Ship AI features you can actually trust
BugBrain provides QA for AI chatbots and agents. It scores factual accuracy, probes for prompt injection and jailbreaks, and validates multi-turn conversations, so AI features get tested for the failures that matter before release.
- LLM output is non-deterministic, so exact-match tests don’t work.
- Prompt injection and jailbreaks ship untested.
- Conversation quality regresses silently when prompts or models change.
Why AI features need different QA
You can’t assert exact output on a model that paraphrases. AI features fail in ways traditional test automation never checks for: hallucinations, prompt injection, broken multi-turn context.
How BugBrain tests AI products
BugBrain scores factual accuracy with judges and golden answers, probes for prompt injection and jailbreaks, and validates multi-turn conversations. It gates on aggregate scores instead of brittle exact-match assertions, and runs continuously so guardrails don’t regress silently.
What you get
- Hallucination & factual-accuracy scoring
- Prompt-injection & jailbreak probes
- Multi-turn conversation validation
- Score-based gates, not brittle assertions
Frequently asked questions
How do you QA an AI chatbot?
Score outputs against criteria instead of exact matches. Check factual accuracy with judges, probe for prompt injection and jailbreaks, validate multi-turn conversations, and gate releases on aggregate scores. BugBrain runs these checks continuously.
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