# Introduction ### Decentralized Continuous AI Audit Infrastructure Ensuring the accuracy and fairness of LLM models is paramount. As these models become integral to key sectors such as healthcare, finance, and transportation, the risks associated with biases and inaccuracies increase significantly. Traditional methods of LLM evaluation often struggle to catch subtle biases or predict how models will perform in diverse real-world scenarios. This gap not only threatens the reliability of AI applications but also raises serious ethical concerns. Addressing these challenges requires a robust, transparent, and participatory approach. Blockchain tech, with its inherent transparency and immutability, offers a promising solution by enabling verifiable records of evaluation that cannot be altered. Biggest disruptions AI world is seeking is not just another newer LLM model, but the most advanced infrastructure that will enable faster AI disruption with continuous auditing. We are solving this with the most sensible community driven approach who are the actual users of these models and see mistakes always. **EthosAI, incentivizes such mistakes and broader issues in AI led by our committee of reviewers who approve community inputs to translate into biggest database of AI audit configurations incentivizing community back with their inputs.**