Property Finder removes label bias, picks cheaper, more accurate Bedrock model
What is Fix evaluation bias to unlock better models on Amazon Bedrock?
Property Finder discovered that 96.8% of its vision-AI test labels were copied from the incumbent model, hiding its real performance. By building an unbiased ground-truth set, using evolutionary prompt optimization, and re-evaluating on Amazon Bedrock, they switched to a model that is both more accurate and lower-cost.
Who it is for
ML engineers and product teams using Bedrock should audit their evaluation data to avoid inherited bias and can apply this workflow to get better, cheaper models.