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Empirical evaluation compares managed and custom LLM architectures for financial data governance, suggesting efficiency improvements.
This paper presents the first controlled empirical comparison of three LLM deployment architectures for financial data governance: (A) platform-managed agents, (B) custom multi-agent factory, and (C) direct API calls. Key finding: platform-level prompt caching reduces context costs by ~90%, making managed agents competitive while delivering 16% higher quality. v2: Fixed broken LaTeX references.
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Karl J. Mollan Neyra (2026) studied this question.
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