Developers · Updated 27 Oct, 10:23 pm IST
Property Finder fixes evaluation bias when moving vision AI to Amazon Bedrock
Why it matters for readers: It’s an example of how bad testing data—not model quality—can block better AI choices.
- Property Finder discovered 96.8% of their evaluation labels were inherited from a single model’s predictions rather than human verification.1
- The biased ground truth made alternative models appear to underperform regardless of actual quality.1
- The team uncovered the issue during migration of their vision AI workload to Amazon Bedrock while seeking a more cost-effective option.1
- Property Finder processes tens of thousands of property images daily across MENA and evaluates 11 quality attributes per image.1
- They rebuilt unbiased ground truth and used evolutionary prompt optimization to select the right model on Bedrock.1
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