AI Quality Assurance
AI Assurance
Evaluates generative AI, RAG, agents and model-powered features for quality, factuality, safety, security, consistency, privacy, cost and governance.
What every engagement includes
Executive summary for business stakeholders
Confirmed scope, assumptions and exclusions
Defect register with severity, priority and evidence
Release recommendation: Go, Conditional Go or No-Go
Service catalogue
15 services
15 services
15 services
15 services
15 services
14 services
4 services
AI Quality Assurance
AI Assurance
Response quality testing
Hallucination and factuality testing
RAG and knowledge-base testing
Prompt and conversation testing
AI safety testing
AI security testing
Bias and fairness testing
Agent and tool-calling testing
Structured-output testing
AI performance and cost testing
Robustness and consistency testing
Model regression testing
Privacy and data-leakage testing
AI governance and compliance testing