Ship AI features you can actually trust
BugBrain provides QA for AI chatbots and agents — scoring factual accuracy, probing for prompt injection and jailbreaks, and validating multi-turn conversations — so AI features are tested for the failures that matter before release.
- LLM output is non-deterministic — 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 new ways — hallucinations, prompt injection, broken multi-turn context — that traditional test automation never checks for.
How BugBrain tests AI products
BugBrain scores factual accuracy with judges and golden answers, probes for prompt injection and jailbreaks, validates multi-turn conversations, and gates on aggregate scores instead of brittle exact-match assertions — run 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.
See it on your own app
Start free in minutes — no credit card, no scripts to write.