AI Benchmarks
Evaluate AI Models with Custom Benchmarks
Turn model evaluation into clear, repeatable metrics that map to your unique business outcomes.
Turn model evaluation into clear, repeatable metrics that map to your unique business outcomes.
why custom ai benchmarks matter
LLM leaderboards and off-the-shelf benchmarks provide useful reference points, but they rarely reflect the unique challenges of your business. HumanSignal makes it easy to design custom benchmarks that align with your specific domain, data, and success metrics.
Expose model blind spots early, preventing costly errors in production.
Compare models side by side using your data, not someone else’s leaderboard.
Track improvements over time and link model performance directly to business outcomes.
Demonstrate quantifiable, transparent evidence that your AI systems meet internal standards and compliance requirements.
AI benchmarks are standardized, repeatable tests for AI systems.
Test suite tailored to your use case
How the benchmark evaluates tasks
HumanSignal provides tools to turn your proprietary data into repeatable, trustworthy benchmarks:
Work with SMEs to define the tasks and evaluation criteria.
Run your chosen models on the benchmark dataset.
Use automated metrics and/or human evaluations for accuracy, reliability, and alignment.
Expand benchmarks as new requirements or edge cases emerge.
case study
In our recent blog tutorial, we evaluated GPT-5 against a custom benchmark built from realistic use cases.
Key insights:
This demonstrates why custom benchmarks are essential for organizations that want model performance tied to business outcomes.
Whether you’re deploying LLMs into production or exploring model fit,
HumanSignal gives you the framework to
measure what matters.