What it does
The repository includes task schemas, labeled rows, a runner, and calibration checks for document routing and transaction coding.
Benchmarks & research
PadFlow contributes anonymized land-development decisions for testing confidence-aware models such as Jev.
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The repository includes task schemas, labeled rows, a runner, and calibration checks for document routing and transaction coding.
Your developer can borrow this testing script to measure different AI models. They can check how well a model sorts incoming documents or labels business expenses. The tool records how often the AI finds the correct answers. It also tracks how sure the AI is when making a choice.
To start the test, your developer runs the provided script. They will need an access key that connects the tool to a service like OpenRouter. The included public examples are very small. They help you compare models, but they cannot prove a system is fully ready.