Argo-Bench: Why Enterprise Data Agents Need Multi-Table Workflows, Not Just SQL Generation

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Most text-to-SQL benchmarks test whether an agent can generate a single SELECT statement. Argo-Bench asks a harder question: can an agent navigate 235 tables, reconstruct hidden business facts, run statistical analyses, and execute actions that change the state of a simulated enterprise? The answer is no. Frontier models score above 95 on only 34.8% of tasks and average 59.5 points. The gap reveals what breaks when you move from query generation to multi-stage data workflows.

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Argo-Bench: Why Enterprise Data Agents Need Multi-Table Workflows, Not Just SQL Generation

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