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End-to-end evaluation methodologies for LLMs, Agentic AI, Traditional ML, and Multimodal systems. Built for enterprises, regulators, and auditors.
Specialized evaluation for AI agent systems using our proprietary frameworks
Hallucination Detection
Prompt Refinement Analysis
Static Trace Analysis
Knowledge Retrieval Analysis
Planning Error Analysis
Failure Detection
Cost Monitoring
Jailbreaking Perturbation Testing
Statistical Anomaly Detection
Temporal Anomaly Detection
Tool Misuse Analysis
Counterfactual Bias Perturbation
Ethics Drift Analysis
Identity Verification
Tool Invocation Logging
Graphical Visualisation
Entity Causal Analysis
Execution Trace Segmentation
Comprehensive evaluation for large language models
4 tests
5 tests
4 tests
8 tests
3 tests
5 tests
3 tests
4 tests
Custom metrics available for deployment in audits
Evaluation methodologies for classic machine learning systems
5 tests
3 tests
4 tests
4 tests
4 tests
Evaluation for vision language models and image recognition systems
4 tests
4 tests