AI & LLM Product Testing
An AI that hallucinates isn't a feature — it's a liability your customers will notice first.
AI products unlock enormous potential, but they also introduce failure modes that traditional QA simply doesn't catch. A chatbot giving wrong answers, a model that starts talking nonsense after an update, or a security gap via prompt injection — your users will find these before you do. Get test coverage built specifically for AI products: output quality, security probing, and ongoing tracking of whether your model still performs after every change. The result: AI you can stand behind, and customers who trust you for it.
What's included
- LLM output quality — relevance, accuracy, and hallucination detection before your users encounter them
- Security testing — prompt injection and adversarial scenarios that stress-test your model's resilience
- Regression monitoring — after every model update, know immediately whether quality has slipped
- AI product integration — UI/UX flows, edge cases, and chatbot evaluation across real conversation scenarios
- RAG system testing — relevance of retrieved documents, grounding of responses in source data, and confabulation detection
- Voicebot and voice AI — intent recognition testing, edge cases in voice scenarios, and response intelligibility
Who this service is for
- Software companies and SaaS platforms with AI features — chatbot, recommendation engine, or generative content
- Startups and development teams building their own LLM application or product on GPT, Claude, Gemini, or another model
- Companies deploying RAG systems, voicebots, or AI assistants to production