This repository has been evolved into a specialized framework for Algorithmic Auditing and AI Compliance Monitoring. It provides the necessary infrastructure to log agentic decision-making processes, ensuring full traceability in accordance with ISO/IEC 42001 (AI Management Systems). By capturing the metadata of LLM interactions, it enables real-time monitoring for bias detection and model drift, serving as a critical audit trail for organizations deploying high-risk AI systems under the EU AI Act.
Designed with a Privacy-First mindset, this system incorporates automated PII Redaction and differential privacy layers to ensure that audit logs remain compliant with global data protection regulations like GDPR and CCPA. It demonstrates senior-level AI Leadership by bridging the gap between autonomous agent performance and rigorous regulatory oversight, providing a secure enclave for sensitive operational logs while maintaining the transparency required for institutional accountability.
- Line Breaks: I added a double space between the paragraphs. In Markdown, a single line break often gets ignored, so the double break ensures it looks clean on mobile and desktop.
- Bold for Emphasis: I kept your bolding for the specific regulations (ISO/IEC 42001, GDPR, etc.) as it helps auditors quickly scan for compliance keywords.
- Header Levels: I used #### to keep the sub-headers appropriately sized relative to a main ## Project Name header.
This project was bootstrapped with Create React App.
In the project directory, you can run:
Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
Launches the test runner in the interactive watch mode.
See the section about running tests for more information.
Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about deployment for more information.
Note: this is a one-way operation. Once you eject, you can’t go back!
If you aren’t satisfied with the build tool and configuration choices, you can eject at any time. This command will remove the single build dependency from your project.
Instead, it will copy all the configuration files and the transitive dependencies (Webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except eject will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.
You don’t have to ever use eject. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.
You can learn more in the Create React App documentation.
To learn React, check out the React documentation.
This section has moved here: https://facebook.github.io/create-react-app/docs/code-splitting
This section has moved here: https://facebook.github.io/create-react-app/docs/analyzing-the-bundle-size
This section has moved here: https://facebook.github.io/create-react-app/docs/making-a-progressive-web-app
This section has moved here: https://facebook.github.io/create-react-app/docs/advanced-configuration
This section has moved here: https://facebook.github.io/create-react-app/docs/deployment
This section has moved here: https://facebook.github.io/create-react-app/docs/troubleshooting#npm-run-build-fails-to-minify
This repository has evolved into a specialized framework for Algorithmic Auditing and AI Compliance Monitoring. It provides the necessary infrastructure to log agentic decision-making processes, ensuring full traceability in accordance with ISO/IEC 42001 (AI Management Systems). By capturing the metadata of LLM interactions, it enables real-time monitoring for bias detection and model drift, serving as a critical audit trail for organizations deploying high-risk AI systems under the EU AI Act.
Designed with a Privacy-First mindset, this system incorporates automated PII Redaction and differential privacy layers to ensure that audit logs remain compliant with global data protection regulations like GDPR and CCPA. It demonstrates senior-level AI Leadership by bridging the gap between autonomous agent performance and rigorous regulatory oversight, providing a secure enclave for sensitive operational logs while maintaining the transparency required for institutional accountability.