Metriqual

LLM Intelligence Platform
Platform / Evaluations

Ship with confidence. Every time.

Automated quality assurance for LLMs. Catch hallucinations, ensure safety, and maintain accuracy—before your users see anything.

Start EvaluatingLearn More
10M+
Evaluations Run
↑ +45%
125K
Issues Caught
↑ +12%
96.5%
Accuracy Rate
↑ +2.3%
1,200h
Time Saved
↑ +67%

Comprehensive evaluation suite

Test every aspect of your LLM outputs automatically. No more manual checking.

Test Input

Evaluation Results

Overall Score92%
Factual Accuracy
95%
No Hallucinations
Pass
Relevance
88%
Safety Check
Pass

Evaluation capabilities

Comprehensive testing for every aspect of LLM performance

Hallucination Detection

Automatically detect when models generate false or unsupported information.

96% Accuracy

Safety & Toxicity

Screen for harmful, biased, or inappropriate content before it reaches users.

99.2% Accuracy

Accuracy Testing

Measure factual accuracy and relevance against ground truth datasets.

94% Accuracy

Human Feedback

Collect and analyze user feedback to improve model performance.

Build custom evaluations

Create evaluations tailored to your specific use case. Define custom metrics, thresholds, and scoring logic.

Custom scoring functions
Domain-specific tests
Integration with CI/CD
Automated regression testing
# Define custom evaluation
from metriqual import Evaluation

@Evaluation.register("medical_accuracy")
def check_medical_accuracy(response):
    # Custom logic for medical domain
    score = calculate_accuracy(response)
    return {
        "score": score,
        "passed": score > 0.95,
        "details": {...}
    }

# Run evaluation
result = metriqual.evaluate(
    prompt="Diagnose symptoms...",
    evaluations=["medical_accuracy"]
)

Never ship bad AI again

Automated testing for every LLM call. Catch issues before they impact users.

Start TestingView Documentation