AI Ethics for Fairness is a software application that supports the detection, evaluation and mitigation of bias in AI models by analysing datasets, training models and applying fairness processing techniques.

LLM Vulnerability Scanner and Guardrails provides comprehensive assessment of LLM vulnerabilities and automatic application of optimal defensive techniques to generative AI on LLMs.

Diagnose bias in LLMs (Large Language Models) from various points of views, allowing users to choose the most appropriate LLM.

Intersectional Fairness (ISF) is a bias detection and mitigation technology developed by Fujitsu for intersectional bias, which is caused by the combinations of multiple protected attributes. ISF is hosted as an open source project by the Linux Foundation.

Fujitsu AI Ethics Impact Assessment assesses the potential risks and unwanted consequences of an AI system throughout its lifecycle and produces evidence which can be used to engage with auditors, approvers, and stakeholders. This is a process-driven technology that allows to: 1) map all interactions among the stakeholders and the components of the AI system; 2) assess the ethical risks emerging from such interactions; 3) understand the mechanisms whereby incidental events could occur, based on previous AI ethics incidents.