The revAIsor project aims to tackle the growing concern of trust and transparency in AI systems by developing an AI compliance platform that incorporates auditing using advanced tools. The goal is to create a platform that adopts a compliance-by-design approach, ensuring that AI systems are built with compliance in mind, and a life cycle management process, enabling the continuous monitoring and auditing of AI systems. As AI systems are being used more frequently in critical applications, the need for AI assurance is becoming increasingly important. While AI has the potential to provide significant benefits, it is crucial to ensure that these systems are trustworthy, reliable, and compliant with regulations. Recent studies have shown that AI models can contain biases and inaccuracies, leading to discriminatory outcomes. Moreover, GPT language models, including GPT-3, have been shown to generate biased and inaccurate responses in specific contexts. While these models have impressive capabilities, they are not infallible and require careful monitoring and evaluation to ensure they are providing accurate and unbiased results. Additionally, we will explore using synthetic data to test for simple bias and explainability, enhancing the reliability and robustness of the AI models. To address these issues, AI compliance by design is critical. This means ensuring that AI systems are designed with compliance and ethical considerations in mind rather than trying to retrofit compliance requirements onto existing systems. The revAIsor platform will be built using blockchain and web3 technology, ensuring that audit records are tamper-proof and secure. The platform will use decentralised storage and encryption protocols to store and protect sensitive audit data, making it virtually impossible to hack or manipulate. The platform will offer several features, including data and model validation, explainability analysis, bias and fairness testing, and compliance monitoring. These features will enable auditors to quickly and easily evaluate the quality and reliability of AI systems. By providing auditors with advanced features for data and model validation, bias and fairness testing, compliance monitoring, and explainability analysis, the revAIsor platform will play a critical role in ensuring the trustworthiness and compliance of AI systems. Auditing using advanced tools, such as the revAIsor platform, will enable auditors to evaluate the quality and reliability of AI systems more effectively, ultimately promoting transparency and trust in the development and use of AI technology.