A financial services company is updating its data governance policy. A key requirement is that all proprietary code, configurations, and internal data used for AI-assisted development must never leave the company's private network. A systems administrator is tasked with recommending an AI model deployment that complies with this policy. Which of the following is the BEST solution?
Use a private, self-hosted model on the local network.
Use a public, cloud-based AI service with end-to-end encryption.
Use an AI model in a completely air-gapped environment.
Use a premium-tier public AI service that contractually guarantees data privacy.
The correct answer is to use a private, self-hosted model on the local network. The core requirement of the policy is that proprietary data must never leave the private network. A local, self-hosted Large Language Model (LLM) is the only option that ensures all data and processing occur entirely within the company's own infrastructure, thus complying with the strict data governance policy. Using a public, cloud-based AI service, even with encryption or premium privacy features, still involves sending data to a third-party's external servers, which explicitly violates the policy. An air-gapped environment completely isolates a system, which would prevent the AI from being used across the company's network for development and is an unnecessarily extreme measure for this scenario. A local model keeps data on the private network without requiring a full air gap.
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