> For the complete documentation index, see [llms.txt](https://www.aicontrolarchitecture.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.aicontrolarchitecture.org/author.md). # About the Author I'm **Ankush Chowdhary**, founder of **Neo Control** ([neocontrol.ai](https://neocontrol.ai)), and I created the AI Control Architecture. I built it from a single conviction: enterprises are handing probabilistic systems deterministic authority over data, decisions, and actions, faster than they can control it, and the next serious AI failure will come from that gap, not from a model "becoming evil." The AI Control Architecture is my answer: a way to make an AI's authority **bounded, provable, and reversible** before it is granted, not after it fails, and to keep the human judgment that cannot be outsourced to the machine. I have spent 30 years building and operating enterprise security at hyperscale across three continents, including at **IBM**, **HPE**, **AWS**, and the **HOYA Group**. I hold two patents in AI cybersecurity, created the **Recursive Cyber Defense Framework (RCDF)** alongside ACA, authored the official *Google Cloud Professional Cloud Security Engineer* exam guide, and hold a US O-1A for extraordinary ability in cyber and AI security. I built the AI Control Architecture to distill that practitioner experience into an openly licensed body of work: a way to give AI real authority over enterprise data, decisions, and actions without losing control of it. Neo Control ([neocontrol.ai](https://neocontrol.ai)) is where I operationalize it: classifying what an AI can see, decide, and do, proving those controls hold, and intervening when AI acts. ## Connect * Neo Control: [neocontrol.ai](https://neocontrol.ai) * LinkedIn: [linkedin.com/in/ankushchowdhary](https://linkedin.com/in/ankushchowdhary) * Email: ## Stewardship The AI Control Architecture is published **openly, under a permissive license**, stewarded by Neo Control, with the aspiration of becoming a shared standard for AI control. Neo Control maintains the specification and its reference implementation, but the AI Control Architecture is intended to be independently implementable, inspectable, and adoptable by any organization. Contributions, corrections, and jurisdiction-specific mappings are welcome through the repository. My goal is not to own it. It is to be its originator and steward, and to see it become the common control language beneath how enterprises, vendors, and institutions govern AI. *** *Version 0.1.0 ยท Licensed under the terms in* [*LICENSE.md*](/project/license.md)*.* --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://www.aicontrolarchitecture.org/author.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.