
Regulations & Standards Compliance
EU AI Act
South Korea AI Act
UNESCO AI Guidelines
Canada's AIDA
NIST AI RMF
US State - AI Acts
ISO 42001:2023 Audit
ISO 42001:2023 Implementation
SDAIA - AI Ethics Guidelines
AI Security Assessment
An AI Security Assessment evaluates the resilience of AI systems against threats such as adversarial attacks, data poisoning, model inversion, and supply chain compromises. It includes testing the robustness of machine learning pipelines, validating security of training datasets, and reviewing controls for deployment environments.
AI Privacy Assessment
AI Privacy Assessments examine how AI systems collect, use, and process personal data, ensuring compliance with laws like GDPR, DPDP Act, and emerging AI regulations.
The focus is on lawful basis of processing, data minimization, explainability, and risks from automated decision-making. Assessments include reviewing datasets for personal/sensitive attributes, evaluating anonymization or pseudonymization, and analyzing.
