Services
Each engagement is scoped to your system. These are the areas we usually cover, alone or together.
LLM and chatbot evaluation
We measure how well your model or assistant answers the questions your users actually ask.
- Custom evaluation datasets from your documents and use cases
- Accuracy, relevance and hallucination scoring
- Retrieval (RAG) quality: are the right sources found and used?
- Model and prompt comparisons to support vendor or version decisions
Adversarial and security testing
We try to make your AI misbehave, so others can't.
- Prompt injection, including indirect injection through documents and tools
- Jailbreak and policy-bypass attempts
- Sensitive data and system-prompt leakage
- Misuse of connected tools and actions in agentic systems
Bias and fairness review
We check whether outcomes or tone change for different groups of users.
- Paired-prompt testing across demographic and language variants
- Review of refusals, tone and quality differences
- Findings framed to support your own risk and compliance work
Functional, regression and performance testing
We test the AI feature as part of your product, not in isolation.
- End-to-end tests of AI features in web and mobile apps
- Regression suites to rerun when models, prompts or data change
- Latency, throughput and failure handling under load
- Test automation your team can keep running after handover
Reporting and handover
Every engagement ends with something your engineers and decision-makers can use.
- A written report with severity, reproducible examples and recommended fixes
- The test datasets and scripts we built for you
- A walkthrough session with your team
Our testing supports your own assurance and compliance work. It is not legal advice or a certification, and we don't claim it replaces either.