Image Analysis
Test vision models on your actual images at scale. Find the model that's accurate, consistent, and cost-effective for your specific use case.
You need to process thousands of images. Which model actually works?
Vision AI is powerful, but every use case is different. What works for generic image recognition might fail completely on your specific domain—building inspections, product quality, medical imaging. You need to test at scale, but existing tools can't handle it.
01
Tool timeouts block large-scale testing
Existing eval tools have 15-minute windows. With 50-second processing per image, you can only test a handful before getting cut off.
02
Non-deterministic outputs break trust
Run the same image twice, get different answers. Some models are more reliable than others—but you can't measure variance without proper testing.
03
Generic scoring doesn't fit your domain
A roof condition score of '3' vs '4' isn't completely wrong—it's partially correct. You need custom distance-based metrics, not binary pass/fail.
04
Domain experts write prompts, engineers run tests
Your architects or inspectors know what to look for. But they can't run experiments themselves—it's constant back-and-forth.
How Lovelaice solves this
Run benchmarks on thousands of images across multiple models. Define custom metrics that match your domain. Measure variance to find reliable models.
Upload your validated image dataset
Bring images with known ground truth—the dataset you've already validated with domain experts. Lovelaice handles 5-20 images per test case.
Define custom metrics per property
Roof material, condition score, building features—each property can have its own scoring logic, including distance-based partial matches.
Run each test multiple times
Test the same input 3-5 times per model. See variance across runs. Identify which models are deterministic vs unpredictable.
See results first, then dig into failures
Side-by-side model comparison view. See which models perform best, then drill into specific failures to iterate on prompts.
Where teams use this
Real estate & property
Building inspections, roof analysis, condition assessments. Process hundreds of thousands of addresses reliably.
Insurance
Damage assessment, claims processing, property valuation from satellite and street view imagery.
Manufacturing & QA
Product defect detection, quality control, assembly verification.
Infrastructure
Asset inspection, maintenance detection, infrastructure monitoring.
What teams discover
Proper benchmarking reveals which models are actually reliable for production use.
Explore other use cases
Discover more ways Lovelaice can help your team.
Find the vision model that actually works
Stop guessing based on generic benchmarks. Test on your images, with your metrics, at your scale.