Fail Closed, Not Open: Designing an AI Gateway for Regulated Enterprises
A developer proposes an AI gateway design for regulated enterprises to manage LLM access and usage across multiple teams.
- A proposed AI gateway design for regulated enterprises aims to manage LLM access and usage across multiple teams.
- The 'fail closed, not open' approach ensures access is denied by default and only granted when explicitly approved.
- The gateway would provide features like request tracking, access logging, and model versioning for effective LLM management.
A developer has suggested a design for an AI gateway to help regulated enterprises manage access to large language models (LLMs) across multiple teams. This approach aims to ensure compliance with regulatory requirements. The proposed gateway would provide a centralized interface for teams to request access to specific LLMs, with a focus on transparency and accountability.
The developer's idea is to create a 'fail closed, not open' system, where access is denied by default and only granted when explicitly approved. This approach is designed to mitigate the risks associated with LLM usage in regulated environments.
The proposed gateway would also provide features such as request tracking, access logging, and model versioning to ensure that teams can manage their LLM usage effectively.
This design concept is relevant to developers, businesses, and investors interested in AI governance and compliance. It highlights the importance of responsible AI development and deployment in regulated industries.
ensures responsible AI development and deployment in regulated industries
compliance with regulatory requirements, risk mitigation
governance and compliance in AI development
regulating ai gateways for enterprise use
- llm
- large language model
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