AI Testing Service

AI testing validates software where AI influences generated content, predictions, recommendations, decisions, or user flows. It evaluates functionality, output quality, safety, performance, and production behavior against defined product requirements.

LLM applications are tested with realistic prompt sets, rephrased requests, edge cases, long-context inputs, multilingual scenarios, and unsafe input attempts. Results are evaluated for relevance, consistency, grounding, format adherence, safety, and response time.

RAG testing evaluates retrieval and generation both separately and across the full response flow. QA engineers check whether the system retrieves relevant sources, grounds answers in those sources, provides accurate attribution, and handles missing, conflicting, or outdated information correctly.

Traditional software testing checks product behavior against defined expected results. AI testing also evaluates variable outputs, prompts, datasets, answer grounding, safety, model updates, and behavioral changes across repeated interactions.

The cost depends on the number of AI features, model complexity, target platforms, integrations, test data, compliance needs, and release timeline. QATestLab can prepare a free estimation after reviewing the product scope.

QA should join once the team has product flows, prompts, model behavior expectations, datasets, or integration logic ready for validation. Early involvement helps establish testable requirements, evaluation criteria, and quality thresholds before release.

Yes. AI testing can provide documented evaluation criteria, traceable results, risk records, safety findings, and monitoring recommendations to support internal governance and readiness work aligned with the selected framework. Legal assessment, certification, and formal conformity assessment remain outside QA testing.

Yes. We can support production monitoring, continuous evaluation, regression testing, drift detection, safety reviews, A/B checks, and release validation after model, prompt, retrieval, or data updates.