How Property Finder Crushed Evaluation Bias and Slashed Costs by 86%
Property Finder discovered that their vision-AI model was inheriting bias from its predecessor—96.8% of evaluation labels came straight from the old system, masking real accuracy issues. They fixed it by building unbiased ground truth, optimizing prompts evolutionarily, and switching to a cheaper, more accurate model on Amazon Bedrock.
source: [aws/machine-learning-blog]