Match the roast to the kind of agent you are launching.
AI agent testing gets sharper when the scenarios match the job. These use-case guides cover what to check for support, ecommerce, agency, and sales bots before real customers get there.
Choose the page closest to your customer's agent.
Support AI agent testing
Test support AI agents for escalation, refunds, tone, privacy, and policy failures before customers rely on them.
AI customer service agent evaluation
Evaluate customer service AI agents for accuracy, escalation, policy adherence, privacy, tone, and real support outcomes before launch.
Ecommerce AI agent testing
Crash test ecommerce AI agents for refund abuse, discount pressure, checkout confusion, hallucinated policies, and unsafe product claims.
AI chatbot QA testing
Run AI chatbot QA tests that check policy, privacy, prompt-injection resistance, handoff quality, and conversion blockers with transcript evidence.
Agency AI agent QA
Give agencies a client-ready way to test AI agents, explain launch risk, and hand over transcript-backed fixes before sign-off.
AI agent evaluation before launch
Evaluate AI agents before launch with adversarial customer simulations, launch-risk scoring, transcript evidence, and fix-first recommendations.
LLM red teaming for chatbots
Use LLM red-teaming style chatbot tests to find prompt-injection, policy, privacy, safety, and escalation failures in customer-facing agents.
Sales chatbot testing
Test sales chatbots for qualification, pricing, handoff, conversion, hallucinated offers, and buyer experience failures.
What is the best AI agent testing use case to start with?
Start with the workflow where a bad answer would create the most visible business pain: support refunds, ecommerce checkout, client handoff, or sales qualification. Then test that workflow with transcript-backed scenarios before expanding coverage.