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AI testing checks whether a product built on a model gives correct, safe and stable results. It covers answer quality, behaviour under adversarial input, bias, performance and drift after release. This directory lists 88 companies that state they test AI products for clients.

The same input can give different outputs, so tests assert on properties and score ranges instead of exact values. Quality is measured on evaluation sets, and new risks such as hallucination, prompt injection and bias need their own tests. Testing continues after release because model behaviour can drift.

This directory groups AI testing into 12 services, from LLM output evaluation and RAG pipeline validation to red teaming, bias audits and drift monitoring. The service stated by the most published entries is red teaming and adversarial testing, stated by 56 of 88.

Testing AI products means checking a model-based product itself: its answers, safety and bias. Using AI tools to test software means a QA team uses AI to write or run tests for ordinary applications. This directory lists only the first; vendors whose AI page covers only the second are listed as not published with the code no-ai-page.

Start with the product type and the location you need, then compare the services each vendor states and the facts that have two sources. The directory's comparison pages put two vendors of the same company type side by side. The guide on choosing an AI testing company lists questions to ask every vendor.