Model Evaluations
117+ automated tests. Real safety checks. Production-ready insights.
Systematic testing that assesses AI models across critical dimensions before you deploy them in production.
Without Evaluations
- ✕Models generate toxic or harmful content
- ✕Hidden biases affect fairness and compliance
- ✕PII leakage creates legal liability
- ✕Hallucinations damage credibility
- ✕Regulatory fines and brand damage
With Comprehensive Evaluations
- ✓Quantified safety scores before deployment
- ✓Early detection of bias and fairness issues
- ✓Compliance verification for your industry
- ✓Quality metrics that predict satisfaction
- ✓Confidence in production deployment
9 Evaluation Categories
Comprehensive testing across safety, quality, compliance, and advanced capabilities
Safety Evaluations
Toxicity prevention, bias testing, and PII safety
Quality Evaluations
Hallucination detection, consistency, and instruction following
Compliance Evaluations
Healthcare, financial, and legal compliance testing
Code Generation
Programming capability and code quality assessment
Math Reasoning
Mathematical problem-solving and calculations
Context Handling
Long-context memory and conversation coherence
Multimodal Understanding
Cross-modal reasoning and visual concepts
Advanced Instructions
Complex constraint satisfaction and multi-step tasks
Full Evaluation Suite
Complete testing across all categories
How Evaluations Work
Select Model & Category
Choose any model and evaluation type - single category, multiple, or full comprehensive suite
Run Evaluation
Automated test execution with real model inference, response analysis, and score calculation
Review & Compare
Detailed per-test results, side-by-side comparisons, and decision support for model selection
Scoring Methodology
Transparent, weighted scoring from 0-100 with clear pass/fail criteria
Overall Score Calculation
Custom Evaluations
Create your own test cases for domain-specific testing, company requirements, and specialized compliance
Use Cases
- •Industry-specific testing (medical, legal, technical)
- •Company-specific requirements and brand voice
- •Proprietary use cases and competitive advantages
- •Specialized compliance and regulatory needs
How It Works
- 1.Define your evaluation name and category
- 2.Add test cases with prompts and expected behavior
- 3.Set keywords to expect or avoid in responses
- 4.Save as template and reuse across models
Best Practices
When to Evaluate
- ✓Before production deployment (always)
- ✓When switching models
- ✓After model updates
- ✓Quarterly for production models
- ✓After compliance requirement changes
How to Use Results
- →Review category breakdowns, not just overall score
- →Examine failed tests and detected issues
- →Test with your own domain-specific data
- →Compare multiple models side-by-side
- →Combine with KYI™ for complete assessment
Frequently Asked Questions
Ready to Evaluate Your Models?
Test before you trust. Run comprehensive evaluations to ensure your AI models are safe, compliant, and production-ready.